We evaluated the best generative AI chatbots on the market to see how they compare on cost, feature set, ease of use, quality of output, and support to help you determine the best bot for your business. Here are our picks for the top 21 generative AI chatbots for 2024.

Top Generative AI Chatbot Software

The following chart shows at a glance how the top generative AI chatbot software we evaluated compares on features, query limit, language model, and price—as well as whether the vendor provides a Chrome extension to improve ease of use—to help you determine the best option for your needs.

Freshchat

Best for Automating Self-Service

Overall Rating: 4.6

• Cost: 5
• Feature Set: 5
• Ease of Use: 5
• Quality of Output: 5
• Support: 2.5

Freshchat enables businesses to automate customer interactions through chatbots and also offers live chat capabilities for real-time customer support. It allows companies to manage and streamline customer conversations across various channels and an array of integrated apps.

Freshchat provides features like customizable chat widgets, agent collaboration, customer context, and analytics to track chat performance and customer satisfaction. What distinguishes Freshchat is that it enables sales and marketing—and even support teams—to not only reach customers but to scale those interactions so that the expertise of each live company staffer can be used to converse with many customers.

It does this using its unified agent workspace—which holds a full menu of past conversations—as well as responses from sales, marketing, and support, which an agent can quickly and easily share with an interested customer.

What I found most interesting was that the app has a “Freddy Insights” tool that provides key trends and insights that can be fed into a conversation at opportune moments to prompt a faster decision.

Pros and Cons

Pricing

• Free: Up to 10 agents
• Growth: $23 per agent, per month, or $228 per agent billed annually
• Pro: $59 per agent, per month, or $588 per agent billed annually
• Enterprise: $95 per agent, per month, or $948 billed annually

Features

• Chatbot analytics
• Canned responses
• Customer satisfaction (CSAT) survey and report
• Analytics and reporting
• Multi-channel communication

Crisp Chatbot

Best for Lead Nurturing

Overall Rating: 4.6

• Cost: 5
• Feature Set: 3.5
• Ease of Use: 5
• Quality of Output: 5
• Support: 5

Crisp Chatbot uses artificial intelligence to understand user queries and provide relevant responses. It can handle basic inquiries, provide product information, schedule appointments, and collect customer feedback.

In a growing trend across the AI chatbot sector, the Crisp Chatbot can be customized to match a business’s branding and tone. This is increasingly important in crowded markets where a number of companies are seeking to create a distinct brand to cut through the clutter.

In my conversations with Crispchat, I found the bot extremely helpful at answering my questions. When I asked whether it was good for small businesses, it answered in the affirmative and gave me two salient reasons why—24/7 support and ease-of-use—while also explaining the positive impact these would have on my company’s customer experience.

Pros and Cons

Pricing

• Free: 14-day trial
• Basic: Free forever for two seats
• Pro: $25 per month, per workspace for up to four seats
• Unlimited: $95 per month, per workspace for up to 20 seats
• Enterprise: Contact for custom quote

Features

• Integrations with social apps like Facebook Messenger, WhatsApp, Line, and Instagram
• Conversation routing capability
• Capable of sending multilingual messages
• MagicReply feature provides suggested AI-powered chatbot answers on multiple channels, in several languages

ChatGPT

Best Chatbot for Versatility and Advanced Generative AI Chat Features

Overall Rating: 4.5

• Cost: 4.2
• Feature Set: 4.4
• Ease of Use: 5
• Quality of Output: 3.8
• Support: 5

Developed by OpenAI as part of the GPT (generative pre-trained transformer) series of models, ChatGPT is more than just another natural language processing (NLP) tool designed to engage in human-quality conversations with users. The fact that it was developed by OpenAI means this generative AI app benefits from the pioneering work done by this leading AI company. ChatGPT was the first generative AI app to come to market, launching in November of 2022.

The OpenAI platform can perform NLP tasks such as answering questions, providing recommendations, summarizing text, and translating languages. Aside from content generation, developers can also use ChatGPT to assist with coding tasks, including code generation, debugging help, and programming-related question responses.

I have used ChatGPT for various tasks, from summarizing long articles for research purposes to brainstorming business plans and customer pain points. The output is almost always satisfactory, in-depth, and surprisingly nuanced.

OpenAI has received significant funding from Microsoft and will likely be a leader in the years ahead, both in terms of advanced functionality (depth and versatility of toolset) and its ability to offer technology that’s ahead of the curve.

Pros and Cons

Pricing

• Free: Access to limited features
• ChatGPT Plus: $20 per month
• Enterprise: Contact OpenAI for a custom quote

Features

• Analytics dashboard for enterprise users
• Can understand and generate text in multiple languages
• Offers contextual understanding of extended conversation

Kommunicate

Best for e-Commerce Businesses

Overall Rating: 4.5

• Cost: 3.3
• Feature Set: 5
• Ease of Use: 5
• Quality of Output: 5
• Support: 4

Kommunicate is a generative AI-powered chatbot designed to help businesses optimize customer support and improve the customer experience. One of its chief goals is assisting and completing sales for e-commerce vendors, though it also handles support and the full range of customer queries.

The app provides automated conversational capabilities through chatbots, live chat, and omnichannel customer support. Kommunicate can be integrated into websites, mobile apps, and social media platforms, allowing businesses to engage with customers in real time and provide instant assistance regarding any issue that involves a sale or service.

To assist with this, it offers a FAQ bot to lessen the load of simple, repetitive customer queries. The app’s feature set is far more robust due to a long list of integrations, including OpenAI, IBM Watson, Zapier, and Shopify. It enables easy, seamless hand-off from chatbot to a human operator for those interactions that call for it.

Pros and Cons

Pricing

• Free: 30-day trial
• Lite: $100 month-to-month, or $1,000 billed annually, for up to two teammates; $20 per month for each additional teammate
• Advanced: $200 month-to-month, or $2,000 billed annually, for up to five teammates; $30 per month for each additional teammate
• Enterprise: Custom pricing

Features

• Omnichannel—web, mobile, and social media
• CSAT rating
• Integrations with third-party services
• Can manage customer conversations through bots, live chat, Facebook, WhatsApp, and Line

Claude

Best Chatbot for Long Conversational Memory

Overall Rating: 4.4

• Cost: 5
• Feature Set: 3.5
• Ease of Use: 5
• Quality of Output: 5
• Support: 4

Claude is Anthropic’s free AI chatbot. It runs Claude 3, a powerful LLM known for its large context window of 200,000 tokens per prompt, or around 150,000 words. This gives it one of the best conversational memories around.

To put that in perspective, you can be at the tail end of a conversation the size of Jane Austen’s Pride and Prejudice and Claude will still remember everything that was said, taking your previous questions, file uploads, and responses into account when it responds to your newest prompts.

Its ability to analyze and summarize long documents is excellent, and its answers tend to be more straightforward than those of Chat-GPT. When trying Claude, I was constantly surprised at how concise its answers were to my questions. It felt like I was messaging a true human expert rather than someone going out and finding the answers and regurgitating them back to me. All of this makes Claude a valuable research assistant and creative collaborator

Pros and Cons

Pricing

• Free: Unlimited access to Claude.ai chat
• Claude Pro: $20 per month

Features

• 200,000 token context window (around 500 pages)
• Document summarization and analysis
• Straightforward, clear responses
• Integrates with 600 apps through Zapier

ChatSpot

Best for HubSpot Customers

Overall Rating: 4.4

• Cost: 5
• Feature Set:5
• Ease of Use: 5
• Quality of Output: 5
• Support: 1

ChatSpot combines the capabilities of ChatGPT and HubSpot CRM into one solution. With this tool, you can draft blog posts and tweets and also create AI-generated images, or you can feed it a prompt to enable you to get specific data from your HubSpot CRM.

ChatSpot allows you to perform many functions, including adding contacts and creating tasks and notes. You can also ask it to summarize your CRM data or generate a bar chart of results to understand your company’s performance.

If you’re a HubSpot customer, this chatbot app can be a useful choice, given that Hubspot offers so many ways to connect with third party tools—literally hundreds of business apps. And HubSpot, as its users are well aware, is a platform that offers great functionality for sales reps. This chatbot will likely remain a top candidate for sales and marketing professionals who need improved functionality for customer sales and service.

Pros and Cons

Pricing

• ChatSpot is free

Features

• Uses OpenAI’s GPT-3 and GPT-4
• Integration with ChatGPT, HubSpot, DALL-E, and Google Docs
• Prompt templates and library

Intercom

Best for Handling Support Queries

Overall Rating: 4.3

• Cost: 2.3
• Feature Set: 5
• Ease of Use: 4.5
• Quality of Output: 5
• Support: 5

Intercom AI’s chatbot, Fin, powered by large language models from OpenAI, aims to improve customer experience, automate support processes, and enhance user engagement. The fact that OpenAI (with all of its deep funding and vast expertise) provides Intercom’s underlying engine is clearly a plus.

Intercom can engage in realistic conversations with customers, helping to resolve common issues, answer questions, and initiate actions. It’s an app aimed clearly at the lucrative call center sector. In trying Intercom while acting as a customer seeking assistance, I found that its answers to my questions were helpful and quick. It also felt like there was a human on the other end of the chatbox.

So, what distinguishes it? It has gained wide adoption in the industry and is used by companies ranging from Amazon to Microsoft to Meta. It also offers a “plug and play” chatbot architecture to make setup relatively easy. And Intercom’s “Composer AI” feature enables a call center rep to rephrase a message with one click, turning a single phrase into longer, more detailed response. It can easily summarize entire conversations with one click.

Pros and Cons

Pricing

• Free: 14-day trial
• Fin AI Chatbot: Usage measured in resolutions; $0.99 per resolution.
• Essential: ​​$39 per seat, per month
• Advanced: $99 per seat, per month
• Expert: $139 per seat, per month

Features

• Supports up to 43 languages
• Integrates with Facebook and Instagram
• Answers customer questions based on support content
• Makes article suggestions

Google Gemini

Best Chatbot for Brainstorming Ideas

Overall Rating: 4.3

• Cost: 5
• Feature Set: 5
• Ease of Use: 4.5
• Quality of Output: 5
• Support: 1

Formerly known as Bard, Google Gemini is an AI-powered LLM chatbot built on the PaLM2 (Pathways Language Model, version 2) AI model. You can export your Google Gemini conversation to Google Docs or Draft in Gmail, and the platform allows you to create a shareable public link you can send to a third party, making it useful in collaborative workflows for professional work environments.

It’s a major plus for this app that it’s developed and supported by Google. Admittedly, this app had some difficulties when it was first rolled out. Apparently scrambling to keep up with the phenomenal success of OpenAI’s ChatGPT, Google didn’t iron out all the bugs first. However, Gemini is being actively developed and will benefit greatly from Google’s deep resources and legions of top AI developers.

An important benefit of using Google Gemini is that its supporting knowledge base is as large as any chatbot’s—it’s created and updated by Google. So if your team is looking to brainstorm ideas or check an existing plan against a huge database, the Gemini app can be very useful due to its deep and constantly updated reservoir of data.

Pros and Cons

Pricing

• Free to use

Features

• Can export conversations
• “Google it” function directs you to search engine to provide more information
• Can generate code in 20 programming languages

For an in-depth comparison of two leading chatbots, read our guide: ChatGPT vs. Google Bard: Generative AI Comparison

Jasper

Best Chatbot for Marketing and Sales Teams

Overall Rating: 4.2

• Cost: 2.7
• Feature Set: 5
• Ease of Use: 5
• Quality of Output: 5
• Support: 3

The Jasper generative AI chatbot can be trained on your brand voice to interact with your customers in a personalized manner. Jasper partners with OpenAI and uses GPT-3.5 and GPT-4 language models and their proprietary AI engine. The company also sources from other models such as Neo X, T5, and Bloom.

Jasper’s strongest upside is its brand voice functionality, which allows teams and organizations to create highly specific, on-brand content. This capability is invaluable for marketing and sales teams that need to ensure that all chatbot communications are created with an accurate brand identity.

Out of the box, Jasper offers more than 50 templates—you won’t need to create a chatbot persona from scratch. The wide array of models that Jasper accesses and its focus on customizing for brand identity means this is a choice that marketing teams should at least audition before they make any final selections for an AI chatbot.

Pros and Cons

Pricing

• Creator: $49 per month billed monthly, or $468 billed annually
• Pro: $69 per month billed monthly, or $708 billed annually
• Business: Custom quotes

Features

• Browser extension available
• Supports up to 30 languages.
• Integrates with Zapier, Webflow, Make, Google Sheets, and other tools
• Collaboration capability

For a full portrait of today’s generative AI leaders, see our guide: Generative AI Companies: Top 12 Leaders

Tidio

Best for Small and Medium-Sized Businesses

Overall Rating: 4.2

• Cost: 4.1
• Feature Set: 3.5
• Ease of Use: 5
• Quality of Output: 5
• Support: 4

SMBs looking for an easy-to-use AI chatbot to scale their support capacity may find Tidio to be a suitable solution. Tidio Lyro lets businesses automate customer support processes, reduce response times, and handle tasks such as answering frequently asked questions. You can also use Tidio Lyro to answer customer inquiries, provide automated responses, and assist with basic analytics, allowing you to manage customer support efficiently.

Tidio fits the SMB market because it offers solid functionality at a reasonable price. SMBs are under pressure to offer basic customer service at a low cost; to address this, Tidio allows the creation of a wide array of prewritten responses for simple questions that customers ask again and again. Tidio also offers add-ons at no extra cost, including sales templates to save time with setup.

Additionally, the quality of Tidio’s output was ranked highly in our research, so even as the AI chatbot focuses on affordability, it offers a quality toolset.

Pros and Cons

Pricing

• Free: Up to 50 live chat conversations
• Lyro AI: Starts at $39 per month for up to 200 conversations
• Tidio+: Starts at $499 per month

Features

• Live chat capability
• Integration with Messenger, Instagram, WhatsApp, and email services
• Multi-language support
• Canned responses

Perplexity AI

Best Chatbot for Finding Information on the Internet

Overall Rating: 4.2

• Cost: 4.2
• Feature Set: 4.4
• Ease of Use: 5
• Quality of Output: 5
• Support: 2

Perplexity AI is a generative AI chatbot, search, and answer engine that allows users to express queries in natural language​​ and provides answers based on information gathered from various sources on the web. When you ask a question of Perplexity AI, it does more than provide the answer to your query—it also suggests related follow-up questions. In response, you can either select from the suggested related questions or type your own in the text field.

Perplexity AI’s Copilot feature can guide users through the search process with interactive multiple searches and summarized results. This capability is helpful when exploring complex topics. However, it’s limited to five searches every four hours for free plan users and up to 300 searches for paid users.

Perplexity AI’s strength in searching the internet means this tool is ideal for advanced researchers, from academic to small business to large enterprise, including companies that want to explore how they’re viewed on the web. Because AI enables it to understand your search query at a multi-dimensional level, the app can guide you in directions you might not have thought of, making it “serious researcher’s best friend.”

Pros and Cons

Pricing

• Free: Limited features
• Pro: $20 per month, or $200 per year

Features

• Supports Claude 3, Llama 3, and GPT-4
• Supports 30 languages, including English, Bengali, and Danish
• Text and PDF file upload capability

LivePerson

Best for Conversation Analytics

Overall Rating: 4.1

• Cost: 0.6
• Feature Set: 5
• Ease of Use: 5
• Quality of Output: 5
• Support: 5

The LivePerson AI chatbot can simulate human conversation and interact with users in a natural, conversational manner. Its goal is to discover customer intent—the core of most successful sales interactions—using analytics. To this end, LivePerson offers what it calls a “meaningful automated conversation score,” a metric that attempts to quantify whether a given bot-human interaction was successful in terms of company branding and service.

Additionally, the platform enables you to convert webpages, PDFs, and FAQs into interactive AI chatbot experiences that use natural human language to showcase your brand’s expertise. The bot’s entire strategy is based on making as much content as possible available in a conversational format.

LivePerson can be deployed on various digital channels, such as websites and messaging apps, to automate customer interactions, provide instant responses to inquiries, assist with transactions, and offer personalized recommendations. Significantly, LivePerson is also geared to be embedded in social media platforms, so it certainly aims to reach a large consumer base.

Pros and Cons

Pricing

• Conversational Cloud: Pay-as–you-go, per resolution
• Generative AI: Pay-as-you-go, per resolution

Features

• Conversation builder and orchestrator
• Administrative function includes the ability to create and manage users and skills
• Supports 19 messaging channels, including Facebook, Instagram, X  and WhatsApp.
• Reporting and analytics

Chatsonic

Best Chatbot for Individuals in the Creative Industries

Overall Rating: 4

• Cost: 4.6
• Feature Set: 4.4
• Ease of Use: 5
• Quality of Output: 2.5
• Support: 2

Trained and powered by Google Search to converse with users based on current events, Chatsonic positions itself as a ChatGPT alternative. The AI chatbot is a product of Writesonic, an AI platform geared for content creation. Chatsonic lets you toggle on the “Include latest Google data” button while using the chatbot to add real-time trending information.

The benefit of this “latest data” approach is that it helps individuals in creative fields like advertising and marketing stay up to date on current trends. In contrast, some of the more advanced chatbots use large language models that are updated infrequently, so those looking for this week’s information won’t find what they need.

This current events approach makes the Chatsonic app very useful for a company that wants to consistently monitor any comments or concerns about its products based on current news coverage. Some companies will use this app in combination with other AI chatbot apps with the Chatsonic chatbot reserved specifically to perform a broad and deep brand response monitoring function.

Pros and Cons

Pricing

• Free: Up to 10,000 words per month
• Unlimited: $20 per month billed monthly, or $192 billed annually for one user
• Business: $19 per month billed monthly, or $152 billed annually for one user; up to 200,000 words for GPT 3.5 or 33,333 words for GPT 4.0; add words and users for additional cost
• Enterprise: Custom quote

Features

• Google Docs-like Sonic Editor
• Integration with third-party apps
• More than 100 AI templates

Poe

Best Chatbot for Testing Multiple AI Chatbots

Overall Rating: 3.9

• Cost: 5
• Feature Set: 2.8
• Ease of Use: 4.5
• Quality of Output: 5
• Support: 3.9

Poe is a chatbot tool that allows you to try out different AI models—including GPT-4, Gemini, Playground, and others listed in this article—in a single interface. This is helpful for people who want to pit them against each other to decide which tool to purchase. It’s also great for those who plan to use multiple LLM models and unlock their various strengths for a low price of $16.67 per month when paid annually.

For example, if you plan to use Claude 3 for conversational chat and GPT 4 for content generation—their respective specialties—you can get both by subscribing to Poe rather than paying for each separately, which would cost $40 per month. Developers can also use Poe to build their own chatbots using one of the popular models as the foundation, streamlining the process.

Pros and Cons

Pricing

• Free: Limited access
• Poe Subscription: Starts at $16.67 per month; includes unlimited daily messages and access to exclusive bots like GPT 4 and Claude-3-Opus

Features

• Test and compare multiple popular AI chatbots
• Access multiple AI chatbots like GPT-4 and Claude-3-Opus for low price
• Free version available
• Streamlines building your own AI chatbot using a top LLM as your model

Drift

Best for Businesses that Rely on B2B Sales and Marketing

Overall Rating: 3.8

• Cost: 1.8
• Feature Set: 5
• Ease of Use: 4.5
• Quality of Output: 5
• Support: 2

Drift’s AI is trained on more than 100 million B2B sales and marketing conversations, enabling it to understand and respond to B2B customer inquiries in the conversational manner that’s expected in this market sector—including multi-language support.

The Drift AI chatbot is designed to handle different types of conversations, including lead nurturing, customer support, and sales assistance. It can engage with website visitors and provide relevant information or route inquiries to the appropriate human representative.

Drift can be custom-trained for your B2B business in fine detail, allowing it to learn your brand’s voice and respond in a manner similar to your in-house reps. The B2B market is a specific use case for AI chatbots, and Drift’s focus on this market means that a B2B company can set up a highly functional chatbot that will evolve with the B2B market over time with less work.

Pros and Cons

Pricing

• Premium: $30,000 billed annually
• Advanced: Available upon request
• Enterprise: Custom quote

Features

• User administration with role-based access control
• Live chat, custom chatbots, and AI-powered chatbots
• Meeting scheduler with Google, Office 365, and Teams integration
• Conversation and conversion reporting capability

Ada

Best for Customer Service Automation

Overall Rating: 3.8

• Cost: 0.6
• Feature Set: 5
• Ease of Use: 5
• Quality of Output: 5
• Support: 2.5

Ada is an AI-powered customer service automation platform that uses natural language processing and machine learning algorithms to automate customer service tasks. It is designed to help resolve customer issues, allowing businesses to streamline customer service operations and enhance the customer experience.

There are two ways to use Ada. You can either connect it to your knowledgebase and use generative AI to answer questions grounded in your existing content, or build a hard-coded chatbot using Ada’s natural language understanding and its drag-and-drop platform for a pre-scripted easy and fast setup.

In either case, Ada enables you to monitor and measure your bot KPI metrics across digital and voice channels—for example, automated resolution rate, average handle time, containment rate, CSAT, and handoff rate. It also offers predictive suggestions for answers, allowing the app to stay ahead of customer interactions. Ada’s user interface is intuitive and easy to use, which creates a faster onboarding process for customer service reps.

Pros and Cons

Pricing

• Generative: Contact Ada’s sales team for quote
• Scripted: Contact Ada’s sales team for quote

Features

• Integrations with third-party apps like Shopify, Marketo, and Clearbit
• Automated resolution measurement
• Advanced branding including additional customizations

YouChat

Best Chatbot for Students

Overall Rating: 3.6

• Cost: 5
• Feature Set: 2.9
• Ease of Use: 5
• Quality of Output: 3.8
• Support: 1

Designed by You.com, YouChat is an AI-powered generative chatbot that can summarize text, write code, suggest ideas, compose emails, and answer general questions based on information available on the web.

It also cites its information source, making it easy to fact-check the chatbot’s answers to your queries. YouChat combines various elements in search results, including images, videos, news, maps, social, code, and search engine results on the subject.

In essence, YouChat is a lighter weight tool with an affordable price plan that performs a wide array of tasks—particularly those needed by students. YouChat offers an easy user interface that will appeal to a busy user base that wants to jump right in without undergoing a lot of technical training.

The upside of this kind of easy-to-use app is that, as generative AI advances, today’s fairly lightweight tools will likely offer an enormous level of functionality. So any student or SMB user who starts with it now will probably reap greater benefits in the months and years ahead.

Pros and Cons

Pricing

• Free: Up to 10 AI writing generations
• YouPro: $14.99 per month
• YouPro for Education: $6.99 per month

Features

• Code generator
• Multimodal search capability
• Support for social media profiles

HuggingChat

Best Chatbot for Developers

Overall Rating: 3.3

• Cost: 5
• Feature Set: 2.9
• Ease of Use: 4.8
• Quality of Output: 1.3
• Support: 1

Developed by Hugging Face, HuggingChat is a chatbot based on the Open Assistant Conversational AI Model. It uses NLP and ML algorithms to interact with users and can generate answers to questions, write essays, write code, translate text, and construct emails. The platform has been trained on a large dataset of diverse conversations and can learn from new interactions.

Hugging Face has a large and enthusiastic following among developers—it’s something of a favorite in the development community. Its platform is set up as an ideal environment to mix and match chatbot elements, including datasets ranging from Berkeley’s Nectar to Wikipedia/Wikimedia, and the AI models available range from Anthropic to Playground AI.

Many of these resources may not mean much to the SMB owner or enterprise manager, but they mean a great deal to developers with the expertise to use a deep resource base to customize an AI chatbot. Given that HuggingChat offers such a rich developer-centric platform, users can expect it to grow rapidly as AI chatbots are still gaining more adoption.

Pros and Cons

Pricing

• Free: Limited access
• Pro: $9 per month; gives early access to new features
• Enterprise Hub: $20 per user, per month

Features

• Web search functionality complements response with web content
• Multilingual support
• Can debug and write code and create Excel formulas

Replika

Best for Personal Use

Overall Rating: 3.2

• Cost: 5
• Feature Set: 0.6
• Ease of Use: 5
• Quality of Output: 5
• Support: 1.5

Replika is an artificial intelligence chatbot designed to have meaningful and empathetic-seeming conversations with users. It’s focused more on entertaining and engaging personal interaction rather than straightforward business purposes.

To support its goal, Replika uses natural language processing and machine learning algorithms to understand and respond to text-based conversations. Replika aims to be a virtual friend or companion that learns from and adapts to your personality and preferences.

To better engage, the platform learns your texting style and mimics it. Of course, this means that the longer you interface with the app, the more accurately Replika can mimic your style.

Its motto is “My AI Friend,” and the vendor claims that it can offer dialogue geared for emotional support. To that end, it can engage in a wide variety of topics or even help you learn new things.

Pros and Cons

Pricing

• Free: Limited access
• Month-to-Month: $19.99
• Annual: $69.96.
• Lifetime: $299.99

Features

• Role-playing activities
• Communication through text, pictures, voice calls, and video calls
• Can engage in conversations about a wide range of topics, from personal interests to general knowledge
• Guides users through specific conversation topics such as mindfulness, stress management, or self-care

Bing Chat Enterprise

Best Chatbot for Organizations in the Microsoft Ecosystem

Overall Rating: 3.1

• Cost: 4
• Feature Set: 3.5
• Ease of Use: 1.8
• Quality of Output: 2.5
• Support: 4

Microsoft generative AI tool Bing Chat Enterprise uses GPT-4, which includes a top large language model, to generate natural language responses to user queries. Bing Chat Enterprise has three conversation styles: creative, balanced, and precise. These styles help you set the tone for the expected response to your query.

Bing Chat Enterprise is available in 160 regions. Users can also access it via the Windows Copilot Sidebar, making this app easily accessible. Microsoft is incorporating AI across its product portfolio, so this chat app will likely show up in a number of applications. If your company uses Microsoft, this chat app is a good choice.

The greatest strong point for the Bing Chat tool is that it’s produced by Microsoft, arguably the leader in AI today. The company’s deep resources and dominant technical expertise in AI software should support this chat app very well in the years ahead.

Microsoft is also skilled at serving both the consumer and the business market, so this chat app can be configured for a variety of levels of performance. It has the depth of features needed to serve the SMB market and large enterprise.

Pros and Cons

Pricing

• Free: Available to customers licensed for Microsoft 365 E3, E5, Business Standard, Business Premium, or A3 or A5 for faculty
• Standalone: $5 per user, per month

Features

• Versatile mix of conversation styles for different enterprise AI use cases
• Citation capability lets you fact-check output
• Lets users upload images or can generate images

OpenAI Playground

Best Chatbot for Customizability

Overall rating: 3.0

• Cost: 4.15
• Feature Set: 5
• Ease of Use: 0.55
• Quality of Output: 2.5
• Support: 2

OpenAI Playground was designed by the same generative AI company that created ChatGPT (see above). As such, it is well funded and is continuously improved by some of the best developers in the AI industry. Expect it to stay ahead of the curve in terms of feature set.

The platform is a web-based environment allowing users to experiment with different OpenAI models, including GPT-4, GPT-3.5 Turbo, and others. OpenAI Playground is suitable for advanced users looking for a customizable generative AI chatbot model that they can fine-tune to suit their business needs. This advanced platform enables a vast level of choices and approaches in an AI chatbot.

OpenAI Playground’s focus on customizability means that it is ideal for companies that need a very specific focus to their chatbot. For instance, a sophisticated branding effort or an approach that requires a very proprietary large language model, like finance or healthcare. Given that this app needs true developer expertise to be fully customizable, it is not the best choice for small businesses or companies on a tight budget.

Pros and Cons

Pricing

Priced per 1,000 tokens, about 750 words; varies by model choice. New users get $5 in free credit to use for their first three months.

• GPT-4 Models: Input costs $0.03, output costs $0.06 for 8,000 context; input costs $0.06, output costs $0.12 for 32,000 context
• GPT-3.5 Turbo: Input costs $0.0015, output costs $0.002 for 4,000 context; input costs $0.003, output costs $0.004 for 16,000 context

Features

• Text and completion summarization
• Multiple options for model selection
• Language translation
• Sentiment analysis

Key Features of Generative AI Chatbots

Generative AI chatbots require a number of advanced features to accomplish their many tasks, ranging from context understanding to personalization.

Natural Language Processing

Natural language processing is a critical feature of a generative AI chatbot. NLP enables the AI chatbot to understand and interpret casual conversational input from users, allowing you to have more human-like conversations. With NLP capabilities, generative AI chatbots can recognize context, intent, and entities within the conversation.

Context Understanding

Context understanding is a chatbot’s ability to comprehend and retain context during conversations—this enables a more seamless and human-like conversation flow. A high-quality artificial intelligence chatbot can maintain context and remember previous interactions, providing more personalized and relevant responses based on the conversation history. This enables chatbots to provide more coherent and relevant replies.

Personalization

When shopping for generative AI chatbot software, customization and personalization capabilities are important factors to consider as they enable the tool to tailor responses based on user preferences and history. ChatGPT, for instance, allows businesses to train and fine-tune chatbots to align with their brand, industry-specific terminology, and user preferences.

Multilingual Support

An AI chatbot’s ability to communicate in multiple languages makes it appealing to global audiences. This functionality also allows the chatbot to translate text from one language to another.

How to Choose the Best Generative AI Chatbot For Your Business

The best generative AI chatbot for your company serves your business’s needs and balances quality service with moderately expensive or lower cost pricing based on what works with your budget. Additionally, you’ll need to ensure it has all the necessary AI features you need for your operations, and that these features will be supported going forward.

Organizations in the Microsoft ecosystem may find Bing Chat Enterprise beneficial, as it works better on the Edge browser. ChatGPT does not cite its data sources, but it is one of the most versatile and creative AI chatbots. Google Bard cites data sources and provides up-to-date information, but its response time is sometimes slow. Chatsonic can generate AI images as part of the answer to your query.

What appear to be positives to you may be negatives to another user, and vice versa. The best tool for your business is unique to you—conduct your own research to fully understand the chatbot market, identify your overall AI goals, and shop for a chatbot tool that offers features and capabilities that meet your requirements.

How We Evaluated the Best Generative AI Chatbots

We evaluated today’s leading AI chatbots with a rubric that balanced factors like cost, feature set, quality of output, and support.

Feature Set | 30 percent

Features carry the most weight in our evaluation process. We evaluated various capabilities offered by each generative AI software, including multi-language support, the ability to accept spoken word input, the programmability of the solution, the kind of users it is built for, and customization options.

Ease of Use | 25 percent

We assessed each generative AI software’s user interface and overall user experience. This included evaluating the ease of installation, setup process, and navigation within the platform. A well-designed and intuitive interface with clear documentation, support materials, and the AI chatbot response time contributed to a higher score in this category.

Cost | 20 percent

We reviewed each AI chatbot pricing model and available plans, plus the availability of a free trial to test out the platform. Our research found that some platforms are completely free, while some offer both free and paid plans—a tool like Google Bard gives you access to all its features for free, ChatGPT has a free plan with access to GPT 3.5 capabilities, while GPT 4 requires a monthly subscription. On the other hand, Jasper is a paid chatbot offering a seven-day free trial.

Support | 15 percent

Our analysis also considered the level of support provided by the AI software provider. We assessed the availability and responsiveness of customer support, including customer service hours, email support, live chat support and knowledge base.

Quality of Output | 10 percent

To determine the output quality generated by the AI chatbot software, we analyzed the accuracy of responses, coherence in conversation flow, and ability to understand and respond appropriately to user inputs. We selected our top solutions based on their ability to produce high-quality and contextually relevant responses consistently.

AI Chatbots: Frequently Asked Questions (FAQs)

Below, we provide answers to the most commonly asked questions about AI chatbots.

What Features Should Businesses Look for in AI Chatbots?

Key features to look for in AI chatbots include NLP capabilities, contextual understanding, multi-language support, pre-trained knowledge and conversation flow management. It is also important to look for a tool with a high accuracy rating, even if the questions asked are complex or open-ended.

Why are AI Chatbots Important for Businesses?

AI chatbots are important to businesses because they enhance customer experience and provide various operational benefits, such as improved customer experience, personalized experiences, cost reduction, and increased productivity. Most important: they provide customer service at a far lower cost.

How Can AI Chatbots Enhance Customer Support and Engagement?

AI chatbots can boost customer support by providing 24/7 support, answering common questions, and personalizing interaction based on customer preferences. (For instance, multilingual AI chatbots can communicate in multiple languages, enabling businesses to assist customers from different regions).

What are Traditional Chatbot Builders?

Traditional chatbot builders are tools that help you build conventional rule-based chatbots that stick to a prewritten script. Compared to AI chatbots, they lack natural language processing abilities and feel far less human-like.

Bottom Line: Today’s Top AI Chatbots Take Highly Varied Approaches

Determining the “best” generative AI chatbot software can be subjective, as it largely depends on a business’s specific needs and objectives. Chatbot software is enormously varied and continuously evolving,  and new chatbot entrants may offer innovative features and improvements over existing solutions. The best chatbot for your business will vary based on factors such as industry, use case, budget, desired features, and your own experience with AI. There is no “one size fits all” chatbot solution.

For a full portrait of today’s top AI companies, read our guide: 150+ Top AI Companies

The post 21 Best Generative AI Chatbots in 2024 appeared first on eWEEK.

We tested the top AI writing software to see how it compares on features, pricing, and relative strengths and weaknesses, and to see how well it meets a variety of common use cases. Here are our picks for the best AI writing tools in 2024:

• Copy.ai: Best for Beating Writer’s Block
• Rytr: Best for Copywriters
• Quillbot: Best for Paraphrasing
• Frase.io: Best for SEO Teams and Content Managers
• Anyword: Best for Copywriting Performance Analysis
• Grammarly: Best for Grammatical and Punctuation Error Detection
• Hemingway Editor: Best for Content Readability Measurement
• Writesonic: Best for Blog Content Writing
• AI Writer: Best for High-Output Bloggers
• ContentScale.ai: Best for Creating Long-Form Articles

Comparing the Top AI Writing Tools

The following chart shows at-a-glance how each of the AI writing tools compare on key features, pricing, and availability of a free version.

Copy.ai

Best for Beating Writer’s Block

Copy.ai is an artificial intelligence writing tool designed to help marketers, business owners, and copywriters create various forms of content, including website copy, sales landing pages, email, and social media and blog posts. A boon to content marketers, Copy.ai can automatically conduct SEO research and produce content briefs for writers, streamlining the production process and giving writers guidance.

Another distinctive feature is the thought leadership tool, which automatically turns raw transcripts from interviews with experts into a variety of content assets, including blog posts, social media posts, and newsletters. This dramatically reduces the time it takes to manage content repurposing. The AI writing tool also lets you easily generate copy that aligns with your organization’s persona.

Copy.ai’s in-platform AI chatbot acts as a writing assistant to help beat writer’s block by aiding with brainstorming. For example, I asked it to give me 10 Instagram post ideas for fashion week—it delivered 10 useable ideas I could use as the basis for my social posts. These features enable your team to create and distribute more high-quality content at a lower cost than before.

Pros and Cons

Pricing

• Free: Up to 2,000 words per month
• Starter: $49 per month or $36 per month billed annually for one seat, unlimited words
• Advanced: $249 per month or $186 per month billed annually for up to five seats
• Enterprise: Call for quote

Key Features

• More than 90 copywriting tools included
• Allows you to save and reuse key information via its Infobase feature
• Streamlines SEO content research and brief creation
• Automates content repurposing
• Chat feature enables sales and marketing teams to interact more naturally with AI
• Easy content brainstorming
• Automated sales email writing
• Supports 25 languages

For an in-depth guide to the best AI detection tools, read our guide: AI Detector Tools

Rytr

Best for Copywriters

Rytr is an AI-powered writing tool capable of producing copywriting content on various topics. It’s one of the best AI writing tools for commercial copywriting jobs, where copywriters can use it to automate the creation of post and caption ideas, paragraph content, SEO meta titles, emails, call to actions, replies, and other less complex copywriting assets.

The platform also supports more than 40 other use cases, including generating blog ideas and creating job descriptions. In addition, paid users can create their own use cases by training Rytr for their specific needs.

I tested Rytr out for copywriting and asked it to write me a call-to-action for “A knee pad that protects middle-aged gardeners from hurting themselves.” In response to my prompt, it provided the following two variants:

• “Safeguard your knees, garden with ease.”
• “Safeguard your knees, garden in comfort.”

When I changed the tone from “convincing” to “humorous,” it generated two more options that were not useable out-of-the-box but were still useful for ideation:

• “Kneel with confidence, gardenlords!”
• “Unleash your inner knee-jerk green thumb!”

Overall, Rytr its a useful AI writing tool for copywriters who want to streamline their writing process and come up with more ideas for a variety of content types.

Pros and Cons

Pricing

• Free: Up to 10,000 characters per month
• Saver: $9 per month, or $90 per year; up to 100,000 characters per month
• Unlimited: $29 per month, or $290 per year

Key Features

• Content outline and brief generator
• Chrome extension for improving your writing
• Business idea generator
• Supports copywriting frameworks like AIDA (Attention–Interest–Desire–Action) and PAS (Problem–Agitation–Solution)
• Serves as keyword extractor and generator
• Creates SEO meta descriptions
• Writes calls-to-action

To see top AI software in several categories, see our guide: Best Artificial Intelligence Software

QuillBot

Best for Paraphrasing

QuillBot is an AI-powered writing assistant that, unlike most AI writing tools, focuses on helping you paraphrase and summarize texts. This makes it great for content marketers who often have to write repetitive copy with slight variations across their different content assets or even within the same blog post. For example, instead of writing “automate your administrative accounting tasks” five times, they could use QuillBot to spin that into five different variations.

It also functions as a citation generation tool, making it somewhat useful for academics—but it may not be the best tool for writing essays and research papers, as its output doesn’t consistently pass AI detection tools.

One of QuillBot’s standout features is the ability to choose from nine modes of paraphrased output. You can select from natural, academic, simple, creative, shortened, expanded, and more. As an example, when I prompted it with “The shift to agriculture took thousands of years” in academic mode, the output read, “The transition to an agrarian society spanned several millennia.”

Overall, I found the tool helpful for the outwardly simple but cognitively-taxing task of coming up with new ways to express your ideas in writing.

Pros and Cons

Pricing

• Free: Limited capability
• Premium: $19.95 per month, $13.33 per month billed semi-annually, and $8.33 per month billed annually
• Team: Varies depending on the number of users

Key Features

• Offers Chrome and Word extensions for grammar checking
• Can create source citations in various styles, including APA, MLA, and Chicago
• Nine paraphrasing modes
• Language translator capability

See the very best of today’s generative AI tools: Top Generative AI Apps and Tools

Frase.io

Best for SEO Teams and Content Managers

Frase.io is an AI writing tool designed to help you generate content, provide suggestions for better writing, and optimize articles for SEO. SEO teams and content managers use its templates and outline builder to automatically produce article structures that align with the intent of the searcher, and as a result, increase the chances that the article will rank highly in search engine results pages (SERPs).

Frase’s keyword optimization feature will identify important keywords while you write, make suggestions about how frequently to use them, and track how often they are used in the copy. In addition to keyword tips, it also tells you the ideal number of headings, words, links, and images your articles should have to outrank the competition.

Many of the SEO managers I’ve worked with have used Frase, and I’ve found it especially helpful for optimizing articles for SEO. Watching the SEO “topic score” go up as I make edits is motivating and lets me know I’m on the right track.

Pros and Cons

Pricing

• Trial: $1 for five days
• Solo: $15 per user, per month, or $144 billed annually
• Basic: $45 per user, per month, or $456 billed annually
• Team: $115 per month, or $97 billed annually, for three users; $25 per month for each additional seat

Frase also offers a Pro Add-On that allows unlimited AI content for $35 per month, but does not offer a free plan.

Key Features

• Automated content briefs and outlines
• Content SEO topic scoring capability
• AI written SEO-optimized copy
• Suggestions on keyword optimization
• Google Search Console (GSC) integration

For a detailed look at a leading AI tool, see our guide: ChatGPT: Understanding the ChatGPT ChatBot

Anyword

Best for Copywriting Performance Analysis

Anyword is an AI writing tool that uses machine learning algorithms to generate content and analyze the performance of your copy across various channels. What distinguishes the tool is its Copy Intelligence functionality, which analyzes all of your previously published content to determine which messaging works best on your website, ads, socials, and email channels while clueing you into opportunities to improve your copy.

Its Target Audience feature lets copywriters and marketers define their ideal readers down to their key problems and desires. The AI writing tool will then take this into account when creating and analyzing content.

I found Anyword’s templates extremely helpful for prompting the AI writer to create content that fit my needs. In addition, its self-guided wizards walked me through the information I needed to provide the tool for it to write a blog post or ad campaign for my needs.

Pros and Cons

Pricing

• Starter: $49 per user, per month, or $468 billed annually
• Data Driven: $99 per month, or $948 billed annually for three users
• Business: $499 per month, or $5,988 billed annually for three users
• Enterprise: Custom pricing

Key Features

• Supports up to 30 languages
• Google Chrome extension available
• More than 100 performance-driven templates
• Integrates with Grammarly
• Analyzes copy performance
• Identifies ways to enhance your content
• Adheres to your brand guidelines and target audience data

Grammarly

Best for Grammatical and Punctuation Error Detection

Grammarly is a popular AI writing app that helps you improve your writing by checking for grammatical and spelling mistakes and offering suggestions for enhancing clarity, tone, conciseness, and style. It can be used in a wide range of contexts, including writing emails, reports, essays, or social media posts.

Grammarly can be used as a browser extension, a desktop application, or a mobile app. It’s free to use with limited features, or is available with additional functionalities as a premium subscription.

I’ve found Grammarly’s free version to be extremely useful as an AI editing tool. When I use it to run a final grammar and spelling check on a finished article, it inevitably catches mistakes and offers solutions to fix them. I also use it when writing emails to get the tone right. For example, when emailing a new client, I like to make sure the tone is confident and upbeat—Grammarly’s tone detector helps me achieve that goal.

Pros and Cons

Pricing

• Free: Free version lacks some high-end features
• Premium: $30 per month, or $144 billed annually
• Business: $25 per month, or $300 billed annually

Key Features

• Real-time grammar correction
• Generative AI assistance
• Plagiarism checker
• Advanced clarity suggestions
• Writing tone detector
• Checks grammar, spelling, and punctuation

Hemingway Editor

Best for Content Readability Measurement

Named after a writer known for his concise and simple prose, Hemingway Editor is a writing tool that helps you enhance the clarity, grammar, and readability of your written work. It analyzes text and provides various readability suggestions while highlighting lengthy, complex sentences, excessive adverbs, passive voice, and hard-to-read phrases.

It also assigns a readability score based on the grade level required to understand the text. If the score is too high, content writers can tweak the highlighted sentences to lower the grade level. It is available both as a web-based application and as a desktop app.

I’ve used Hemingway in various capacities and I find that it does its main job of measuring content readability extremely well. Its passive voice detector is my favorite part of the tool.

That said, one of the risks of using an AI editing tool like Hemingway is that, if you follow its suggestions without thinking, you may edit all the rhythm, flow, and personality out of your writing, leaving you with text that’s plain, lifeless, and stilted and suited for a grade level well below your target. Overall, though, I’ve found it a useful tool for making sure blog content is clear and easy to understand while streamlining the editing process.

Pros and Cons

Pricing

The platform is free to use.

Key Features

• Improves writing clarity and conciseness
• Provides a readability score
• Offers alternative word suggestions
• Detects passive voice and excessive adverbs
• Highlights hard-to-read sentences

To see a comparison between two leading AI tools, read our guide: ChatGPT vs. Google Bard

Writesonic

Best for Blog Content Writing

Writesonic uses artificial intelligence technology, specifically natural language processing (NLP), to provide content generation services. It’s one of the best AI writing tools for creating full blog posts.

Writesonic’s AI can generate text based on prompts and user input. In the case of creating a blog post, the wizard will ask you to input information such as article length, keywords, number of headings, topic, and references. Once you’ve approved of the outline, it’ll generate a blog post following these instructions as well as SEO optimization best practices.

While it can be a helpful resource for automated content creation, the quality of generated content may vary, and human editing is often required to ensure accuracy and coherence.

Pros and Cons

Pricing

• Free: 25 generations per month
• Standard: $948 billed annually
• Professional: $2,388 billed annually
• Advanced: $4,788 billed annually

Key Features

• Supports GPT 3.5 and GPT 4
• AI article and blog writer
• Article rewriter
• Sentence expander
• Text summarizer
• Story generator
• Landing page generator

AI Writer

Best for High-Output Bloggers

AI Writer is designed to generate full-length articles in minutes, making it great for high-output bloggers, affiliate marketers, and other people who need articles fast. The platform lets you tailor the AI’s writing to your specific needs by selecting from a long list of recommended keywords for your topic or by manually inputting your chosen keywords. It also suggests sub-topics for your article and helps you structure your content with headings. The tool even cites its sources, displaying journalistic responsibility.

Significantly, it helps you choose topics about which to write. While exploring the platform, I found its topic generator helpful for coming up with article topics using a seed keyword—after prompting with “cold calling,” for example, I received a long list of article keywords and their associated traffic. I then selected Research and Write, a one-click article feature for Cold Calling Leads, and within minutes, I had a basis for a new 600-word article on the topic.

Compared to other AI writing tools, AI Writer’s blog content creation was incredibly quick. However, a note on quality—although AI Writer’s articles are typically well-written, SEO-friendly, and factually correct, they could benefit from a writer’s touch. When I took another pass to add personality, anecdotes, actionable insights, and personal experiences to the copy, it became more appealing to readers and search engines.

Pros and Cons

Pricing

• Basic: $29 per user, per month
• Standard: $49 per month for three users
• Power: $375 per month for 10 users

Key Features

• AI text generator
• SEO editor
• One-click article writer
• Topic generator based on seed keywords (with traffic estimate)
• Can publish to WordPress
• Email composer
• Text rewording capability

ContentatScale.ai

Best for Creating Long-Form Articles

Those looking for an AI writing tool to automatically create long-form articles (over 2,000 words) may find ContentatScale features suitable. After plugging in your topic and further context, it will automatically generate body text, headers, subheaders, a title, bulleted lists, a call to action, and other content elements necessary for effective long-form SEO articles. Not only will it write the blog post—it will also help you come up with ideas, outlines, and relevant keywords in a fraction of the time it would take you to do it manually.

The platform claims to pass AI detection tests, indicating that its generated content mimics human writing and is not easily distinguishable from human-written content. ContentatScale also offers an AI detector solution that ranks as one of best reviewed AI detector tools. Overall, it can be helpful for streamlining the long-form content writing process.

Pros and Cons

Pricing

• Trial: Seven days; $39.99
• Solo: $250 monthly for eight posts
• Starter: $500 per month for 20 posts
• Scaling: $1,000 per month for 50 posts, or $1,500 per month for 100 posts

Key Features

• Keyword, YouTube, podcast, file, blog outputs
• Unique Voice AI Training options
• AI detection capability
• Natural language processing analysis

How to Choose the Best AI Writing Software for Your Business

Choosing the best AI writing tool for your business depends on your AI writing needs and your budget. Our “best-for” use cases are a good starting point to help you decide. In addition, here’s a little more information to help you narrow down your choice:

• Copy.ai and Rytr are best for copywriters and social media managers looking to create short-form content and marketing copy.
• AI Writer, Anyword, and Writersonic are solid options for those looking to create blog posts at scale.
• Frase can help you optimize your content for SEO.
• Grammarly and Hemingway are great options for checking grammar, spelling, and style in your AI-generated content.
• QuillBot and Writesonic may be the best for paraphrasing.

Other factors to consider when choosing the best AI writing tools for your business include features, content quality, user interface, and customization options. Keep in mind that it doesn’t have to be an either-or choice—these tools can be used together for better quality content. For example, you can use QuillBot to paraphrase Anyword’s AI-generated text, Grammarly to correct spelling and punctuation errors, and the Hemmingway App to improve readability.

How We Evaluated the Best AI Writing Tools

We weighed the best tools across five categories. Each category has subcategories that helped us evaluate and compare the AI writing tools.

Feature Set | 30 percent

We assessed the writing capabilities of each tool, including its grammar and spelling correction, sentence rephrasing, and content generation capabilities. We looked for tools that provided accurate and high-quality writing suggestions.

Quality of Output | 25 percent

We evaluated the accuracy and coherence of the generated content produced by each AI writing tool. Tools that could generate clear, well-structured, and error-free content received higher scores.

Cost | 20 percent

We examined the different pricing plans offered by each AI writing tool. This included evaluating the cost of the tool on a monthly or annual basis, as well as any additional fees or hidden costs. We compared each tool’s cost to its value, looking for tools that offer a high level of functionality for a reasonable price.

Support | 15 percent

We assessed the availability and responsiveness of customer support channels, such as email, live chat, or phone support. Prompt and helpful customer support is essential for users who may encounter issues or need assistance with the tool. We also considered the availability of resources and documentation, such as user guides, tutorials, or knowledge bases.

Ease of Use | 10 percent

We looked for tools that have an intuitive and user-friendly interface, allowing users to navigate and utilize the tool’s features easily.

FAQs (Frequently Asked Questions)

Is there a free AI writing tool?

There are plenty of free AI writing tools for content creation, editing, and paraphrasing, including some of those reviewed in this guide. While many of the AI writing tools’ advanced features are restricted to paid users, some writers will find the feature sets in the free plans sufficient for their needs.

How can companies benefit from AI writing tools?

Companies can benefit from AI writing tools by using them to streamline the content creation and editing process across various marketing channels, from social media to SEO blog content. These tools can automatically generate content, help with brainstorming, and suggest edits to improve your copy. Overall, AI writing tools help businesses improve efficiency and increase content marketing output and quality.

Will the content created by AI writing tools seem robotic?

The output of AI writing tools will not have the compelling quality of writing created by human writers. After all, AI writing tools are merely generating text—they’re not thinking, considering personal anecdotes, or making unique connections between ideas. Ultimately, the output of AI writing tools need a human touch to create quality writing.

Bottom Line: Top AI Writing Tools Improve Efficiency

This guide highlights our recommendations for the best AI writing tools to help with your writing needs, but they may not fit every use case perfectly. AI is a tool that can help with idea and content generation and quality improvement, but the best results still require a skilled human touch. When used properly, these tools can boost efficiency and are likely to continue driving changes in any market sector that relies on written content.

Read next: for more assistance with your projects, read our analysis of the best AI chatbots and the top conversational AI tools.

The post 10 Best AI Writing Tools (2024): Enhance Your Writing with AI Magic appeared first on eWEEK.

Certainly some industry observers see these two technologies as an unusual marriage. Business intelligence has a long legacy as a steady platform to rely on for critical data analysis. Major financial decisions are made based on the insights derived from BI applications.

By comparison, generative AI is brand new emerging technology. It offers vast potential – creative output based on mere text prompts – yet sometimes slips into hallucinations. Is this new player a good fit for the starchy world of business intelligence?

Indeed, Phong Le said, the combination of generative AI and BI is nascent. In contrast, “MicroStrategy has been doing business intelligence for over 30 years. We invented the sector as you know it, and there haven’t been that many major innovations in the space in the last 10 years.

“Generative AI has, in my opinion, breathed new life into the BI space and redefined what’s important.” Generative AI’s ability to answer in natural language is useful in both consumer and business contexts, he said. “When you get into the core of what businesses need, they need the answers to numerical data.”

“What I want to know when I ask a question to anyone, an analyst or eventually a gen AI bot…I don’t want a predictive answer – I want the answer. And that’s what gen AI plus BI starts to do – and it solves a problem that isn’t solved today.”

Watch the full interview or jump to select interview highlights below.

Interview Highlights: Phong Le on How Generative AI Improves Business Intelligence

These interview highlights have been edited for length and clarity. 

Adding generative AI is “the biggest change, the biggest additive change to business intelligence that we’ve seen in decades. And look, gen AI has done that for every sector of software, but BI especially. So I am really excited about what the future portends.”

Over the past decade or so, companies have worked to distribute access to BI insights out to the “edge” workers in the corporation, the retail managers, the sales people on the go.

“That came in the form of dashboards and applications,” Le said. “And what people have found is the further you go away from the corporate core, the less likely people are to be comfortable consuming that information in a traditional dashboard or a grid report.”

In other words, a finance person in corporate is comfortable using a BI program, while a retail store manager typically isn’t.

“The store manager is going to use instinct rather than consume the data in a grid report. So what we tried to do over the last three years is [figure out]: how do we get the edge workers to use BI more and more?

“They’re not really reading their emails. So let’s give it to them in the web where they can self-serve. Well, they don’t really go to the web, so let’s give it to them in a mobile device. Now we’re moving somewhere.

“What gen AI does, for the retail store worker, rather than all of these consumption paradigms that they don’t use now, it just lets them ask a question. Natural language: what’s my inventory at this particular point?

“So the employee at the front line can now use BI and data to make decisions. And I think gen AI solves that last mile problem.”

To see a list of the leading generative AI apps, read our guide: Top 20 Generative AI Tools and Apps

The post MicroStrategy CEO Phong Le on Generative AI and Business Intelligence appeared first on eWEEK.

Sectigo issues certificates that enable customers to encrypt traffic between websites and users, among other purposes. “So we not only issued 255 million certificates last year, we moved into the certificate lifecycle management space where we help people automate certificates,” Weiss said.

The company’s automation service includes managing SSL certificates issued by both Sectigo and other certificate vendors, on both the public and private side of the market, ranging from web sites to servers to enterprise workloads.

“When you think about all the servers and hardware that are out there, there are probably 10 times as many machines as there are people. And then when you think about workloads, it’s infinitely greater than the number of machines. So the proliferation of certificates and the need to encrypt traffic and transactions – inside the firewall and outside the firewall into servers – has gone up exponentially over the last five to ten years. It’s really exploded.”

Watch the full interview or jump to select interview highlights below.

Interview Highlights: Kevin Weiss on Key Trends in CLM

This interview took place at the recent RSA Conference in San Francisco. The comments below have been edited for length and clarity. 

The Need for Automation

“The certificate lifecycle management business has been around for probably 10 years,” Weiss said. The problem is that as new certifications have proliferated, certificate management hasn’t kept up. Plenty of companies are still trying to manage their certs using Excel spreadsheets.

“Good old Excel still works very, very well,” he said. “But as you get more and more certificates and as people change jobs or somebody leaves the business, the ability to access the spreadsheet and know when a certificate is going to expire becomes a real challenge. We see this every day.

“If you look at last year, for example, Starlink went offline and it was offline for maybe three or four hours. And the next day Elon [Musk] tweeted that, ‘apologies, we had an expired certificate. We’ll do better.’

“So expired certificates can be very, very problematic for making your services available. Certificates are left out there in an environment and aren’t focused on. And if a bad actor gets a hold of it and begins to compromise your environment, that’s a problem. So the need to know where all of your certificates are in an environment, both on the public facing side and inside the firewall, is critical. And that’s what is really driving the need for this automation.”

Sectigo and SCM Pro  

“What I like to say is: perfection is the enemy of the good enough. And so what Sectigo is trying to do is tackle 80 to 90 percent of what most enterprises need and then help them fill in the gaps later on. For us, the real goal is to continue to make [service] available.

“We just announced a product recently for the small end of the market, which we call SCM Pro, and it’s a certificate lifecycle management solution for small businesses. And basically we automate the entire lifecycle of that certificate. Once you sign up for the service, we’ll manage it forever for you.”

The post Sectigo CEO Kevin Weiss on Certificate Lifecycle Management appeared first on eWEEK.

The problem with today’s rapid tech innovation, of course, is that hackers also benefit from the advances. “As we’ve seen companies move to the cloud, leverage supply chains more, and look at federated identity, the threat actors have paid attention to that,” Reid said.

These threat actors “are really thinking about it more holistically: how can we focus on you and the type of business you do, the type of things you use in your business?

“For example, if I can compromise your supply chain, then I can indirectly influence your ability to do business or conduct operations. The type of threats they’re using are very different than what we saw before. They’re a lot more coordinated. They’re spending more time doing reconnaissance. They’re spending more time doing open source intelligence on you to understand [what solution] you’re using.”

Watch the full interview or jump to select interview highlights below.

Interview Highlights: Paul Reid on Navigating Today’s Cyberthreats

This interview took place at the recent RSA Conference in San Francisco. The comments below have been edited for length and clarity. 

Improve Cybersecurity by Understanding Global Signals

“One of the things we’ve done a great job on, especially most recently, is we always recognize the importance of the endpoint, the laptops, the desktops, the servers, because that’s where the attackers want to get to.

“What we’re seeing now in these next generation threats is that we need to start looking at global adversary signals. So we’re looking at the concept of adversary signal threat intelligence a little bit differently than traditional threat intelligence. Traditional threat intelligence says here’s what the adversaries are doing, here’s the type of TIPs (threat intelligence platform) they’re using, here’s where they’re operating, here’s the verticals they’re focusing on.

In contrast, with the OpenText solutions, “we tell you what’s happening to you now. So you don’t have to guess, am I being attacked by this adversary or a different one? We’re saying: this is the adversary that is attacking you today.

“So when we do that, we give you additional visibility. The big thing is that we want to look beyond our borders, right? So again, EDR does a great job at looking inside. Now we’ve got to look out, and so what we’re asking companies to do is work with us to define what we call a covered space, a protected area of their company that encompasses not just their main corporate, but also things like, do we have content in a content delivery network? Do we have content in a hyperscaler? That’s where the attackers are looking to attack you.

“Now they’re going after all your presences, just not your corporate presences. So with our new product, cyDNA, we define a covered space that encompasses all that. So we can see the incoming and outgoing adversary signals. You have a good idea of what’s taking place.”

The Future of Cybersecurity

It’s likely that cybersecurity will remain challenging into the future, Reid said. “I think that as long as we have adversaries and the adversaries want to harm us, we’re never going to get to that perfect point.”

However, “I think we can make it a lot harder for our adversaries by doing some fundamental things, right? Patch, separation of duty, credential management, all the fundamental things we’ve talked about, encryption at rest, encryption in motion, things like that.

“But also, get yourself the visibility you need to see those threats coming. Use things like adversary signal analysis to understand what your adversaries are doing. It’s still important to have your threat intelligence. You absolutely need that, but you also need to know exactly what’s happening to you. The more visibility you provide yourself, the better chance you have of being protected.”

The post OpenText’s Paul Reid on Preventing Next Generation Cyberthreats appeared first on eWEEK.

A core focus for Intel 471 is providing threat intelligence. “We’re specifically focused on closed sourced, or what some people call ‘dark web threat intelligence,’ which means it’s not so easy to get,” Hoffman said. “We have researchers all around the world who collect information and we process that information into a usable format. We share that with our customers through our platforms.”

Watch the full interview or jump to select interview highlights below.

Interview Highlights: Brandon Hoffman on Operationalizing Threat Intelligence

This interview took place at the recent RSA Conference in San Francisco. The comments below have been edited for length and clarity. 

The Various Flavors of Threat Intelligence

Traditionally, the challenge of threat intelligence is that it comes in a couple of different flavors, Hoffman explained. “There’s malware-related threat intelligence, like indicators. Those are somewhat easier for customers to operationalize because it’s a technical component that you can put in another technical system.

“But real adversary-focused threat intelligence, which is one of the things that we specialize in, is difficult because it generally comes in a report format. So customers need a group of analysts or threat intelligence experts on their side, on their bench, so to speak, working inside the company who know how to dissect that information, process it, and use it and apply it to the problems inside the company itself,” he said. “As opposed to something like a technical indicator, which you could put into a SIEM or a SOAR or a firewall, and it would just do what it needs to do. So that becomes the challenge.

“There’s a lot of rich data available inside of threat intelligence and unlocking the power of it into an operational system is where we’re focused because that’s one of the biggest challenges we see today in the market.”

Selecting a Threat Intelligence Solution

The first hurdle for customers in selecting a threat intelligence platform is selecting what type of solution is best for them, Hoffman said.

“It depends on the problems the customers are facing. So we have things like open source intelligence, we have vulnerability intelligence, there’s malware intelligence, there’s adversary intelligence.

“Depending on the problem that the company is trying to solve and how integrated security operations and threat intelligence itself is into the business fabric, that will help you decide what you need.

“Now on the operational system side, you have things like TIPs, you have SIEMs, you have SOARs, you have EDR. There are a variety of different operational systems. These are the systems that customers run in their network or on their systems that help them enforce security controls.

“So the type of intelligence you have, the problem you’re trying to solve, will tell you what systems you want to apply the problem to.”

The Titan Offering

“Our classic offering is a product we call Titan,” Hoffman said. “That’s a threat intelligence portal where customers can go and set their requirements, what they’re looking for, the things that are important to them. Like, we’re looking for this type of threat actor, or we’re concerned about this type of attack. What information do you have inside of that portal?

“There are a variety of different ways that the information is delivered. Some of it’s just raw information that somebody could consume and use on their side. Some of it’s finished reporting that might go to the executive level. Some of it’s very technical that people will consume through a programmatic interface, an API. That’s our classic offering – there are lots of different types of intelligence in there.”

The post Intel 471’s Brandon Hoffman on Operationalizing Threat Intelligence appeared first on eWEEK.

As an identity and access management vendor, Ping Identity focuses on providing authentication, verification, and authorization technologies to enterprises for both their workforce and their customers.

As Harding explained, the need for these authentication and verification services has increased exponentially as artificial intelligence has allowed attackers a far greater sophistication.

“Traditionally, scams might have involved phone calls or emails to make you believe something,” he said. “Deepfakes and generative AI have made those scams even harder to detect and easier to implement.

“Now, rather than getting an email, you might get a phone call or a voicemail with a deepfake voice that you recognize, or you might see a video with a deepfake face that you recognize. Or even phishing emails that are now so targeted and written in the flavor of the person being imitated.” Stopping these attacks requires smart and thoughtful strategies that are fully current with today’s most advanced technologies.

Watch the full interview or jump to select interview highlights below.

Interview Highlights: Patrick Harding on Preventing Identity Fraud

This interview took place at the recent RSA Conference in San Francisco. The comments below have been edited for length and clarity. 

The Importance of Training  

Deep fake technology and other deceptive technologies enabled by AI are only going to get better, Harding said. “It’s going to become a cat and mouse game.”

“To deal with that, we’re going to have to do a lot to educate and train users to say, look, you are not going to recognize and understand these deepfakes. So you need to be aware of them.

“You now need to think, alright, if that message that I get, that voicemail that I get, is asking me to do something with a higher risk type of transaction – move money, reset a password, something like that – I need to verify and establish explicit trust that this is actually occurring and is necessary. So there’s a lot of education that’s going to have to occur, unfortunately.”

Biometrics and Private Keys: Decentralized Identity

There are already a number of techniques available to boost authentication, Harding said, pointing to technologies like one-time passwords and multifactor authentication.

“But those things tend to have sort of a friction. You’re not going to basically take a photo of your driver’s license every time you want to log in or every time you need to interact with a service.”

To enable users who need less friction, there’s an industry move toward decentralized identity, he explained.

“This is where my identity information is actually stored in my smartphone and can only be unlocked by me. It could be a local biometric, like a face ID type of thing. And that information is secured with a private key, like a cryptographic private key that is extremely difficult to reproduce. So no generative AI is going to reproduce that. And now my identity can be shared from my decentralized identity wallet on my smartphone with different services.

“So if I’m talking to you on the phone and I’m not sure it’s you, alright, I might ask you, Hey, ping me a notification through your wallet to prove that this is really you.

“We think that decentralized identity is really going to help deal with a number of these security issues we’re seeing right now. We’re eliminating the implicit trust that we’ve had on some of these channels where deepfakes are being used and replacing it with sort of an out-of-hand, explicit trust, essentially using decentralized identity to verify.”

The post Ping Identity’s Patrick Harding on Preventing Identity Fraud appeared first on eWEEK.

The report reveals that today’s companies value innovation regardless of the challenges it poses. “As we innovate more, as we start to bring on more of this concept of dynamic computing, bringing in new technology such as IoT, edge computing, and 5G, that just increases the risk,” Lanowitz said. “And organizations are saying, yes, the risk is increasing. Innovation brings increased risk because it’s all new.”

Yet, she explained, even though companies aren’t sure about how to secure their infrastructure in the face of these changes, 74% of survey participants said the benefit of innovation outweighs the risk.

The innovation, Lanowitz said, “gives us better visibility into our supply chain. It delivers better business outcomes, it increases our overall revenues. It gives us a way to collaborate with cybersecurity teams earlier in the lifecycle of a project. So all of these benefits outweigh the risk that is brought in through innovation.”

Watch the full interview or jump to select interview highlights below.

Interview Highlights: Theresa Lanowitz on Key Cybersecurity Trends

This interview took place at the recent RSA Conference in San Francisco. The comments below have been edited for length and clarity. 

Introducing LevelBlue

Lanowitz has long been well known as the Head of Cybersecurity Evangelism at AT&T Business. Just before we spoke, the company underwent a name change:

“Level Blue might be a new name to some of the people out there watching this. What we announced here at RSA was that LevelBlue is an alliance between AT&T and WillJam Ventures. And what LevelBlue offers is a strategic extension of your team, and we do that through our consulting services to help you protect your business intelligence. We do that with our managed security services to help you predict your security investments. And we do that with our LevelBlue threat intelligence teams to help you mitigate risk and really foster innovation.

“And the fourth component of what we do here at Level Blue is the thought leadership research that we’re going to talk about today.”

Increased Budgets vs. Underfunded Security Efforts

The LevelBlue report found that between 2023 and 2024, security spending increased 11%. This significant increase is good news, Lanowitz said.

“However, there’s a downside to that because what we found is that there are these external triggers that say, yes, you can have more funding for cybersecurity. So if there’s a breach, you get more funding for cybersecurity. There are all of these external events to trigger more money released for cybersecurity.

“And what we found out, and this is fascinating because as an industry, we’ve been trying to solve this problem for the past couple of decades: for all the discussion that cybersecurity is now a business requirement, we found out that cybersecurity is still isolated, underfunded, very much a silo, and it’s not part of the strategic business conversations.”

Cybersecurity and Generative AI 

The LevelBlue report asked participants how they are using AI from a cybersecurity perspective, including generative AI, machine learning, and deep learning:

• 61% said, “We are bringing this on slowly,” Lanowitz explained. “We want to make sure we’re doing the right thing with this.”
• 35% said they’re using some form of artificial intelligence. “So think about the very basic uses of artificial intelligence.”
• 21% said they’re engaging with deep learning, “which is more predictive.”
• 15% said they’re using generative AI. Additionally, she noted, generative AI may be deployed in other parts of the business.

Still Unprepared for DDoS: The Need for Business Alignment

The report found that the number one attack type was ransomware. “But then these social engineering types of attacks – email compromise, phishing, stolen credentials, account takeover – come very, very close behind.

“And here’s a really interesting stat. We surveyed seven different industry verticals. We asked them how prepared they felt to remediate these different attack types. Every vertical said they are not prepared to remediate against a DDoS attack or a nation state attack.”

The best strategy for improved security, Lanowitz explained, is better alignment within the business. “The more that cybersecurity team can align their goals with the business and align their budgets as well, the better off we’re going to be from a cyber resilience perspective.

“But it has to start at the top down. The executives have to understand the benefit of cyber resilience. The governance teams have to understand that yes, this is something we need to do. We need to bring in all of the stakeholders.”

The post LevelBlue’s Theresa Lanowitz on New Trends in Cybersecurity appeared first on eWEEK.

Redshift and Databricks provide the volume, speed, and quality demanded by business intelligence (BI) applications. But there are as many similarities as there are differences between these two data leaders. Therefore, selection often boils down to platform preference and suitability for your organization’s data strategy:

• Databricks: Best for real-time data processing and machine learning capabilities.
• AWS Redshift: Best for large-scale data warehousing and easy integration with other AWS services.

Databricks vs. Redshift: Comparison Chart

Databricks Overview

Databricks is a unified analytics platform that provides a collaborative environment for data engineers, data scientists, and business analysts to work together on big data and machine learning projects. It is built on top of Apache Spark, an open-source data processing engine, and offers several tools and services to simplify and accelerate the development of data-driven applications.

Databricks is well-suited to streaming, machine learning, artificial intelligence, and data science workloads — courtesy of its Spark engine, which enables use of multiple languages. It isn’t a data warehouse: Its data platform is wider in scope with better capabilities than Redshift for ELT, data science, and machine learning. Users store data in managed object storage of their choice and don’t get involved in its pricing. The platform focuses on data lake features and data processing. It is squarely aimed at data scientists and highly capable analysts.

Databricks Key Features

Databricks lives in the cloud and is based on Apache Spark. Its management layer is built around Apache Spark’s distributed computing framework, which makes management of infrastructure easier. Some of Databricks’ defining features include:

Auto-Scaling and Auto-Termination

Databricks automatically scales clusters up or down based on workload demands, optimizing resource usage and cost efficiency. It can also terminate clusters when they are no longer needed, reducing idle costs. This feature is particularly beneficial for companies with fluctuating workloads or those looking to optimize cloud costs.

MLflow

Databricks MLflow simplifies the machine learning lifecycle by providing tools to manage the end-to-end ML process—from experimentation to production deployment and monitoring. Data science teams in various industries benefit from MLflow for reproducibility, collaboration, and operationalizing machine learning models.

Delta Lake

Databricks Delta Lake provides reliable data lakes with ACID transactions and scalable metadata handling. It allows for more efficient data management and streamlines data engineering workflows. Companies dealing with large-scale data processing and analytics, especially those with real-time data needs, find Delta Lake valuable. It’s often used in industries like finance, healthcare, and retail.

Databricks Pros and Cons

Databricks offers some great strengths, including its ability to handle huge volumes of raw data, and and its multicloud approach – the platform interoperates with the leading cloud providers. However, a challenge for some: the platform is geared for advanced users; many use cases require real expertise.

Pros

• Databricks uses a batch in-stream data processing engine for distribution across multiple nodes.
• As a data lake, Databricks’ emphasis is more on use cases such as streaming, machine learning, and data science-based analytics.
• The platform can be used for raw unprocessed data in large volumes.
• Databricks is delivered as software as a service (SaaS) and can run on AWS, Azure, and Google Cloud.
• There is a data plane as well as a control plane for back-end services that delivers instant compute.
• Databricks’ query engine is said to offer high performance via a caching layer.
• Databricks provides storage by running on top of AWS S3, Azure Blob Storage, and Google Cloud Storage.

Cons

• Some users, though, report that it can appear complex and not user-friendly, as it is aimed at a technical market and needs more manual input for resizing clusters or configuration updates.
• There may be a steep learning curve for some.

AWS Redshift Overview

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. It allows users to analyze large amounts of data using SQL queries and BI tools to gain insights. Major AWS users would be best on Redshift due to better integration with the entire Amazon ecosystem.

AWS Redshift Key Features

Redshift positions itself as a petabyte-scale data warehouse service that can be used by BI tools for analysis. Some of its best features include:

Columnar Storage and Massively Parallel Processing

Amazon Redshift uses columnar storage and MPP architecture to deliver high performance for complex queries on large datasets. It’s optimized for analytics workloads. Redshift is designed for scalability and performance, making it suitable for enterprises processing terabytes to petabytes of data.

Integration with AWS Ecosystem

Redshift seamlessly integrates with other AWS services like S3, Glue, and IAM, simplifying data ingestion, transformation, and security management within the AWS cloud. Companies heavily invested in the AWS ecosystem and those looking for a fully managed data warehousing solution often choose Redshift.

Concurrency Scaling

Redshift’s concurrency scaling functionality automatically adds and removes query processing power in response to the workload, ensuring consistently fast query performance even during peak usage. This capability is essential for businesses with unpredictable query patterns or those needing consistent performance under heavy loads, such as during business intelligence reporting.

AWS Redshift Pros and Cons

Redshift certainly benefits from being a product of the powerful AWS platform – it offers enormous scalability, and provides a long list of services. However, in some instances it can be expensive, and it doesn’t support all types of semi-structured data.

Pros

• Redshift scales up and down easily.
• Amazon offers independent clusters for load balancing to enhance performance.
• Redshift offers good query performance — courtesy of high-bandwidth connections, proximity to users due to the many Amazon data centers around the world, and tailored communication protocols.
• Amazon provides many services that enable easy access to reliable backups for Redshift datasets.

Cons

• Some users noted that Redshift can sometimes be complex to set up and use at times and ties up more IT time on maintenance due to lack of automation.
• A lack of flexibility in areas, such as resizing, can lead to extra expense and long hours of maintenance.
• It lacks support for some semi-structured data types.

Databricks vs. Redshift: Support and Ease of Implementation

Databricks offers an array of support of advanced use cases, while Redshift tends to be more user friendly.

Databricks

Databricks offers a variety of support options that can be used for technical and developer use cases:

• Databricks can run Python, Spark Scholar, SQL, NC SQL, and other platforms.
• It comes with its own user interface as well as ways to connect to endpoints, such as Java database connectivity (JDBC) connectors.

Redshift

Amazon Redshift is said to be user-friendly and demands little administration for everyday use:

• Setup, integration, and query running are easy for those already storing data on Amazon S3.
• Redshift supports multiple data output formats, including JSON.
• Those with a background in SQL will find it easy to harness PostgreSQL to work with data.

Support and Implementation Winner: Redshift

This category is close, although Redshift is the narrow winner. The platform benefits from its support by AWS. The platform offers relatively accessible ease of implementation.

Databricks vs. Redshift: Integration

Databricks in some cases calls for third party solutions to integrate certain tools, while Redshift is of course a top choice for existing AWS customers.

Databricks

Databricks requires some third-party tools and application programming interface (API) configurations to integrate governance and data lineage features. Databricks supports any format of data, including unstructured data. But it lacks the vendor partnership depth and breadth that Amazon can muster.

Redshift

Obviously, those already committed to the AWS platforms will find integration seamless on Redshift with services like Athena, DMS, DynamoDB, and CloudWatch. The level of integration within AWS is excellent.

Integration Winner: It Depends

Redshift wins in this category, if a company is an AWS client. Obviously, the fact that Redshift is an integral part of the AWS platform helps in this category. In contrast, Databricks integrates with all the major cloud providers (including AWS, of course) and is used by multicloud clients – it clearly is not AWS-dependent.

Databricks vs. Redshift: Pricing

Pricing can vary considerably based on use case: Databricks can be pricey for users who require consultant help, and Redshift charges by the second if daily allotment is exceeded. This category is practically a toss-up.

Databricks

Databricks takes a different approach to packaging its services. Compute pricing for Databricks is tiered and charged per unit of processing, with its lowest paid tier starting at $99 per month. However, there is a free version for those who want to test it out before upgrading to a paid plan.

Databricks may work out cheaper for some users, depending on the way the storage is used and the frequency of use. For example, consultant fees for those needing help are said to be expensive.

Redshift

Redshift provides a dedicated amount of daily concurrency scaling. But you get charged by the second if it is exceeded. Customers can be charged an hourly rate by type and cluster nodes or by amount of byte scanning. That said, Redshift’s long-term contracts come with big discounts.

Roughly speaking, Redshift has a low cost per hour. But the rate of usage will vary tremendously depending on the workload. Some users say Redshift is less expensive for on-demand pricing and that large datasets cost more.

Pricing Winner: Redshift

This is a close one, as it varies from use case to use case, but Amazon Redshift gets the nod.

The differences between them make it difficult to do a full apples-to-apples comparison. Users are advised to assess the resources they expect to need to support their forecast data volume, amount of processing, and analysis requirements before making a purchasing decision.

Databricks vs. Redshift: Security

Like pricing, this category is a close call. Both platform are focused on security.

Databricks

Databricks provides role-based access control (RBAC), automatic encryption, and plenty of other advanced security features. These features include network controls, governance, auditing and customer-managed keys. The company’s serverless compute deployments are protected by multiple layers of security.

Redshift

Redshift does a solid job with security and compliance. These features are enforced comprehensively for all users.

Additionally, tools are available for access management, cluster encryption, security groups for clusters, data encryption in transit and at rest, SSL connection security, and sign-in credential security. These tools enable security teams to monitor network access and traffic for any irregularities that might indicate a breach.

Access rights are granular and can be localized. Thus, Redshift makes it easy to restrict inbound or outbound access to clusters. The network can also be isolated within a virtual private cloud (VPC) and linked to the IT infrastructure via a virtual private network (VPN).

Security Winner: Tie

Both platforms do a good job of security, with strong compliance and monitoring tools, so there is no clear winner in this category.

Who Shouldn’t Use Databricks or AWS Redshift?

Who Shouldn’t Use Databricks 

• Small businesses with minimal data needs: For small businesses with relatively simple data processing and analysis requirements, Databricks may be overly complex and expensive.
• Companies not leveraging cloud platforms: Databricks is tightly integrated with major cloud platforms like AWS, Azure, and GCP. If an organization prefers on-premises solutions or has strict data residency requirements that limit cloud adoption, Databricks may not be the best fit.
• Limited use cases: If the primary focus is on traditional data warehousing and analytics without extensive machine learning or data engineering needs, simpler tools like traditional SQL-based data warehouses might be more suitable.

Who Shouldn’t Use Redshift

• Non-AWS cloud users: Although Redshift is tightly integrated with AWS services, organizations using other cloud providers like Azure or Google Cloud Platform might face challenges in terms of interoperability and data transfer costs when considering Redshift.
• Small-scale or start-up companies: Redshift, being a powerful data warehousing solution, may not be cost-effective for smaller businesses with limited data volumes and budget constraints.

2 Top Alternatives to Databricks & AWS Redshift

Google Cloud Dataproc

Google Cloud Dataproc is a managed Apache Spark and Hadoop service offered by Google Cloud Platform. Similar to Databricks, it provides a fully managed environment for running Spark and Hadoop jobs. However, unlike Databricks, Google Cloud Dataproc supports a broader range of open-source big data tools beyond Spark, such as Hadoop, Hive, and Pig.

Snowflake

Snowflake is a cloud-based data warehouse solution that offers similar capabilities to Redshift. It is known for its simplicity, scalability, and separation of storage and compute. Snowflake automatically handles infrastructure management, scaling, and performance optimization, making it easier to use compared to Redshift.

How We Evaluated Databricks vs. AWS Redshift

To write this review, we evaluated each tool’s key capabilities across various data points. We compared their features, ease of implementation, support, pricing, and integrations to help you determine which platform is the best option for your business.

Our analysis found that Databricks and Redshift tie for features and security, the integration category is a toss-up, and Redshift tops for ease of implementation and pricing – though pricing can vary of course based on utilization.

Bottom Line: Databricks and AWS Redshift Use Different Approaches 

In summary, Databricks wins for a technical audience, and Amazon wins for a less technically savvy user base. Databricks provides pretty much all of the data management functionality offered by AWS Redshift. But it isn’t as easy to use, has a steep learning curve, and requires plenty of maintenance. Yet it can address a wider set of data workloads and languages. And those familiar with Apache Spark will tend to gravitate towards Databricks.

AWS Redshift is best for users on the AWS platform that just want to deploy a good data warehouse rapidly without bogging down in configurations, data science minutia, or manual setup. It isn’t nearly as high-end as Databricks, which is aimed more at complex data engineering, ETL (extract, transform, and load), data science, and streaming workloads. But Redshift also integrates with various data loading and ETL tools and BI reporting, data mining, and analytics tools. The fact that Databricks can run Python, Spark Scholar, SQL, NC SQL, and more will certainly make it attractive to developers in those camps.

The post Databricks vs. Redshift: Data Platform Comparison appeared first on eWEEK.

Our AI jobs salary guide analyzes various AI roles and their average compensation to help you understand the earning potential of each role.

AI Jobs Salary: Comparison Chart

Important Note:  The salary data provided in this guide is sourced from Glassdoor, a reputable platform for job seekers and professionals to access salary insights and company reviews. It’s important to keep in mind that actual salaries may vary slightly based on factors such as the type of company (e.g., startup, mid-sized corporation, large enterprise) and the financial standing of the company at the time of employment.

While the artificial intelligence salary ranges discussed here represent typical compensation levels for AI roles based on industry standards, individual offers may vary based on negotiation, location, specific job responsibilities, and other factors.

Machine Learning Engineer

Machine learning engineers design and implement machine learning algorithms and models to solve specific business problems. Machine learning, because it already has so many practical applications, is generally considered to be one of the fastest growing job titles in the AI landscape. Salary increases can come quickly with experience in advanced skills like machine learning frameworks.

• Early to mid-career: $111,000 – $195,000
• Advanced professional: $147,000 – $284,000.

To learn about ML certifications that can advance your career, see our guide, 6 Best Machine Learning Certifications.

AI Engineer

AI engineers develop and deploy AI systems, including machine learning models and deep learning algorithms. They create algorithms, build AI models, and integrate them into applications and products. The amount you earn leans on your level of experience. AI engineers tend to be employed in the technology, finance, healthcare, and consulting industries.

• Early to mid-career: $102,000 – $204,000
• Advanced professional: $113,000 – $215,000

To learn about AI certifications that can advance your career, see our guide, 30 Top AI Certifications.

Data Scientist

Data scientists are responsible for collecting, analyzing, and interpreting complex data to inform business decisions and strategies. They utilize statistical techniques and machine learning algorithms to derive insights and solve problems. Data scientists require a solid understanding of programming languages like Python or R, as well as expertise in data manipulation and visualization. Experienced data scientists with advanced degrees or specialized skills are in very high demand.

• Early to mid-career: $110,000 – $183,000
• Advanced professional: $119,000 – $229,000

Computer Vision Engineer

A computer vision engineer specializes in developing algorithms and systems that enable machines to interpret and understand visual information from digital images or videos. They work on tasks such as object detection, image recognition, and video analysis. Computer Vision Engineers often collaborate with software developers and researchers to implement and optimize computer vision solutions for various applications such as autonomous vehicles, medical imaging, robotics, and augmented reality. Startups and companies focusing on advanced technologies often offer competitive compensation packages with additional perks like stock options.

• Early to mid-career: $100,000 – $186,000
• Advanced professional: $107,000 – $237,000

Natural Language Processing Engineer

Natural language processing (NLP) engineers develop algorithms and models to enable computers to understand, interpret, and generate human language, or a reasonable facsimile of human speech. They work on tasks such as text classification, sentiment analysis, machine translation, and chatbot development. There are already many highly practical applications of NLP, hence the high salary range at the top end.

• Early to mid-career: $129,000 – $221,000
• Advanced professional: $147,000 – $344,000

Deep Learning Engineer

A deep learning engineer is a specialized role within the broader field of artificial intelligence and machine learning. These professionals focus on developing and implementing deep neural networks and other machine learning algorithms to solve complex problems like image recognition, natural language processing, and autonomous driving. Due to their high-demand skill set, deep learning engineers command competitive compensation.

• Early to mid-career: $109,000 – $189,000
• Advanced professional: $134,000 – $270,000

AI Research Scientist

An AI research scientist is at the forefront of developing new algorithms, models, and techniques to advance the field of artificial intelligence. These professionals typically hold advanced degrees in computer science, mathematics, or related fields and are skilled in areas like machine learning, statistics, and data analysis. Because an AI research scientist may do more theoretical work, the pay is not always as high as other AI specialities.

• Early to mid-career: $129,000 – $194,000
• Advanced professional: $141,000 – $265,000

Business Development Manager

The role of a business development manager in AI is crucial for bridging the gap between technical innovation and market growth. These professionals identify business opportunities, forge strategic partnerships, and drive revenue growth for AI products and services. They play a momentous role in scaling AI solutions and driving adoption among customers. Experience level and track record of successful business development initiatives significantly impact compensation.

• Early to mid-career: $94,000 – $162,000
• Advanced professional: $97,000 – $193,000

To learn about generative AI certifications that can advance your career, see our guide, 12 Best Generative AI Certifications.

AI Product Manager

AI product managers oversee the development and deployment of AI-powered products and solutions. They collaborate with cross-functional teams, including engineers, designers, and marketers, to define product roadmaps, prioritize features, and ensure alignment with business objectives. Experience in product management coupled with AI expertise commands a premium in this role.

• Early to mid-career: $131,000 – $221,000
• Advanced professional: $144,000 – $276,000

AI Consultant

AI Consultants provide expert guidance to organizations seeking to leverage AI technologies for business transformation. They assess client needs, design AI solutions, and oversee implementation to deliver tangible outcomes. Salary for AI consultants can vary widely based on consulting firm, experience level, and project scope. Geographic location also influences compensation, with major consulting hubs offering higher salaries.

• Early to mid-career: $108,000 – $187,000
• Advanced professional: $116,000 – $219,000

How Do I Get Paid More as an AI Professional? 

To increase your earning potential and get paid more as an AI professional, the following strategies can be effective:

Hone Your Skills

Continuously improving and refining your skills is key to increasing your value in the job market. Stay updated with the latest AI trends and technologies in your sector. Take online courses, attend workshops, and actively seek opportunities to deepen your expertise.

Get Certified

Obtaining relevant AI certifications can significantly boost your credentials and marketability. Certifications validate your expertise and demonstrate your commitment to professional development.

Get a Degree

While not always necessary, having an advanced degree (such as a master’s or MBA) can enhance your earning potential, especially in certain fields like business, healthcare, or technology.

Build a Portfolio

Showcase your skills and accomplishments through a strong portfolio. This could include projects you’ve worked on, case studies, articles, or designs. A compelling portfolio demonstrates your capabilities and can differentiate you from other candidates when negotiating higher compensation.

Network

Attend industry events, join professional associations, and connect with peers and mentors in your field. Networking can lead to new job opportunities, referrals, and valuable insights into salary trends.

To see a list of the leading generative AI apps, read our guide: Top 20 Generative AI Tools and Apps 2024.

5 Tips For Negotiating a Higher AI Job Salary

• Research market rates: Before entering negotiations, research the typical salary range for the specific AI role and location. Websites like Glassdoor, PayScale, or industry reports can provide valuable insights into what companies pay for similar positions.
• Highlight your value proposition: During negotiations, emphasize the unique skills, experience, and qualifications you bring. Share specific examples of past projects or achievements demonstrating your AI expertise. Quantify your contributions whenever possible.
• Be prepared to negotiate beyond base salary: Salary negotiations aren’t just about base pay. Consider other compensation components such as bonuses, stock options, healthcare benefits, or professional development opportunities. If the company can’t meet your desired salary, explore different avenues for compensation that may be negotiable.
• Practice effective communication: Approach salary negotiations with confidence and professionalism. Clearly articulate your salary expectations based on market research and your value proposition. Be respectful but assertive, and avoid underselling yourself.
• Know when and how to negotiate: Timing is crucial. Ideally, negotiate after receiving a job offer but before accepting it. Keep the negotiation collaborative rather than adversarial, aiming for a win-win outcome for you and the company.

AI Jobs Salary Outlook: Major Job Growth 

The salary outlook for AI jobs remains promising due to the increasing demand for skilled professionals.

According to ZipRecruiter, the job outlook for AI careers is expected to grow massively as AI becomes capable of accomplishing more tasks. Data from the National Bureau of Labor Statistics shows that employment in computer and information technology occupations is projected to grow much faster than the average for all occupations from 2022 to 2032. The Bureau stated that about 377,500 openings are projected each year, on average.

​​This significant demand underscores the favorable salary outlook for AI professionals as organizations compete to attract top talent with specialized skills in artificial intelligence, machine learning, data analytics, and related fields.

Bottom Line: The Future for AI Salaries is Bright

AI jobs can be highly lucrative, especially for individuals with the right skills, experience, and qualifications. Salaries for AI-related roles vary based on job title, location, industry, level of expertise, and labor market demand-supply dynamics – yet in any case, are some of the highest salaries across the tech sector.

The increasing demand for AI expertise is driving the overall salary outlook upward. Organizations are willing to invest in top talent, and this talent is scarce. To maximize earning potential in AI jobs, professionals should focus on continuous learning, skill development, and staying abreast of industry trends.

For more information about generative AI providers, read our in-depth guide: Generative AI Companies: Top 20 Leaders.

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