Is your on-call rotation quietly burning out top talent?
On-call work is a fact of life for IT operations (ITOps) teams, but as systems complexity and business pressure mount, burnout can quickly spread across teams. When absences increase colleagues’ workload, reduce capacity, and cause cognitive impairment, they inevitably slow incident management workflows.
The good news is that it doesn’t need to be this way.
“By carefully balancing resilience, reliability, and clarity with employee well-being, it’s possible to create on-call schedules that support operational excellence and sustainability.”
By carefully balancing resilience, reliability, and clarity with employee well-being, it’s possible to create on-call schedules that support operational excellence and sustainability. AI can be a useful ally in this process, but establishing sustainable, long-term on-call plans means looking after the humans involved as well as machines.
The pressure is mounting
For modern, digital-centric organizations, extended service downtime can significantly impact customer loyalty, brand reputation, and revenue. The pressure organizations face is huge, whether it’s a retailer staying online during Black Friday or an airline check-in system not buckling under pressure during a busy holiday weekend. On-call incident responders must be ready to step in to diagnose, resolve, and recover, even outside of business hours.
As organizations continue to build out their digital infrastructure and customer demand for seamless experiences grows, ITOps is becoming even more challenging. In this context, around-the-clock readiness requires creating a culture that’s sustainable, flexible, and fair.
Designing a more sustainable approach
Here are four guiding principles for shaping an optimized approach to on-call scheduling.
1. Establish clear ownership and escalation paths
When an incident occurs, clear ownership is critical to avoid confusion and delays, and a service-based architecture can be more effective than a team-based setup.
In a service-based model, alerts are routed directly to a dedicated subject matter expert (SME), responsible for the affected service. In contrast, team-based models rely on rotations among groups of generalists. Organizations that adopt a service-based operations management architecture must maintain an accurate, up-to-date service directory to provide broader visibility into service ownership. This ensures alerts are consistently routed to the most appropriate on-call responder without delay.
Effective escalation policies typically include three elements:
- Timeouts that automatically escalate alerts if not acknowledged or resolved within a defined timeframe.
- Clear escalation targets, such as a specific SME or the on-call owner for the affected service.
- Automation that ensures critical alerts are escalated and resolved swiftly.
2. Reduce cognitive load and operational noise
Cognitive load is a finite resource. Without protection, teams struggle to work quickly and efficiently, with burnout becoming more likely over time. Operational noise compounds the problem by degrading decision-making and increasing the risk of missing true positives.
AI and automation can play an important assistive role here. Event-driven automation helps to deduplicate, correlate, or suppress noise, ensuring only meaningful alerts reach responders. AI tools also reduce manual toil by summarizing incident calls, suggesting automated runbooks, and drafting status updates.
“Cognitive load is a finite resource. Without protection, teams struggle to work quickly and efficiently, with burnout becoming more likely over time.”
AI-supported operations management tools help responders hit the ground running by cutting through alert noise and automatically providing structured, concise, and relevant context to accelerate resolution.
To identify the best opportunities to apply AI, teams should assess where work is repetitive or manual, as these areas are often the strongest candidates for intelligent automation.
3. Protect time, rest, and recovery
Responders should never dread being on call. Allowing sufficient time for rest and recovery is essential for teams to remain productive, resilient, and engaged over the long term.
Context-rich handovers play an important role. AI can be used to generate concise, asynchronous shift summaries that capture open incidents, known risks, upcoming maintenance windows, active suppressions or mutes, and other relevant context. While major incidents are ongoing, a brief live sync may still be necessary to ensure continuity.
On-call rotations should include enforced recovery periods, minimize consecutive shifts, and distribute workload fairly across the team. Additional protective guardrails include capped overrides and automated escalation when overload thresholds are met. AI tools can support sustainable operations by analyzing alert frequency, after-hours impact, and workload patterns, helping organizations design schedules that protect responder well-being.
4. Treat each incident as a learning opportunity
Continuous improvement must be the goal for any organization serious about sustainable on-call scheduling. Post-incident reviews give teams a structured, blame-free way to analyze what happened and identify areas for improvement. Analytics allow teams to track performance against their service-level objectives (SLOs) and use them as benchmarks to drive continual operational excellence.
AI supports this process by surfacing relevant analytics and automating the creation of post-incident reviews and summaries. The insights generated can then be used to continuously refine on-call rotations, escalation paths, service ownership, and runbooks.
Cultural change starts here
On-call scheduling will always be a part of the job for ITOps teams, but AI and automation are rapidly changing how teams approach it. As long as tools are used judiciously and teams keep a human in the loop for severe incidents, there are significant gains to be made.
On-call scheduling is about more than drawing up rotas. It’s about building a culture in which teams are respected and given the tools they need to do their best work. Technology plays an important role in supporting organizational resilience by automating toilsome tasks, filtering out operational noise, and accelerating escalations. However, success ultimately depends on the confidence, judgment, and skills of the humans on call.
