The essential shift every ITOps leader must make to survive an unrelenting stream of incidents

The New Stack

by Ariel Russo

February 19, 2026

AI-Generated Deep Dive Summary

High-profile IT incidents are becoming more frequent and severe, with significant financial and operational consequences for enterprises. A single hour of downtime can cost large companies between $100,000 and $249,999, but this figure doesn’t account for customer churn, lost productivity, or the growing toll on IT operations teams. Traditional incident management methods, reliant on manual processes, are struggling to keep up with the increasing volume and complexity of modern IT infrastructure. To address these challenges, ITOps leaders must embrace AI- and automation-driven approaches to reduce downtime, improve response times, and alleviate burnout among overburdened teams. One critical shift is automating repetitive, low-risk tasks such as alerting, diagnostics, and remediation. By leveraging automated alerts and runbooks, organizations can quickly identify and resolve issues, freeing up IT responders to focus on higher-priority tasks. Additionally, automation can track key metrics like time saved and error reduction, helping build a business case for broader adoption of AI-driven tools. Another transformative approach is deploying generative AI (GenAI) to streamline incident triage and investigation. GenAI excels at summarizing information from logs and metrics, providing incoming responders with contextual insights, such as root cause analysis and suggested fixes. It can also retrieve relevant historical data, including past incidents and updated runbooks, serving as a dynamic knowledge base for teams. Furthermore, GenAI can automate post-incident reporting by synthesizing data from chat transcripts, logs, and action items. Finally, AI agents are proving invaluable by autonomously executing complex workflows to achieve specific goals. These agents differ from GenAI chatbots in that they independently complete tasks rather than just generating content. By handling routine operations, AI agents enable human teams to focus on strategic initiatives, ultimately enhancing efficiency and resilience. For DevOps professionals, these advancements matter because they directly address the challenges of

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Originally published on The New Stack on 2/19/2026