Operations | Monitoring | ITSM | DevOps | Cloud

On July 27, 2026, the Digital Omnibus on AI, Regulation (EU) 2026/1744, entered into force and rewrote the EU AI Act's timeline. The high-risk obligations that were due to apply on August 2, 2026, including Article 73 serious-incident reporting, now apply from December 2, 2027 for standalone high-risk systems (Annex III) and August 2, 2028 for AI embedded in regulated products (Annex I). Not everything moved.

Critical event management platforms help organizations identify, communicate, and respond to critical events that threaten people, operations, facilities, IT systems, or business continuity. Modern critical event management software can combine event management, mass notification, situational awareness, incident response, and operational resilience – but not every platform approaches critical event management in the same way. Some CEM platforms focus on risk intelligence and threat monitoring.

Pharmacists manage much more than dispensing medications. Throughout the day, they may be processing prescriptions, communicating with healthcare providers, assisting patients and coordinating with other pharmacy staff, all while managing a steady flow of incoming calls. For pharmacies that accept prescriptions by phone, those calls add another important communication workflow to an already busy environment.

Incident management used to be easier to picture: an alert arrived, a ticket opened, a support team followed a process, and service returned. Today’s incidents move across cloud platforms, SaaS applications, networks, identity services, observability tools, ITSM queues, and engineering teams. The fundamentals still matter, though. Clear process, ownership, communication, and learning matter more when the environment becomes harder to understand. What has changed is how teams execute them.

AI is rapidly becoming a bigger part of how IT Operations teams detect incidents, interpret signals and decide what to do next.

Ask any operations team what question comes up most, and it isn’t about alert routing or escalation logic. It’s the one typed into a channel a dozen times a day: who’s on call for this right now? It’s also one of the slowest questions to answer. The schedule is set up correctly, the overrides are in place, and the group’s ownership is right.

An alert fires. A ticket opens. Someone gets paged. Then the real work begins: gathering context, finding the affected service, deciding who owns the issue, running diagnostics, applying a fix, validating recovery, and documenting the result. Many IT teams assume that an incident management system is simply the application that opens and tracks the ticket. That is part of the job, but it’s not the whole operating model.

AI adoption is now a measurable driver of both uptime and growth. According to PagerDuty’s 2026 State of AI-First Digital Operations report, 75% of organizations actively incorporating AI into digital operations claim to have improved operational resilience and maturity over the past year. The same report suggests AI in operations is also a revenue driver.

Six weeks into my internship, I was handed the biggest project I'd ever worked on: WhatsApp notifications for on-call paging. It was bigger by a large margin. When we scoped it out it broke into about a dozen chunks, each roughly the size of a whole project I'd done before. This is what I learned from it, and what it was like leading a project of that size as one of the most junior engineers at the company.