Automation & AI Articles

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.
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.
AI can only be as effective as the service management environment that supports it. This article explains why service management architecture, rather than tools alone, provides the operational foundation needed for AI, Agentic AI, and intelligent enterprise transformation.
For 30 years, the ticket ran the IT service desk: submit, log, triage, resolve, close. Agentic AI in ITSM is retiring that model, executing fixes across systems rather than drafting them for a human to click through. There are five places IT leaders get this transition wrong, from inflated agentic claims to the governance gap most vendor decks skip entirely, and why the ticket itself may not survive the shift.
Simone Jo Moore has spent decades arguing that the human sits at the center of every IT process, every tool rollout, every supplier relationship. In her Conversations with Giants episode, she talks about AI as a creative muse and a way to clear the drudgery, why SIAM is a relationship problem at heart, and why she’s still waiting for the industry to drop the dogma and get more honest about the people doing the work.
IT support is usually measured by first-contact resolution and ticket counts, but rarely by whether employees got what they needed. Drawing on a SolarWinds webinar, Stephen Mann looks at why AI’s biggest value lies in preventing issues before a ticket exists, why channel choice counts for more than any single preferred channel, and why most metrics track IT service desk mechanics rather than the outcomes employees experience.
Always-on AI is transforming the IT service desk, but technology alone won’t determine its success. This article examines why organizations must address human purpose, psychological safety and governance alongside AI deployment – and why answering “Why am I needed?” may be the most important question of all.
AI software is the fastest-growing cost in most IT estates, and most teams have no real view of it. The Flexera 2026 State of ITAM Report bears that out: AI tracking is now the field’s biggest challenge, wasted AI spend is climbing, and FinOps is closing in on territory IT asset management used to own. The piece runs through the findings that count for asset and service teams, and what to fix first.
The Olympics demonstrate that success depends on teamwork, preparation, governance, and seamless coordination – not individual talent alone. Discover how these same principles help IT organizations deploy Agentic AI successfully through better context sharing, AI governance, continuous validation, and clearly defined AI responsibilities.
Christian Nissen spent four decades in IT service management and helped shape ITIL along the way. In his Conversations with Giants episode, he makes the case that the industry keeps isolating capabilities it should be reintegrating, that it has swapped service for product, and that the skills worth learning are older and plainer than newcomers expect. Here are the ideas practitioners can use now.
AI is transforming IT service desks, but not in the way many expect. The real limitation isn’t the intelligence of AI models, it’s the lack of usable context in most IT environments. Between CMDB accuracy, knowledge articles, service catalogs, and tacit expertise, AI is only as effective as the information it can access. Without strong context, even the most advanced AI just scales existing issues.
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.