How Generative AI Accelerates Digital Transformation

For example, modern applications were already set to overtake traditional applications in the next few years. But AI threw fuel on that fire and we’re already seeing modern apps breach the apex of dominance in the enterprise portfolio. Because AI is a modern app, and so are the applications being built to take advantage of it.

APIs were already racing toward the top of the priority stack for delivery and security. AI has made everything about APIs a critical priority that’s likely to push general security off the throne. Because most folks are building modern apps (which rely on APIs) and integrating AI services using, you guessed it, APIs.

Generative AI relies on significant compute, storage, and network resources. The kind of resources that are going to amplify the existing hybrid IT operating model and exacerbate the challenges of multicloud estates. The brains behind generative AI—LLMs—are likely to live in a public cloud but there will be some that stay on-premises. And the apps being built to use those LLMs? They’ll be multicloud, too. If you weren’t certain hybrid IT was here to stay, the reality of the resources required for training and inferencing along with a healthy requirement to maintain the privacy of private data is going to solidify the normalcy of the hybrid IT operating model.

Generative AI is accelerating the shift to AIOps as well. It’s the tool AIOps was waiting for, and there’s no dearth of solutions already finding ways to take advantage of this technology’s ability to generate content, code, and queries. In fact, generative AI will take us beyond today’s most mature method—automated scripts—to a state in which the system is able to not only execute the scripts but generate them and the correct policies to boot. It moves the needle for automation from “automated” to “autonomous.” The impact on operations will be profound, but it won’t be fully felt for years. But it’s coming.