Don't Let Content Problems Slow Down Your AI Adoption

Posted by Alyssa Verzino on Jul 10, 2019 3:00:00 PM

Artificial intelligence requires training data -- specifically, well-annotated training data -- in order to learn to do its job correctly. In fact, the data you've got lying around probably isn't good enough for AI. You'll need to refine your data before AI can use it.

Thus, we can assume that the majority of companies looking to adopt an AI knowledge assistant like Talla have to put together a world-class knowledge base first, right?

Wrong.

It turns out, the best time to adopt AI is when your content is a mess. And there's no better way to teach AI solutions like Talla to tell good content from bad than to help you clean your content up.

We detail how this works in Talla's newest eBook, "Why You Should Adopt AI Before, Not After, Fixing Your Content Problems".

In this eBook, we discuss the role AI can play in reorganizing and refining your content library, the advantages of involving AI in your content cleanup, and the kind of features you can expect from an AI assistant that helps develop your new, improved content library and knowledge base.

Don't let bad content or broken knowledge bases stop you from adopting the AI solutions you need. "Why You Should Adopt AI Before, Not After, Fixing Your Content Problems" shows you how to accelerate your AI adoption and clean up your content problems at the same time.

If you're considering a revamp of your internal documentation and data, download "Why You Should Adopt AI Before, Not After, Fixing Your Content Problems" to learn how artificial intelligence can help.

And if you're ready to start your journey towards an AI-optimized content library, contact Talla today.

Topics: AI, automation