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The rise of generative artificial intelligence (AI) coupled with automation platforms is about to drive a democratization of the management of IT services that will make it increasingly trivial to manage IT environments at unprecedented levels of scale.

Generative AI makes use of deep learning algorithms and other data science techniques to construct large language models (LLMs). These LLMs can be accessed via a natural language interface to, for example, create code that can be used to automate a process. Over time, that capability will reduce the level of expertise required to manage complex IT environments. Instead of requiring the skills of a DevOps engineer to automate a workflow, an IT administrator will be able to simply describe the workflow required in natural language.

An automation framework can be used to enable an IT administrator to implement a task without any need for them to master a programming language.

Of course, the deeper the appreciation of how applications and IT infrastructure actually work, the more sophisticated workflows will become. The current fly in the proverbial AI ointment is that general-purpose LLMs, such as the ones created for OpenAI’s ChatGPT, are prone to providing suboptimal suggestions. Having been trained using a corpus of data pulled from across the web, not all the recommendations provided are as good as they could be or, for that matter, should be. Examples of mediocre and often insecure code can be found anywhere, all of which were used to train a general-purpose LLM.

The next wave of LLMs will be much more domain-specific. Highly accurate data will be used to train LLMs that are designed to specifically apply AI to a narrow range of tasks. Case in point: An effort by BMC Software to embed generative AI capabilities into the Helix IT management framework based on LLMs the company is developing. Many organizations already employ Helix to automate IT tasks.

As these capabilities become more widely used, IT organizations will discover the number of applications that can be effectively managed by their IT teams has exponentially increased. It’s not likely generative AI will replace the need for IT professionals any time soon, but the economics of IT are about to be fundamentally altered.

Historically, the single largest cost of IT has been the labor required to manage it. Generative AI coupled with automation frameworks will make it possible to build and deploy more applications while reducing the cost of labor—or, at the very least, keeping labor costs relatively stable. Today, deploying additional applications in IT environments is often limited by the fact that there are not enough IT professionals available to manage them alongside the hundreds of applications that have already been deployed. Generative AI, when applied within the context of an automation framework, changes the labor equation on which many IT decisions are based.

Just as importantly, the end user experience will improve as it becomes possible to automate more tasks and also resolve issues faster. End users will soon expect an IT experience that can only be provided when generative AI technologies are embedded into automated workflows.

Naturally, these types of advances will cause as much consternation as they do excitement. A lot of the toil that makes working in IT less appealing will be eliminated in the months and years ahead. The truth is most IT professionals are not going to want to work for organizations that don’t provide them with the tools needed to succeed. The current stress level most IT teams experience today is too high. Generative AI tools coupled with automation frameworks promise to bring a sense of joy and accomplishment that in recent years has, in far too many instances, been missing.

The challenge and opportunity is to determine what processes are best left to machines to automate versus the ones that still require a level of insight that only humans can still provide.