Where to next for ITSM?

The world is changing rapidly and it can sometimes be hard to keep up with all the new and wonderful innovation being announced, especially in IT. But are you ever left wondering to yourself, where is the innovation in IT Service Management? After all, ITIL originated back in the 80s, in the days of one-hit wonders and big hair. Different iterations have helped it evolve from a rigid, process-heavy framework to a flexible, value-driven guidance model, but it still doesn't exactly scream "cool and innovative". Are there interesting things happening in ITSM, or are we just consigned to the bucket of the "boring but necessary"?

The good news is that we feel that there are actually plenty of exciting things brewing in the ITSM space. Here are five big shifts that we see changing ITSM significantly over the next couple of years.

AI, Machine Learning, Generative AI

We are already seeing this move starting to happen, although broadly speaking we don't think that toolset capabilities are matching up to the sales hype quite yet. In the near future though we see AI moving to become the primary first line of support, with conversational agents that understand natural language, automated resolution and smart triage that routes to the right team instantly. ITSM processes will become more predictive, with incidents being detected (and resolved) before the user even notices, intelligent change risk scoring, demand forecasting for services and resources, and proactive alerts for recurring patterns.

We also see advances in knowledge management, with automatic drafting of solution articles based on clusters of tickets, articles being updated automatically, suggested knowledge to address gaps and contextual answers through Teams, Slack or Email. Incidents will become increasingly self-healing, resolving issues without human intervention. And agents will become "AI-augmented experts", using AI copilots to summarise tickets, draft change plans, release notes and communications and identify root causes.

The risk, of course, is that we will see AI as the solution to all our problems. The reality is though that AI doesn't fix poor process, it magnifies it. There are things that we can be doing now to prepare for when the AI wave hits with full force. We can be working on our ITSM maturity to ensure clean data and processes, mature knowledge practices and consistent classification. We can be investing in automation skills early. We can be strengthening observability and monitoring to ensure that AI has the visibility it needs to act intelligently. And we can be preparing our people and roles, upskilling agents in AI, automation and scripting, developing AI champions and shifting L1 roles towards analysis rather than data entry.

Convergence with ITOM, Observability & DevOps

Increasingly, modern services span infrastructure, cloud platforms and applications. The boundaries are gone. Organisations are shifting toward integrated, end-to-end service delivery models that emphasise speed, resilience and shared accountability.

ITOM provides the operational foundation—monitoring, event management, automation and infrastructure oversight—while observability adds deep insight into system behaviour through logs, metrics and traces, feeding incident management with real-time telemetry and enabling teams to identify issues proactively rather than reactively. DevOps contributes continuous integration, deployment and rapid feedback loops that accelerate change without sacrificing stability.

When brought together with ITSM, these disciplines are beginning to create a unified operating model where incidents are detected earlier, root causes are identified faster, changes move safely through automated pipelines and service health becomes a shared responsibility across development, operations and support teams. The outcome is strengthened service reliability, improved user experience and a move towards a dynamic, collaborative ecosystem aligned to digital business outcomes.

Experience Management

ITSM has traditionally measured performance via metrics like response time, resolution time and service availability, and often the numbers are impressive. But if I'm a user and I can't use my system right now when I need to, what comfort is it to me that IT go on to resolve my issue in 3 days, well within the 5 day SLA? Mature organisations are recognising that employee satisfaction and productivity are tied to their experience of IT services.

And so we have the shift to Experience Management (XM), the practice of capturing, interpreting and improving the human experience of interacting with IT services. XM blends ITSM with disciplines like UX design, human-centred service design, organisational psychology and data-driven feedback loops, with the goal of ensuring IT services feel effective, efficient and supportive from the user's perspective, rather than just technically "available".

Experience Management introduces practices like Experience-Level Agreements (XLAs, which are tied to outcomes and sentiment), continuous listening (through micro-surveys, sentiment analysis and passive telemetry), experience analytics (combining technical and experiential data to see correlations) and human-centred service design (using personas, journey mapping and co-design with users). Together, these help IT organisations prioritise what matters to users, detect friction early, increase employee engagement, reduce tickets by fixing root causes of frustration and demonstrate business value beyond "keeping the lights on". Experience Management reframes IT from a backend service provider to a partner in employee experience and business performance.

Enterprise Service Management

The concept of Enterprise Service Management (ESM) isn't exactly new. The extension of ITSM practices across the rest of the organisation (HR, Facilities, Finance, Procurement etc) first emerged about 15 years ago and many enterprises have dipped their toes in the water to varying degrees over the years.

Historically, though, ESM mostly meant "give HR or Finance a service catalog". The shift now is that it is becoming enterprise-wide workflow orchestration, creating consistent, cross-department experiences and automated processes that span the whole business. Processes that once lived in silos (e.g. onboarding, procurement, policy management) will increasingly be shared, automated and measurable, delivered through common platforms.

We see ESM moving from "forms and queues" to predictive, self-healing processes. AI will automate intake, classification and routing, knowledge lookup, task execution and workflow stitching across systems. Business units will increasingly design their own workflows. Governance models will mature. Platforms will consolidate.

Over the coming years, ESM programs will deliver faster onboarding and cross-functional processes, lower operational costs via automation, consistent employee experiences across departments, better analytics and visibility and much stronger alignment between IT, HR, Facilities, Finance and other service teams.

Hyperautomation and Orchestration

Automation has been one of the top trends in ITSM for several years now. In our experience though, most organisations have only been nibbling around the edges of what is possible. Workflows exist to do some routing, send emails and replace some basic manual tasks (like adding users to an AD group or creating a new virtual machine), but a full blitz on automation is rarely tackled.

We see this beginning to change. In the coming years, hyperautomation will mature from scattered automation tools into coordinated, AI-driven enterprise automation ecosystems. Organizations will move beyond those simple task automations—like RPA bots or scripted workflows—toward end-to-end orchestration, where AI agents understand intent, trigger the right automations and coordinate actions across multiple systems and departments.

AI will handle much of the intake, triage, routing and execution of routine work, while orchestration platforms will become more dynamic, adjusting workflows based on context rather than rigid, prebuilt flows. RPA, workflow, integration and low-code tools will increasingly converge into unified platforms with shared data, governance and observability.

This evolution will spread into IT operations as well, driving self-healing infrastructure, automated remediation and “no-ticket” operational models. Governance will strengthen to ensure security and standardization as automation scales across the enterprise.

All of this will result in faster processes, dramatically reduced manual effort, more predictable outcomes and better employee and customer experiences—marking a shift from fragmented automation to intelligent, autonomous digital operations.

How do I jump on board?

It can be tempting to read about all that is happening and want to jump on board right now, but the reality is, if you're not ready...you're not ready. Mature ITSM is the foundation that makes all of these modern practices work. It provides the clear processes, reliable data, defined services and governance needed for automation, experience improvements and cross-department workflows. Without solid ITSM, organizations end up automating inconsistent processes, feeding AI bad data and struggling to create coherent enterprise workflows.

In short: mature ITSM turns chaos into structure—so AI, Experience Management, ESM, hyperautomation and orchestration can operate effectively, scale safely, and deliver real business value.

The good news - Lida is here to help. You might want to consider our fixed price ITSM Health Check, to take stock of where you are right now and map out a path for where you want to be. Or maybe you'd just like to chat - feel free to drop us a line at services@lida.com.au.