Coronavirus Articles

Robotic hand pressing a large reset button representing the ITSM reset for AI service management

The ITSM Reset: Why AI Can’t Scale Without Strong Service Management Foundations

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.
Classical and futuristic figures illustrating the concept of AI agent governance in ITSM

Why AI Agent Governance Belongs in ITSM

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.
CAB change advisory board meeting with IT professionals reviewing change requests around a table

Beyond the CAB: A Practical Approach to Modern Change Governance

Traditional Change Advisory Boards help organizations govern production changes, but they introduce bureaucracy, delays, and unclear accountability. Troy Kinsey lays out a modern alternative: asynchronous, responsibility-driven approvals based on defined ownership, targeted oversight, and operational readiness. The article walks through what this looks like once you’ve moved past the CAB, and what it takes to get there.
Two portrait photos pinned to a corkboard covered in colorful notes and papers, representing Daniel Breston and the service management story

Want to Get Service Management Right? Grab a Post-it!

What is service management, really? Daniel Breston’s answer isn’t a framework, and it doesn’t need one. It’s a single question, picked up from his first CEO walking a Houston bank with a Post-it pad. This article unpacks the question, why it still works four decades later, and why frameworks keep failing to capture what it captures immediately.
Illustrated figures standing on pillars of varying heights, representing simulation-based learning and decision-making in ITSM training

Why Simulation-based Learning Belongs in Every ITSM Program

Most ITSM training programs stop at the certificate, which is fine for proving someone knows the theory. It says nothing about what they’ll do at 2 a.m. under pressure to close the ticket. Henry Strouts argues the gap between knowing a practice and applying it under pressure is where simulation-based learning belongs, not as a replacement for training but as where teaching finally gets tested.
Illustrated phoenix rising in flames, representing renewal and rebirth in the ITSM tool renewal cycle

ITSM Tool Renewal Guide: 7 Questions to Ask Before Renewing or Replacing Your Platform

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.
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.
Illustrated figure measuring with a large ruler, representing flow metric measurement in IT service management rather than just SLA use

SLA Compliance is Misleading: How to Measure True IT Service Health

SLA metrics capture resolution and response times against fixed targets. They’re aggregate, they’re historical, and they tell you nothing about internal flow quality. A team can optimize for the clock while the way they get there, through escalation ping-pong, midnight heroics, and workarounds instead of fixes, degrades the system underneath. Yuri Kudyn on what to measure instead if you care about true service health.
Bold pop-art illustration of three geometric figures in shutter shades, representing agentic AI concepts in ITSM

The State of Agentic AI in ITSM 2026: Adoption Trends, Benefits, and Challenges

Nearly three-quarters of organizations are already using their ITSM tools’ AI capabilities, and 94% of those able to rate the results report efficiency improvements. Agentic AI adoption is still early though, held back by data quality, governance, and skills gaps. This article shares six findings from the State of Agentic AI in ITSM 2026 survey, with links to the full report and webinar.
Illustrated header showing Lynda Cooper and Roman Zhuravlev as stylized figures seated on large colorful 3D letters representing ISO 20000

How ISO 20000 Has Stayed Useful for Twenty Years

Lynda Cooper has edited ISO 20000 for more than a decade. Her explanation for why the standard has stayed useful for twenty years is also her clearest answer to the question people keep getting wrong about it: standards tell you what to do, not how to do it. The how is what frameworks like ITIL are for, and this article walks through where each one fits.
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.