Automation & AI 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.
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.
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.
A quarter of UK enterprise AI agent deployments aren’t paying back, and new research from KTSL and BMC Helix shows the reasons have almost nothing to do with the technology. This article looks at what’s going wrong inside deployments, why model choice matters less than most vendors suggest, and what enterprises would need to change to close the return gap.
AI agents are automating not just operational IT tasks but parts of ITSM platform implementation, configuration, and maintenance. Richard Mendis argues this shift is underway, and that as it matures, organizations should expect lower costs, less manual intervention, and systems that manage themselves. A look at where self-healing ITSM is credible today, and where vendor claims still outrun reality.
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.
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.