Automation & AI Articles

Illustrated aging robot in a business suit and sunglasses, representing operational maturity in AI-driven IT service management

Before You Automate: How Operational Maturity Determines AI Success in ITSM

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.
Illustrated IT support agent at a computer with headset, representing AI-driven service desk operations in a ticketless enterprise

The Ticketless Enterprise: How AI Agents Prevent Work Instead of Processing It

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.
ServiceTeam ITSM Enterprise 3.0

Provance ServiceTeam ITSM Enterprise 3.0

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.
Illustrated monitoring device with dials and signal lines representing third-party risk detection and trusted runtime truth in IT operations

Agentic IT and Third-Party Risk: Why Trusted Runtime Truth Matters

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.
AI agent deployment failure concept illustration showing a man standing beside a crashed car reading a billboard that says "It's not the car. It's the driver!" with the ITSM.tools logo

Why One in Four Enterprise AI Agent Deployments Aren’t Paying Back

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.
Self-healing ITSM concept illustration showing a large AI robot working at a computer while a manager sleeps in a chair beside the desk

Self-Healing ITSM: Are We Entering the Era of Autonomous Service Management?

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.
Agentic AI in ITSM removing human judgment and increasing operational risk

Agentic AI in ITSM: Why Removing Human Judgment Increases Risk

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.
SITS26 Recap: Key ITSM, AI, and Service Management Insights

SITS26 Recap: Key ITSM, AI, and Service Management Insights from London    

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.
Why service management keeps outliving its ITSM is dead obituaries

ITSM is Dead? Why Service Management Keeps Outliving Its Obituaries

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.
CTO checklist for building AI-ready IT operations in 2026

The CTO Checklist for AI-Ready IT Operations in 2026

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.
AI, Transformation, and What Comes First

AI, Transformation, and What Comes First

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.
AI Terms in ITSM

5 AI Terms Every ITSM Practitioner Should Know in 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.
Are You Delivering Value?

Are You Doing Service Management, or Delivering Value?

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.
ITSM Operating Model Blocking AI Adoption

Your ITSM Operating Model Is Blocking AI Adoption

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.
Shadow AI in IT Support

Shadow AI in IT Support: When Employees Fix Problems Outside the Service Desk

It’s 9am and a sales manager hits a VPN error before a client call. Rather than wait on a service desk ticket, she pastes the error into an AI tool and gets a fix in seconds. Problem solved, but no incident recorded. Judin Joan Soundarya S of ManageEngine looks at what shadow AI costs problem management and security operations, and how ITSM platforms can regain visibility.