The AI ​​content creation space is growing

A new dashboard and report from analyst firm AIContentGen analyzed 20 AI-powered writing software solutions. The company says there are now over 50 vendors in the AI ​​content space. Although the providers have many social and community followings, AIContentGen cannot yet estimate the number of blocked customers. AIContentGen Principal Analyst John Cass told us, “The industry has grown rapidly, with over 53 companies, our market map shows, and although the number of companies does not indicate the customers, it does highlight the development of the market. It’s time to start exploring the use of these tools.

A number of solutions have sophisticated functionality, Cass noted. Peppertype.ai, for example, offers content writing specifically for Twitter and LinkedIn as well as regular blogs. Wordhero has over 50 content types in its toolbox, from Amazon product descriptions to video titles. NeuralText automatically optimizes content for SEO. According to a IBM’s recent report, more than half of executives expect AI to change the way content creators do their jobs. This is likely due, in part, to what Cass identifies as the content production gap. “There’s a gap between how much high-quality content marketing and corporate communications teams can produce and what needs to be generated,” he said.

Why we care. It’s been a decade since natural language generation (NLG) proved capable of creating automated sports and business revenue reports. Indeed, as the landscape of AIContentGen shows, Persado started using mathematical models to generate email subject lines in 2012.

There have been concerns about its use in risky scenarios, such as generating instruction or safety manuals or communicating important information to consumers. Cass said: “In the dashboard, we look at where teams need to be careful in using AI content generation tools, and look at issues like internal control process, biases in AI, regulatory compliance and brand identity.”

Read next: John Cass discusses agile marketing with fellow MarTech panelists

In any case, just as neural networks and deep learning have produced rapid advances in AI’s ability to detect patterns, recognize images, and even analyze video, we shouldn’t be surprised to see an acceleration in the development of NLG.

Please note that this story was not written by a robot.


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About the Author

Kim Davis is MarTech’s Editorial Director. Born in London, but a New Yorker for more than two decades, Kim started covering enterprise software ten years ago. His experience encompasses SaaS for the enterprise, urban planning driven by digital advertising data, and the applications of SaaS, digital technology and data in marketing. He first wrote about marketing technology as editor of Haymarket’s The Hub, a dedicated marketing technology website, which later became a channel on established direct marketing brand DMN. Kim joined DMN proper in 2016, as an editor, rising to editor, then editor, a position he held until January 2020. Prior to working in tech journalism, Kim was an editor deputy head of a hyper-local New York Times newspaper. site, The Local: East Village, and previously worked as an editor for an academic publication and as a music journalist. He has written hundreds of New York restaurant reviews for a personal blog and has been an occasional guest on Eater.


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