ITSM Articles

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, high-quality context within most IT environments. From CMDB accuracy and knowledge articles to service catalogs and tacit expertise, AI is only as effective as the information it can access. Without strong contextual foundations, even the most advanced AI simply scales existing issues. The real opportunity lies in building richer, more reliable ITSM context so AI can deliver consistent, meaningful operational value.
Many IT teams are juggling tight budgets, security gaps, compliance demands, and the growing pressure of AI — yet one discipline that could ease all of these challenges continues to be overlooked. IT asset management (ITAM) has been around for years, but for too many organisations it still means a spreadsheet and good intentions. This article explores why that needs to change, with real-world examples showing how a mature ITAM approach transforms everything from onboarding and budgeting to security and compliance.
Most IT asset handoff failures are not technology issues, they are workflow issues. Devices, tickets, and CMDB records may exist, but unclear ownership, poor visibility, incomplete handoffs, and unmanaged exceptions create delays, security risks, and compliance issues. This article explores five common IT asset lifecycle gaps that undermine onboarding, offboarding, and device management processes, and offers practical ways to improve accountability, readiness, and operational efficiency. Learn how readiness gates, stronger ownership models, and better workflow discipline can transform IT asset handoffs and create a solid foundation for automation and AI-driven service management.
Discover the latest findings from the 2026 HCLSoftware-sponsored ITSM.tools survey on Agentic AI. This article explores AI adoption trends, governance priorities, regional differences, and the correlations between AI maturity, trust, business value, and organizational success, helping IT leaders better understand where Agentic AI is delivering measurable impact in ITSM.
From ancient myths to modern workplaces, we’ve always admired heroes – the ones who step into chaos and save the day. In ITSM, that same mindset often plays out when organizations celebrate the individual who resolves a major incident while overlooking the systemic issues that created the crisis in the first place. While ITSM heroics can demonstrate expertise, dedication, and resilience, they can also reinforce a reactive culture built on firefighting rather than prevention. This article explores why ITSM heroics persist, the hidden organizational and psychological factors behind them, and how leaders can shift recognition away from emergency responders.
AI adoption in ITSM is nearly universal, but many organizations are discovering that AI can only be as effective as the processes, data, and governance supporting it. New research shows a significant gap between widespread AI implementation and the maturity of underlying ITSM practices. While AI is delivering value through automation, predictive insights, and improved user experiences, it cannot compensate for fragmented workflows, disconnected tools, or inconsistent data. As organizations pursue agentic AI and larger-scale automation, strengthening ITSM foundations (an ITSM reset) may be the most important step toward achieving sustainable AI success.
As AI agents gain autonomy and become embedded in critical business processes, organizations face a growing governance challenge. This article explains how established ITSM capabilities – including risk classification, service ownership, CMDB visibility, change management, incident response, and access governance – can provide a practical framework for AI agent governance. Rather than creating entirely new governance models, organizations can extend existing service management practices to ensure accountability, oversight, and operational resilience in the age of agentic AI.
Traditional Change Advisory Boards (CABs) help organizations govern production changes, but can introduce bureaucracy, delays, and unclear accountability. A modern alternative is an asynchronous, responsibility-driven approach where approvals are based on defined ownership, targeted oversight, and operational readiness.
What is service management, really? Daniel Breston’s answer isn’t a framework. It’s a single question, picked up from his first CEO walking a Houston bank with a Post-it pad.
Most ITSM training programs stop at the certificate. That’s an issue, because certification proves someone knows the theory, but it says nothing about what they’ll do when a major incident hits at 2 a.m., and the pressure is on to close the ticket fast. The gap between knowing a practice and applying it under pressure is where simulation-based learning offers something other formats simply can’t. This article makes the case for adding it to your ITSM program – not as a replacement for training, but as the part where what’s been taught finally gets tested against real consequences.
Many ITSM tool renewals are treated as procurement exercises when they should be strategic business decisions. With AI reshaping service management, increasing pressure to reduce costs, and rapidly evolving vendor capabilities, renewing the status quo is no longer the default choice. This guide outlines a practical 90–180 day framework for evaluating your current platform, assessing alternatives, and building stakeholder alignment before contract renewal. It also covers the seven critical questions every IT leader should answer to determine whether to renew, expand, or replace their ITSM solution with confidence.
AI doesn’t fix broken processes – it scales them. While many ITSM teams focus on automation and autonomous IT service desks, the real determinant of AI success is operational maturity. Learn why knowledge quality, workflow consistency, governance, and data hygiene are the foundations of sustainable AI adoption in IT service management.
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.
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.