Posted by Shankar Gomathi on June 12, 2026 The best support tickets are the ones never submitted. And with the emergence of AI, a ticketless enterprise is becoming a reality, allowing Enterprise operations teams to become more effective and less expensive.
Posted by Stephen Mann on June 11, 2026 Provance ServiceTeam ITSM Enterprise 3.0 continues the platform’s evolution as a Microsoft-centric service management solution built natively on Microsoft Power Platform. Designed for organizations looking to maximize existing Microsoft investments, the solution combines ITIL-aligned service management capabilities with low-code flexibility, workflow automation, AI-driven innovation, and deep integration across Microsoft 365, Azure, Power BI, Power Automate, and related technologies. ServiceTeam ITSM Enterprise 3.0 offers organizations a modern alternative to traditional ITSM tools while leveraging the scalability, security, and extensibility of the Microsoft ecosystem.
Posted by Salil Karkarni on June 10, 2026 Strategic roadmaps are filling up with AI agents, command towers, and intelligent automation. Yet 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.
Posted by Sophie Danby on June 4, 2026 A quarter of UK enterprise AI agent deployments aren’t paying back. New research from KTSL and BMC Helix shows the reasons aren’t about the technology.
Posted by Richard Mendis on June 3, 2026 A shift is beginning, including for self-healing. AI agents are increasingly automating not only operational IT service tasks but also parts of ITSM platform implementation, configuration, and ongoing maintenance. As these capabilities mature, organizations can expect lower costs, less manual intervention, and systems that increasingly manage and optimize themselves.
Posted by Mathies Wähner on May 26, 2026 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 removing the people who used to catch the mistakes. The real question isn’t how to implement it, but whether your operating model can survive it.
Posted by Vawns Murphy on May 22, 2026 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.
Posted by Sophie Danby on May 21, 2026 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.
Posted by Rui Alves on May 20, 2026 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.
Posted by Sophie Danby on May 14, 2026 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.
Posted by Raghav S on May 8, 2026 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.
Posted by Sophie Danby on May 6, 2026 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.
Posted by John Mathieu on May 5, 2026 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.
Posted by Judin Joan Soundarya S on April 24, 2026 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.
Posted by Manish Sharma on April 22, 2026 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.