Organizations Can Lose $1M+ Per Hour During Unplanned Disruptions

Learn more about PagerDuty

The financial stakes of extended service disruption has made operational resilience a top priority, according to 2026 State of AI-First Operations Report, a report from PagerDuty.

According to survey findings, 95% of respondents believe their leadership understands the competitive advantage that can be gained from reducing incidents and speeding recovery.

The report also shows that organizations are increasingly considering the adoption of AI for digital operations, with 59% indicating they actively incorporate the technology into operations. The AI adopters appear to be experiencing more success than those who may have discussed it but have not yet incorporated it: 75% report improved operational resilience, compared to only 66% of organizations that improved operational resilience but are not yet using AI.

Additional key takeaways from the report include:

Disruptions have become a board-level financial risk

Some organizations (8%) lose more than $1 million per hour, 34% lose at least $500,000 per hour, and more than two thirds (68%) lose more than $300,000 per hour during IT incidents. The cost of disruptions have grown too high for leaders to ignore and the impact extends beyond immediate revenue loss to damaging brand reputation (52%), introducing recovery costs (50%), reducing productivity (48%) and contributing to developer burnout (42%).

Successful organizations prioritize investments in operational resilience

A majority of organizations have made strides from their investments in the past year, with 71% reporting higher resilience and maturity than a year ago. However, progress appears to vary based on two key factors: business performance and investment. While 77% of organizations plan to increase operational resilience budgets over the next 12 months, companies reporting revenue growth are investing at significantly higher rates (82%) than underperformers (62%).

Post-incident learning capabilities gain recognition

Organizations that reported improved resilience most often attributed this progress to tools that combine integration with learning capabilities. Nearly half of organizations (48%) have increased resilience by turning incidents into structured learning opportunities to improve future performance. Successful companies with revenue growth are more likely to see a massive or moderate need for continuous learning (83%) than companies with flat or decreased revenue (77%). This suggests that the most successful platforms will be those that can transform incidents into systematic improvement cycles.

"The 2026 PagerDuty State of AI-First Operations Report further demonstrates how the financial risk of major incidents makes operational resilience a board-level priority," said Katherine Calvert, chief marketing officer at PagerDuty. "AI-first operations enable organizations to accelerate their incident management workflows so they can restore service more quickly during disruption. With PagerDuty, organizations can not only minimize risk, but cut down on teams’ time spent firefighting so they can focus on driving innovation and revenue."

Methodology: The report draws insights based on survey responses from 1,000 business leaders, IT decision makers and senior developers across Australia and New Zealand, France, Germany, Japan, the Nordic countries, the UK and Ireland, and the US.

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Organizations Can Lose $1M+ Per Hour During Unplanned Disruptions

Learn more about PagerDuty

The financial stakes of extended service disruption has made operational resilience a top priority, according to 2026 State of AI-First Operations Report, a report from PagerDuty.

According to survey findings, 95% of respondents believe their leadership understands the competitive advantage that can be gained from reducing incidents and speeding recovery.

The report also shows that organizations are increasingly considering the adoption of AI for digital operations, with 59% indicating they actively incorporate the technology into operations. The AI adopters appear to be experiencing more success than those who may have discussed it but have not yet incorporated it: 75% report improved operational resilience, compared to only 66% of organizations that improved operational resilience but are not yet using AI.

Additional key takeaways from the report include:

Disruptions have become a board-level financial risk

Some organizations (8%) lose more than $1 million per hour, 34% lose at least $500,000 per hour, and more than two thirds (68%) lose more than $300,000 per hour during IT incidents. The cost of disruptions have grown too high for leaders to ignore and the impact extends beyond immediate revenue loss to damaging brand reputation (52%), introducing recovery costs (50%), reducing productivity (48%) and contributing to developer burnout (42%).

Successful organizations prioritize investments in operational resilience

A majority of organizations have made strides from their investments in the past year, with 71% reporting higher resilience and maturity than a year ago. However, progress appears to vary based on two key factors: business performance and investment. While 77% of organizations plan to increase operational resilience budgets over the next 12 months, companies reporting revenue growth are investing at significantly higher rates (82%) than underperformers (62%).

Post-incident learning capabilities gain recognition

Organizations that reported improved resilience most often attributed this progress to tools that combine integration with learning capabilities. Nearly half of organizations (48%) have increased resilience by turning incidents into structured learning opportunities to improve future performance. Successful companies with revenue growth are more likely to see a massive or moderate need for continuous learning (83%) than companies with flat or decreased revenue (77%). This suggests that the most successful platforms will be those that can transform incidents into systematic improvement cycles.

"The 2026 PagerDuty State of AI-First Operations Report further demonstrates how the financial risk of major incidents makes operational resilience a board-level priority," said Katherine Calvert, chief marketing officer at PagerDuty. "AI-first operations enable organizations to accelerate their incident management workflows so they can restore service more quickly during disruption. With PagerDuty, organizations can not only minimize risk, but cut down on teams’ time spent firefighting so they can focus on driving innovation and revenue."

Methodology: The report draws insights based on survey responses from 1,000 business leaders, IT decision makers and senior developers across Australia and New Zealand, France, Germany, Japan, the Nordic countries, the UK and Ireland, and the US.

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Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

 

The Incident Load Is Rising, but Recovery Times Aren't Moving

Two things happened to production incidents between 2023 and now, and they did not happen at the same speed. The first is that a class of dependency that barely existed three years ago now accounts for one incident in ten. Incidents disclosed by AI model and AI application providers rose from 1.7% of all disclosed unplanned incidents in 2023 to 10.7% in 2026 year to date, roughly a sixfold rise; that counts only incidents at AI companies themselves, so the true share is higher. The second is that the time to close an incident has not come down ...

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If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...

As AI Scales Across Enterprises, Breaking Points Emerge

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

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Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

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Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

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