Under an early access program, PagerDuty, Inc. is making available a tool that brings generative artificial intelligence (AI) capabilities to its IT service management (ITSM) platform.

Jonathan Rende, senior vice president of products for PagerDuty, said PagerDuty Copilot for the PagerDuty Operations Cloud extends previous investments in machine learning algorithms the company has made as part of an ongoing effort to apply AI to ITSM.

Designed to be invoked via Slack, PagerDuty Copilot makes use of multiple large language models (LLMs) to automate tasks ranging from providing summarization of IT incidents to creating code to automate workflows. PagerDuty plans to transparently swap LLMs in and out of its platforms as AI advances continue to be rapidly made, noted Rende.

PagerDuty Copilot provides a level of abstraction for invoking AI models along with appropriate guardrails that make it simpler to manage IT operations without IT teams needing to have AI expertise, said Rende.

The overall goal is to boost the productivity of IT operations teams by eliminating much of the drudgery and toil that conspires to make working in IT tedious, noted Rende. AI technologies are not likely to replace the need for IT personnel as much as they will enable IT teams to focus on tasks that add more value to the business, he added.

It’s now only a matter of time before generative AI capabilities are pervasively applied across both ITSM and DevOps workflows. Less clear is the impact those capabilities will have on the best practices currently relied on to manage those workflows as more tasks are automated. Ultimately, however, AI should make it easier for more organizations to embrace those best practices as the level of skill and expertise required to manage IT at scale is reduced.

In addition, the whole concept of issuing tickets to manage tasks tracked by a central system of record may need to evolve simply because AI has automated requests for service. There will naturally need to be some system of record for tracking requests. Still, ultimately that process will be managed via copilots rather than by a ticket created by an end user that is then tracked via an ITSM platform.

Savvy IT teams, in the meantime, are already moving to determine which tasks and workflows will be automated in anticipation of AI becoming more widely embedded in ITSM and DevOps platforms. Roles and responsibilities within IT teams will inevitably evolve as AI increasingly automates mainly mundane tasks, such as creating reports that many IT professionals would rather not spend time writing.

The biggest IT management platform challenge in the future might not necessarily be adjusting to AI as much as it will be orchestrating requests that are likely to be generated by multiple types of copilots that have been embedded into almost every application.

One way or another, AI is about to transform how IT operations are managed. As disruptive as those advances will be, AI, more importantly, will also enable organizations to manage IT at levels of scale that were previously unimaginable.