Mathies Wähner on why Agentic AI fails in ITSM. Drop it into an operating model that isn’t ready and it doesn’t make you smarter, just faster at being wrong, while quietly removing the people who used to catch the mistakes. The real question isn’t how to implement Agentic AI, but whether your operating model can survive it once it’s running at scale.
Mathies Wähner on why Agentic AI fails in ITSM. Drop it into an operating model that isn’t ready and it doesn’t make you smarter, just faster at being wrong, while quietly removing the people who used to catch the mistakes. The real question isn’t how to implement Agentic AI, but whether your operating model can survive it once it’s running at scale.
Somebody announces the death of service management every few years, and they’ve been doing it for 35 years now. Barclay Rae has heard every version and thinks they all miss the same thing: the job at the heart of service management is human, not technological. That’s why no new wave of tech has managed to kill it, and AI has made the case for it stronger.
Every new tool promises to simplify IT operations and adds another layer of complexity instead. Rui Alves argues bolting AI onto disconnected systems just gives you automation without intelligence, and the CTOs getting real value in 2026 are doing the unglamorous work first: connecting service management, monitoring, assets, FinOps, and governance into a single operational layer.
Compliance evidence is usually assembled from scattered systems, but one source hides in plain sight: your ITSM platform. Mahati Dwibhashi of ManageEngine shows how change records, access approvals, incident logs, and asset data captured through daily operations double as audit evidence for SOC 2 and ISO 27001. She also covers the workflow tweaks that make the data audit-ready.
Many IT service desks still operate with a “very important person” (VIP) list, treated as long-held IT support best practice. But given how much the business now depends on technology, that list is showing its age, and it’s likely getting in the way of something more useful to the organization. This article makes the case for the VIR list as its replacement.
Every few years, the IT industry settles on a new savior. Agile. Then DevOps. Now AI. Kaimar Karu argues organizations adopt each one without first knowing what they want from it, then act surprised when results don’t live up to the hype. In this episode of Roman Jouravlev’s Conversations with Giants series, Kaimar covers why AI should never be the goal in itself and the skills technology won’t replace.
IT support teams often spend all their time reacting to issues – resetting passwords, restoring services, responding to issues (incidents), and managing major incidents such as outages. In this article, learn how problem management helps eliminate root causes, reduce repeat incidents, lower costs, and shift IT from firefighting to prevention.
Most organizations overestimate what a single CMDB “transformation” can do and underestimate the power of a stream of small, compounding design and automation decisions. This article explains the benefits of the latter over the former.
Read any ITSM platform brochure today and the same cluster of AI terms stares back: agentic AI, AI agents, RAG, AIOps, MCP. The vocabulary is moving faster than most IT teams can keep up with. Raghav S of ManageEngine explains what each one means in an ITSM context, how they differ, and how to tell which capability fits a problem you have.
Value is what the customer decides it is, not what the IT department or a framework says. It’s the test Stuart Rance has applied across a thirty-year career: would anyone on the receiving end say your work created value for them? In episode three of Conversations with Giants he explains why he hates tool replacement projects, and why using agentic AI to cut headcount is the wrong use of the technology.
If AI is the strategic priority, why are the teams meant to implement it still buried in ticket queues? John Mathieu of Allari argues the blocker isn’t culture, skills, or tooling but the operating model itself: reactive work and AI projects compete for the same people, and reactive always wins. His fix is bifurcated execution, separating the two into distinct streams with protected capacity.
This article takes my less-than-stellar experience with Uber and considers it through an ITSM lens. Hopefully, it might also make you think about the services your IT organization offers and delivers, and how they are perceived by your end-users/customers.
When Askar Aituov joined as a Developer Experience consultant at one of Kazakhstan’s largest banks, with 700-plus engineers, he expected the usual challenges: stakeholder alignment, change resistance, legacy tooling. What he didn’t expect was to watch a mature ITIL 4 implementation quietly fail to deliver what it was supposed to. This article walks through what went wrong, and why.
This article explores the role of maturity models in Service Management and ITSM – what they do well and where they often fall short – and introduces a more practical approach your organization can adapt to drive meaningful improvement.