If you’re involved in the IT sector, you’ll probably have picked up on the bustle as organisations seeking to capitalise on AI go about getting their data ready to integrate this transformative technology into their way of working. This is a very necessary undertaking, because AI systems need access to accurate, connected, governed and meaningful data if they are to deliver reliable results.

But as enterprises move beyond experimentation and start introducing AI into production environments, another question is becoming increasingly important: is the AI itself ready for the enterprise?

As we know, generative AI produces extraordinarily powerful results, but it can also generate outputs that are inconsistent or just plain wrong. A degree of unreliability is manageable in everyday use, but when AI-generated outputs begin informing critical business decisions, be they operational, financial or strategic, the stakes are considerably higher. 

It’s becoming clear that AI readiness extends beyond the data. To be truly AI-ready, enterprises need to factor in how AI operates within their environment, what it is permitted to access and generate, and what controls need to surround its outputs.

In our latest blog, Intenda CTO Jaco van Niekerk explores this side of AI readiness, outlining the measures organisations should put in place before making the big leap from experimenting with AI to using it confidently in their production environments. If your organisation is preparing to make that leap, this one’s for you.