ITSM Articles

Most Slack-based support isn’t a service desk; it’s a search bar and good intentions, and every untracked request is a governance issue waiting to surface. Taylor Halliday walks through building a real ticketing workflow with two channels, Slack’s Workflow Builder, and an emoji status board, then lays out exactly which pains mean you’ve outgrown the hack and need a dedicated tool.
Agentic AI systems build responses nobody specified in advance, and traditional governance models weren’t built for that. Jon Stevens-Hall draws on complexity thinking, from Cynefin to LLM-as-judge testing, to ask what it takes to govern behavior that develops rather than behavior that’s designed, and why loosening control in the right places might be the only way to keep it.
Salil Kulkarni, CSIO at Virima, argues that when an AI agent gets overridden, the issue is rarely the model. It’s a data layer that’s stale, incomplete, or missing the context a human would have caught. Drawing on decades leading technology at Caesars, Las Vegas Sands, and in hospitality revenue management, he sets out four conditions a data layer must meet before an AI agent can be trusted to act.
Matt Beran’s advice is blunt: never suggest ESM. He argues that IT teams jump straight to the framework and the acronym before another department has finished describing its actual problem, and that this is what turns a useful idea into an initiative people resist. His case is to help departments examine their own work first, let them own the solution, and let ESM show up without ever needing the name.
Gartner brought back the Magic Quadrant for IT Service Management Platforms after retiring it in 2022, and the vendor map looks very different. Freshworks jumped from Challenger to Leader, displacing Ivanti to Niche Player, while Halo and TeamDynamix arrived as new Challengers. These magic quadrant moves say more about market momentum than product fit, and the 2026 report has plenty to offer.
Service management has outgrown the IT department. Technology is now chosen and managed across the organization, often outside IT, and the specialized tools and teams around it have stopped joining up. David Cannon argues that the valuable work has shifted from running the IT service desk to orchestrating and governing the whole picture, and that cloud holds a lesson for anyone planning AI.
Hiring for potential rather than tenure led Michael Privat to offer a senior engineering role to an intern rather than a more experienced candidate. He argues that years of experience became a reliable hiring signal only because access to knowledge was once scarce and slow to build, a condition AI has now largely erased. What predicts performance today, he says, is adaptability, curiosity, and a willingness to take ownership of a problem without a playbook, qualities a résumé’s years-of-experience line doesn’t capture. His case is that hiring processes still screen candidates out on tenure before any of that gets a chance to show.
Shared devices don’t always track their handoffs the way ITSM tickets suggest. A device marked “resolved” can still be sitting uncharged in the wrong place, with no record of who took it or when. This article looks at why that gap exists, what a connected smart locker workflow can look like, and how to pilot the fix before scaling it across locations.
ITSM AI agent pilots that dazzle in the demo but stall in production are usually blamed on the AI model. The article’s author, a ten-year ServiceNow veteran, argues that the real issue is the CMDB beneath it: incomplete, duplicated, and poorly governed data that any AI agent inherits as its own weakness. Before offering four steps to close what he calls a skills gap, not a technical debt problem.
The 2026 Gartner Magic Quadrant for IT Service Management Platforms is out, and with it a fresh crop of vendor-gated links to track down. Sophie Danby has rounded up every free ITSM-relevant analyst report she could find, from Gartner and Forrester to IDC, covering everything from AIOps and endpoint management to privileged access.
The Uptime Institute puts the cost of a major outage above $100,000 for most organizations, and the biggest cause isn’t ignorance. It’s staff not following procedure under pressure. Training doesn’t fix that alone. This article works through where an experiential learning component belongs in the budget, what the evidence supports, where it stops, and the two objections that come up every time someone asks for the money.
AI may automate incidents, requests, and knowledge management, but it also becomes a service that requires governance, accountability, and human ownership. Discover why service management remains essential in an AI-driven future and why trust depends on more than intelligent technology.
ITSM teams are being told to do more with fewer people, and the old approach, hire more people, doesn’t scale. Richard Mendis argues digital workers change that: AI built into the builder layer automates the repetitive configuration work and keeps the knowledge that usually leaves with a departing admin. This is the new mandate, not another project nobody gets to.
A UK doctor’s practice pushes patients toward an online triage system instead of the phone, and the writer spends a week getting nowhere before a five-minute conversation with a receptionist gets the job done. The parallel to IT self-service and “deflection” is hard to miss. A look at what happens when technology shifts effort onto the person asking for help, and why that isn’t self-service at all.
James Finister has spent a career in service management and now works on AI ethics, and his argument is that the industry still doesn’t value people enough. In episode 11 of Conversations with Giants, he makes the case for governing AI honestly and early, designing work around the people you have, and remembering that SIAM is about relationships and trust, not just the contract.