The engineer you pay $200,000 a year just spent an hour copy-pasting data between dashboards. Again.

Software engineers have critical skills that are in the highest demand. And yet, many world-class engineers are currently spending too much of their time clearing tickets, routing alerts, and responding to the same types of incidents over and over again. 

This operational toil is costing you. Every time a principal engineer gets paged to restart a service or decipher a noisy dashboard, your organization loses out on hours (or days) of high-impact work. That’s time that could have gone towards improving systems, optimizing architecture, or innovating on where your technology could go next. 

These interruptions are costly, and they also pose a strategic risk that enterprises can’t afford if they want to remain competitive. When your best people are wasting their time on break/fix and automatable tasks, you risk slowing down innovation, burning out your talent, and compromising the value you deliver to your customers. 

Modern enterprises are breaking this cycle by leveraging automation and AI for routine work, freeing up engineers to optimize for the present and build for the future.

Operational toil is costing you more than you think

Operational toil is often dismissed as the cost of doing business in increasingly complex systems, but it’s actually quietly eating away at your budget, productivity, and retention. 

According to Catchpoint’s 2025 SRE Report, site reliability engineers (SREs) spend 20% of their time on repetitive, manual work, at the median. On a 20-person SRE team with an average salary of $180,000, that’s $720,000 a year spent on tasks that could be automated.

The hidden costs go deeper. Teams that are consumed by thousands of alerts and rote tasks don’t have the bandwidth to build the automations, reliability improvements, or new features that drive the business forward. Imagine what your teams could be building if they weren’t spending the equivalent of one work day a week on firefighting and processing tickets.

Then there’s the human toll. If your smartest people feel like button pushers, they’ll go somewhere else. Burnout and boredom drive attrition, and in today’s talent market, losing a senior developer could mean months of rehiring and retraining for an impact-driving role.

You don’t have to choose between speed and stability

Operational toil doesn’t just waste engineering time—it creates fragility. Beyond inefficiency, teams that still rely on legacy systems and manual workflows are dealing with tool sprawl, brittle integrations, and human-dependent processes. The result is a false choice: either move fast and risk outages, or play it safe and fall behind. Neither approach works. 

The only way forward is to reshape how operations run. AI and automation deliver both speed and resilience by replacing repetitive toil with modern operational capabilities like: 

• AI for pattern detection and decision support, so issues are flagged early and triaged intelligently
• Automations for safe, repeatable execution of operational tasks, reducing human error and removing friction
• Standard approved paths that promote consistency and reduce cognitive load and variance for your teams

Enterprises are already adopting these changes. According to PagerDuty’s 2025 State of Digital Operations Report, 64% of IT leaders expect their operations budget to increase this year—with investments aimed primarily at efficiency, resilience, and operational excellence. The mandate is clear: AI-first operations will replace toil with impact. 

At PagerDuty, our Operations Cloud makes this real by delegating the manual, repetitive parts of incident resolution to AI and automation, freeing engineers from break/fix jail to build tomorrow’s innovations.  Here’s what it looks like in practice: 

• Well-understood incidents are fully automated by AI agents. Think: expired SSL certs, auto-scaling, or known memory leaks. 
• Partially understood incidents go through AI-led triage with human approval. AI groups alerts, surfaces past context, and recommends actions, but humans make the call.
• New, novel, and major incidents are human-led with AI support. AI handles context-gathering, status updates, and documentation so engineers can focus on solving the issue.

This model helps teams automate the repetitive, augment the complex, and accelerate every part of the incident lifecycle. And it’s already making a measurable impact in category-leading enterprises.

How leading enterprises are freeing up their engineers

Companies like Schneider Electric and TUI are already proving the impact of adopting AI-first operations with PagerDuty. 

Schneider Electric, a global leader in energy management, was struggling with the sheer volume of alerts generated by its systems. Using PagerDuty’s AIOps, Schneider cut noise by 65–75%, reduced mean time to acknowledge (MTTA) by 87%, and automated closure for 40% of incidents. That’s 5,000 manual notifications per month eliminated, giving their engineers time to focus on proactive reliability work. 

TUI, the world’s largest integrated tourism organization, was on a mission to stand up more resilient IT operations and drive efficiency. With PagerDuty, TUI automated incident response times across its platforms, reducing recovery times by up to 90% and saving millions in the process. By automating incident response, they freed up engineers to focus on building better customer experiences, which is critical in an industry where service quality drives competitive advantage.

When you let AI handle the toil, your people finally have the space to do what they were hired for: innovating, scaling, and delivering value.

Let AI handle break/fix. Let your people build.

Your engineers were hired to solve hard problems, build great systems, and drive the business forward. But that won’t happen if they’re stuck rebooting services and triaging alerts. 

AI-first operations change the equation. By offloading manual, repetitive tasks to intelligent systems, you give your teams the space to innovate and the resilience to scale. 

With 51% of companies already deploying AI agents today and 86% expecting to be operational with them by 2027, the shift to automation is accelerating. The enterprises that lead this change will define the new standard for operational excellence.

Read How AI is Reshaping Digital Operations to learn how leading organizations are leveraging AI and automation to drive operational efficiency and build resilience.