Service Management

For many organisations, service performance has long been understood through spreadsheets, inconsistent incident data, and informal knowledge that rarely reflects the full picture. This session explores how one Technology function broke free from that cycle - moving from manual, unreliable reporting to a unified, automated insight engine that shows exactly how services are operating in reality, not perception.

We’ll share the transformation journey: improving the quality of incident information, standardising operational data, and building a suite of reporting that leaders across Technology and the wider business can trust. The shift didn’t just create cleaner dashboards, it changed conversations, accelerated decisions, and exposed trends that had previously been invisible.

Whether you’re a CIO, Head of Service, or Service Management professional looking to elevate operational maturity, this session will show you how fact‑based insight can unlock strategic value, drive better investment decisions, and reposition Service Management as a proactive, data‑driven partner to the business.

Purposeful, enterprise-aligned conversations, rather than "chats", exhibit the values and goals of the organisation that owns them, and consequently of the user they are intended for. To achieve enterprise intentions, and to be enterprise-contextual, requires a service paradigm which "chat-based" products cannot provide.

Creating organisation-aligned conversations requires

1. they be designed in a way that utilises the power of generative AI models

2. there be a mechanism for executing purposeful designs

3. conversational features which AI models are not designed for be supported. 

These requirements expose general challenges with using gen-AI and opportunities for addressing them.

Generative AI models are probabilistic and non-deterministic. To utilise them for AI conversations aligned to organisational needs requires a systems architecture to make many-step usage of generative AI work. While engineering a platform to execute aligned designs, we have exposed the exciting, puzzling and even worrisome aspects of deploying AI solutions in professional settings – especially those which are advisory, which encourage best practice, are quality-orientated, or regulatory.

To help service management professionals navigate the plethora of AI concepts and AI-related technologies available to their decision making, the talk will address a selection of these. To make them concrete and to help with making sense of them, we will use a simple, purposeful conversation – designed (in advance) specifically for the SM/ITAM specialist group – and invite the audience to participate in its use and the resulting discussion of what is most important for the SM/ITAM community. 

Project Managers – have you ever been “forced” to engage with a Service Design and/or Transition team, received little value and then be taxed for the “pleasure”?

Or perhaps such a function doesn’t exist, and then there’s a last minute scramble to get everything ready before your project goes live and closes down.

Service Support Teams – have projects implemented new or amended services and you have little or no idea how the service is to be supported? You’re left running around trying to work out who is responsible for what and how the service “works”.

Service Transition Leads – do you feel like you’re banging your head against a brick wall trying to steer projects in preparing their service for ongoing operation

Leaders – are you fed up with the costs, complaints and limited value?

If so, this session is for you. We’ll explore how to create a Service Design and Transition service that adds value, has transparent fair costs, and that everyone wants to use. 

Every organisation is racing to implement AI governance frameworks - the #1 trending topic in ITSM. But there's a fundamental problem nobody's addressing:

You cannot govern AI systems without accurate visibility into your IT infrastructure.

Research shows 75% of organizations get no meaningful value from their CMDBs [INOC, 2025] - the very foundation AI governance requires.

Framework compliance doesn't equal business value. This session challenges conventional ITSM orthodoxy and provides executives and practitioners with a financially-grounded roadmap connecting CMDB maturity to measurable AI governance outcomes.

• Why current AI governance approaches mirror failed Waterfall methodology

• The true financial cost of CMDB failure (with real case study data)

• How broken CMDBs create ungovernable AI environments

• A pragmatic, outcome-focused approach to fixing both problems simultaneously

• 5 actionable steps to implement Monday morning

This presentation demonstrates that success isn’t just about technology—it’s about how technology is designed, developed, and deployed within an agile release process. It introduces a shift-left approach to help organisations standardise services, accelerate delivery, and strengthen governance.

The session will illustrate a typical release process, expose its flaws, and show how it can be transformed into a model suitable for all IT teams. This model aligns with frameworks such as FinOps, ITIL, and TOGAF, while prioritising six critical principles:

• Cost analysis

• Governance,

• Standardisation

• Security

• Agility

• On-demand capabilities.

Through a graphical presentation showcasing an innovative technology lifecycle—from architecture phases to production feedback loops. It will highlight automated guardrails and demonstrate how these can empower teams across infrastructure, applications, and data domains.