Agentic ITSM Tools Are Arriving Faster Than Enterprises Can Absorb Them
Agentic ITSM tools from major vendors are moving from roadmap to reality, but enterprise IT readiness is lagging. Ivanti’s autonomous service desk agent, launched in April, can create incidents, submit requests and search knowledge bases without analyst intervention. ServiceNow agents promise similar end-to-end handling of routine IT tasks. Early adopters like Grand Bank report that these capabilities are key to freeing teams from repetitive work so they can focus on higher‑value initiatives. Yet most organisations are still in pilot mode. McKinsey research shows about 62% are experimenting with agentic AI, while only a small minority are scaling agents in any business function. This gap highlights a core issue: buying agentic ITSM tools is easy, but redesigning an estate to let them act autonomously, safely and measurably is far harder. Without that redesign, “autonomous” agents quickly fall back into human‑heavy workflows.
The Plumbing Problem: Why Legacy ITSM Estates Hold Agents Back
Agentic ITSM is exposing how much existing IT estates were built for tickets, not autonomous actors. McKinsey describes this as a “plumbing problem”: infrastructure designed for human‑led workflows cannot support agents that must cross multiple systems, execute actions via APIs and operate under tight governance. In unified communications, for example, resolving a call quality issue spans network telemetry, device health, carrier status and ITSM records. If an agent cannot reliably traverse each system, the incident bounces back to a human, defeating the purpose of deployment. The situation is compounded by basic operational hygiene gaps. As Red Hat’s leadership has noted, many teams are still struggling with fundamentals such as consistent patching. Agentic ITSM tools depend on accurate configuration data, stable platforms and clear system interfaces. When those foundations are weak, agents amplify noise instead of reducing it, generating more tickets and manual rework.
Beyond Technology: Process Redesign and Cultural Change
The enterprises seeing meaningful gains from agentic ITSM tools are transforming more than their technology stack. In McKinsey’s research, one multinational automated up to 80% of roughly 450,000 annual tickets and redeployed half its service team, while maintaining a customer satisfaction score of 4.8 out of 5. Crucially, this outcome followed a deliberate redesign of workflows and customer journeys around agent‑led resolution. This kind of shift demands new thinking about roles, processes and risk. IT service teams must move from handling every request to orchestrating and supervising agents. Service owners need to define which tasks can be safely automated and where human judgment remains essential. Culturally, leaders must help staff trust that automation is not about replacement, but about elevating their work. Without these process and mindset changes, even sophisticated ServiceNow agents or similar tools end up acting as glorified chat interfaces layered on top of legacy practices.
The Missing Layer: Observability and Trust in ServiceNow Agents and Peers
As enterprises pilot ServiceNow agents and other agentic ITSM tools, a fresh challenge is emerging: monitoring what these systems actually do. Traditional uptime metrics only confirm that services are running. They do not explain what decisions an agent made, which systems it changed or why. Analysts at Gartner warn that this visibility gap makes scaling AI risky, because errors in opaque decision‑making can trigger substantial financial, reputational and regulatory consequences. To build trust, IT leaders need observability tailored to AI and automation: traceability of actions, clear audit logs and explanations for key decisions. Gartner expects a growing share of organisations deploying AI to invest in dedicated observability tooling in the coming years, but most are still at an early stage. Until this oversight layer matures, many enterprises will be reluctant to grant agents broader autonomy, limiting the potential efficiency and responsiveness gains from IT automation adoption.
A Practical Framework to Close the Enterprise IT Readiness Gap
Closing the gap between agentic ITSM capabilities and enterprise IT readiness requires a structured adoption framework. McKinsey highlights four technical prerequisites: a sufficiently accurate CMDB for agents to act on; actions exposed via APIs with embedded policy checks; a clear governance model defining what agents can and cannot do; and active monitoring of inference costs and outcomes. For most ITSM teams, this is not a simple checklist but a multi‑year programme of work that should begin before procurement. On top of that, IT leaders should pursue staged IT automation adoption: start with low‑risk, high‑volume use cases; design new workflows around agents rather than bolting them onto legacy processes; and invest in skills for automation engineering, prompt design and AI governance. With budgets under pressure and infrastructure demands rising, the organisations that systematically prepare their estates and cultures for agents will be best placed to realise sustainable ROI.