ITSM Articles

The 2026 HCLSoftware-sponsored ITSM.tools survey looks at how Agentic AI is being adopted across service management. This article breaks down the adoption trends, governance priorities, and regional differences the survey found, plus how AI maturity correlates with trust, business value, and organizational outcomes. It’s a snapshot of where Agentic AI is currently delivering in ITSM, and where it still isn’t.
From ancient myths to modern workplaces, we’ve always admired the people who step into chaos and save the day. In ITSM, that mindset plays out when organizations reward the person who resolves the crisis while ignoring the systemic issues that caused it. Alexandros Christias covers why ITSM heroics persist and how to shift recognition from firefighting to prevention.
AI adoption in ITSM is nearly universal, but AI is only as effective as the processes, data, and governance behind it. Research shows a wide gap between AI use and the maturity of underlying ITSM practices. AI can automate and predict, but it can’t fix fragmented workflows, disconnected tools, or bad data. Strengthening ITSM foundations, an ITSM reset, may be the biggest step toward making AI work at scale.
As AI agents gain autonomy and become embedded in critical business processes, organizations face a growing governance challenge. Suganya Raju argues that established ITSM capabilities, including risk classification, service ownership, CMDB visibility, change management, and access governance, already provide most of the framework needed. The article covers how to extend what teams already run rather than reinventing.
Traditional Change Advisory Boards help organizations govern production changes, but they introduce bureaucracy, delays, and unclear accountability. Troy Kinsey lays out a modern alternative: asynchronous, responsibility-driven approvals based on defined ownership, targeted oversight, and operational readiness. The article walks through what this looks like once you’ve moved past the CAB, and what it takes to get there.
What is service management, really? Daniel Breston’s answer isn’t a framework, and it doesn’t need one. It’s a single question, picked up from his first CEO walking a Houston bank with a Post-it pad. This article unpacks the question, why it still works four decades later, and why frameworks keep failing to capture what it captures immediately.
Most ITSM training programs stop at the certificate, which is fine for proving someone knows the theory. It says nothing about what they’ll do at 2 a.m. under pressure to close the ticket. Henry Strouts argues the gap between knowing a practice and applying it under pressure is where simulation-based learning belongs, not as a replacement for training but as where teaching finally gets tested.
Too many ITSM tool renewals get treated as procurement exercises when they should be strategic decisions. Manish Sharma lays out a 90–180 day framework for evaluating your current platform, assessing alternatives, and building stakeholder alignment before contract renewal. The guide also covers the seven questions every IT leader should answer to decide whether to renew, expand, or replace their tool.
AI doesn’t fix broken processes, it scales them. Matt Beran argues that while ITSM teams focus on automation and autonomous service desks, the real determinant of AI success is operational maturity. The article covers why knowledge quality, workflow consistency, governance, and data hygiene are the foundations of AI that keeps working after go-live rather than failing quietly, and where teams tend to underinvest first.
The best support tickets are the ones never submitted. Shankar Gomathi argues that with AI agents in the mix, a ticketless enterprise is closer than most support teams think, letting IT operations become more effective and less expensive. The article covers what a ticketless model looks like, which categories of ticket disappear first, and what has to be true internally to reach that state.
Provance ServiceTeam ITSM Enterprise 3.0 is a Microsoft-native service management platform built on Microsoft Power Platform, combining ITIL-aligned capabilities with low-code flexibility, workflow automation, and integration across Microsoft 365, Azure, Power BI, and Power Automate. This solution snapshot covers where the platform fits, who it’s built for, and how it compares against traditional ITSM tools.
Strategic roadmaps are filling up with AI agents, command towers, and intelligent automation. Salil Karkarni argues that both agentic IT and third-party risk programs share a hidden constraint that rarely makes it into keynotes: neither can succeed without a trusted, runtime view of what exists, how it is connected, and which services it supports. The article looks at why that gap keeps derailing both.
SLA metrics capture resolution and response times against fixed targets. They’re aggregate, they’re historical, and they tell you nothing about internal flow quality. A team can optimize for the clock while the way they get there, through escalation ping-pong, midnight heroics, and workarounds instead of fixes, degrades the system underneath. Yuri Kudyn on what to measure instead if you care about true service health.
Nearly three-quarters of organizations are already using their ITSM tools’ AI capabilities, and 94% of those able to rate the results report efficiency improvements. Agentic AI adoption is still early though, held back by data quality, governance, and skills gaps. This article shares six findings from the State of Agentic AI in ITSM 2026 survey, with links to the full report and webinar.
Lynda Cooper has edited ISO 20000 for more than a decade. Her explanation for why the standard has stayed useful for twenty years is also her clearest answer to the question people keep getting wrong about it: standards tell you what to do, not how to do it. The how is what frameworks like ITIL are for, and this article walks through where each one fits.