Support has always been a critical part of engineering, but the way we approach it is evolving. Ascendion works across multiple domains such as infrastructure, platforms, applications, SRE, DevOps, and IAM. In large enterprise production environments, a significant portion of tickets, especially at the L1 and L2 levels, follow standard processes.

Take a password reset, for example. The steps are clear: validate identity, get manager approval, reset the password, and share the details. This doesn’t need human intervention anymore. Through AIPO, we train AI agents to handle these tasks autonomously.

By automating routine tasks, engineers get time back to focus on L3 issues where things aren’t so clear-cut. These are the challenges that require human expertise: for example, analyzing logs, understanding system interactions, performing root cause analysis, etc. With AIPO, support teams are empowered with tools and agents that reduce procedural effort, enabling deeper analysis and faster resolution.

In today’s IT operations, general-purpose AI agents often struggle to deliver consistent outcomes. With AIPO, we take a smarter approach: we create small, reusable, task-driven agents for each persona. One agent creates a ticket, another handles execution, and a third closes the ticket and communicates. This modular approach creates an agentic workflow that resolves incidents more efficiently.

Facing a surge of 20 alerts? Instead of backlogged queues, AIPO instantly launches 20 task-specific agents running in parallel, delivering rapid, consistent resolution. Even better, these agents learn on the fly when an engineer adjusts a workflow. The agents observe and adapt without manual retraining. This intelligent automation improves speed, consistency, and reliability, freeing engineers to tackle more meaningful, higher-value challenges.

And the shift is real: AI for IT operations (AIOps) adoption is accelerating. Gartner predicts that by 2026, 30% of enterprises will automate more than half of their network activities, up from less than 10% in 2023. Currently, AI handles 10–15% of support activity. In the next two years, I expect that to grow to 30–40%, transforming how IT teams operate.

Many organizations rely on platforms like ServiceNow alongside vendor automation tools. But engineers often waste valuable time switching between systems to troubleshoot complex issues. One of the biggest advantages of AIPO is its ability to integrate seamlessly with existing tools. It acts as a thin orchestration layer in the client ecosystem, sitting across existing tools, creating a single pane of glass for incident visibility and response. Instead of guessing or passing issues between teams, engineers can act faster with greater clarity.

Forrester underscores that AIOps must fit within existing infrastructures instead of replacing them. When AIOps integrate with legacy systems, it brings flexibility, efficiency, and enhanced security to operations.

Proven Impact: A Fortune 500 client lowered incident resolution time by 40%, reduced number of incidents handled by human engineers, and improved their NPS score after implementing AIPO. By eliminating the need to toggle between systems, their teams could focus on preventing issues, rather than reacting to them.

The power of AIPO becomes even more evident in large-scale environments. Consider a global retailer with more than 70,000 stores. Each location has its own routers, servers, and IoT-enabled devices. Flooded with alerts, it wasn’t just a matter of “What’s broken?” Their team was also asking, “What’s likely to fail next? What can wait? What demands immediate attention?”

With AIPO, we moved them from a reactive to a predictive model. By analyzing patterns and trends, AIPO helped prioritize issues, reducing downtime by 25% and ensuring critical systems stayed operational during peak hours. Forrester affirms this shift toward predictive operations: AIOps is now a core resilience strategy. By surfacing advanced analytics and proactive insights, it not only reduces disruption but drives continuous improvement.

Ascendion continues to expand AIPO’s use cases. We started with 10 predefined incident scenarios, but every client conversation brings up new ideas of where we can implement AIPO. From monitoring to observability, DevOps, and access management, the possibilities are limitless.

When a client sees their request received and resolved in five minutes or less, it’s more than a matter of speed. It represents a frictionless experience that frees teams to focus on the right problems and helps businesses unlock greater value from the systems they already own.

AIPO is not simply another software. It is a transformation of how IT operations are designed and delivered. By applying AI where it creates the most impact, we are improving efficiency, while also redefining what IT operations can achieve.

AIOps has quickly evolved beyond experimentation and is becoming the foundation for how resilient, efficient, and client-centric enterprises run their platforms. The organizations that succeed will be those that apply AI where it delivers the greatest value, orchestrating across tools, predicting issues before they occur, and giving engineers the space to solve what truly matters. The opportunity is clear. The next generation of IT operations won’t be measured by uptime or ticket closure alone. It will be measured by how seamlessly technology serves people and how confidently enterprises can scale without disruption. AIPO is the pathway to that future. Now is the moment to embrace it.

If you are ready to reimagine what IT operations can achieve, let us start the conversation today. Together, we can apply AI where it works best and build the intelligent operations your enterprise needs for the decade ahead.