Operations | Monitoring | ITSM | DevOps | Cloud

When a major IT incident hits, most organizations know what it costs in the moment: lost transactions and missed SLAs. But according to the findings of our 2026 State of AI-First Operations report, the most significant consequences often don’t show up until long after the incident is closed—in customer relationships, team health, and brand reputation.

A majority of office professionals (72%) believe they understand how to use AI for their job better than the team responsible for managing AI at their company. While it’s encouraging to see employees embrace AI with such confidence, organizations will want to ensure they are providing the tools, guidance, and safeguards needed to help employees use AI safely.

This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey towards autonomous operations. Read on to learn about how PagerDuty Advance Insights Agent (now Generally Available for Microsoft Teams users) builds towards this vision. As AI accelerates development and teams ship more code than ever, operational data is everywhere; insights aren’t.

This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey towards autonomous operations. Read on to learn about how PagerDuty Advance Scribe Agent updates (Generally Available) build towards this vision. When a major operational issue hits, there’s always someone drawing the short straw to take on the most thankless job in incident response: scribing the call. Chances are you were already that someone.

We’ll be rolling out new Slack capabilities to eliminate more manual toil from your incident workflow: click once to promote any alert to an incident, get dedicated channels created automatically, page responders without leaving Slack, and manage all your settings in one place. This is part of our path to autonomous operations: reducing toil, protecting your capacity, and letting you stay in flow. If you’re only using PagerDuty for on-call scheduling, you’re missing the full picture.

AI promise and AI capabilities often diverge, with developers often reporting much faster code production, but not enough change in how incidents are handled. When the rate of change is faster than ever, but the rate of recovery from incidents isn’t moving, developers wind up stuck in firefighting mode. And, when these systems fail, it’s costly. According to PagerDuty’s State of AI-First Operations, over a third of surveyed companies report losing $500K per hour of downtime.

This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey towards autonomous operations. Read on to learn about how PagerDuty’s Shift-Based Schedules (planned GA in May) builds towards this vision. PagerDuty has long been the gold standard for on-call management, helping thousands of teams build the foundations of digital reliability.

Earlier this year at our H1 2026 launch, we announced PagerDuty’s vision for autonomous operations: a future where AI agents learn from every incident, prevent failures before they happen, and progressively automate so teams can focus on innovation instead of firefighting.