Skip to main content

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

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.

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

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

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.

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...