As IT environments become more complex, the task of quickly resolving incidents is increasingly hindered by fragmented teams, siloed communications, and manual processes. Reducing Mean Time to Resolution (MTTR) is a key objective for organisations looking to maintain operational stability and service reliability. Integrating AI into IT workflows offers a structured approach to streamlining automating response actions, and reducing time to resolution. While AI-runbooks can support faster triage and consistent remediation, they come with challenges around cost, implementation, and internal adoption which are important to overcome to be able to implement these tool for adaptive feedback loops to improve incident response.
In this webinar, our panel will explore the practical considerations and strategic value of implementing AI-powered incident management frameworks. Discussions will include how to overcome the typical adoption barriers, drive internal buy-in, and build a future-proof response model that scales with your organisation’s needs.
Learning Objectives:
- Examine how AI can support faster incident response and contribute to reducing MTTR
- Explore the role of real-time feedback loops in improving ongoing incident resolution
- Understand the challenges involved in deploying AI-runbooks and securing stakeholder buy-in
- Discuss how automation can be introduced into existing IT operations without reducing oversight or visibility
