SITS26 brought together ITSM leaders, practitioners, and vendors to explore the future of AI, automation, change management, digital employee experience, and service transformation. Here are some of the biggest lessons and practical takeaways from this year’s event in London.
Somebody announces the death of service management every few years, and they’ve been doing it for 35. 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, which is exactly why no new wave of tech has managed to kill it. If anything, AI has made the case for it stronger.
Every new tool promises to simplify IT operations and somehow adds another layer of complexity instead. Rui Alves argues that bolting AI onto a tangle of disconnected systems just gives you automation without intelligence, and that 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. A practical checklist for what AI-ready operations actually require.
Every few years, the IT industry settles on a new savior. Agile. Then DevOps. Now AI. The pattern, as Kaimar Karu sees it, is that organizations adopt each one without first knowing what they want from it, and then act surprised when the results don’t live up to the hype. In this episode of Roman Jouravlev’s Conversations with Giants series, Kaimar covers the iron curtain still sitting between ITIL and DevOps, why the ITIL guiding principles are a net rather than a recipe, why AI should never be the goal in itself, and the skills technology won’t easily replace.
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 rather than treating the buzzwords as a checklist.
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, why the guiding principles were ITIL Practitioner’s most important contribution, 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 project work compete for the same people, and reactive always wins. His fix is bifurcated execution, separating the two into distinct streams with protected capacity, so AI initiatives stop drifting toward urgency.
It’s 9am and a sales manager hits a VPN error before a client call. Rather than wait on a service desk ticket, they paste the error into an AI tool and get a fix in seconds. The problem is solved, but no incident was recorded. Judin Joan Soundarya S of ManageEngine looks at what shadow AI costs problem management and security operations, and the practical ways ITSM platforms can regain that visibility without slowing users down.
Everyone is selling agentic AI, but the gap between the weakest and strongest versions is enormous. Manish Sharma of Rezolve.ai sets out a four-stage maturity model for AI in ITSM, from legacy retrieval through reactive assistants and process agents to true agentic systems that reason, act across connected systems, and catch problems nobody asked them to look for. He also offers the questions to put to any vendor claiming agentic AI.
The mismatch between producer effort and user value is something Mark Smalley, IT Paradigmologist and author of nine books on digital and service management, has been thinking about throughout his career. In this article on the first episode of Roman Jouravlev’s Conversations with Giants series, Mark covers several ideas that have held up across four decades in ITSM.
AI is already here. The level of AI inclusion in ITSM tools and platforms is quite remarkable when you look at it closely. The question isn’t whether to engage with it — it’s whether your organization has the right foundations in place to make it work. Trust, governance, and a clear reason for adopting it in the first place are what separate the organizations that get results from those that don’t.
The Service Desk Institute (SDI) held its annual SPARK conference in Birmingham in March. In this article, you’ll find an overview of what Vawns Murphy sees as the best bits, including top tips and advice from the presenters.
The rule of thumb in ITSM has long been that implementation costs one to three times the software license. Richard Mendis of Bytemethod.ai makes the case that agentic AI finally breaks this calculation, by taking on the configuration, documentation, and maintenance work that consumes the bulk of implementation budgets.
In this article, learn how artificial intelligence (AI) help desks powered by LLMs and AI agents automate IT support, reduce Tier 1 tickets, cut costs, and scale IT support operations.
There is a growing chorus complaining about “AI slop” in IT service management (ITSM). This article by Ian Clayton looks at how we had “slop” before we had “AI slop” and the connectivity between the two.