SIAM+ AI month reflections: how AI is challenging traditional service management thinking

At Scopism , we turned June into ‘SIAM+ AI’ month in the Scopism SIAM community. We had the idea in response to questions from community members about how AI can be applied in SIAM models, and we wanted to start some initial research ahead of the SIAM body of knowledge refresh scheduled for 2025.

Now that the month is complete, I’m taking the opportunity to reflect on some of the lessons that I learned and new ideas shared. The first thing that I must do is extend my sincere thanks to all of our speakers and session attendees. We had 11 sessions including two social meetups and every one of them gave us new perspectives on the intersection between AI and SIAM. Our community is so generous in sharing its knowledge. If you missed any of the sessions you can also find them in the past events section in the community.

In this blog I’ll reflect on two initial ideas:

AI is challenging traditional service management thinking

AI adoption is moving beyond buzzwords and hype

I’d love to hear your thoughts as well – do you agree?

AI is challenging traditional service management thinking

The first broad reflection that I have is that AI and AI adoption is challenging service management thinking in ways that we've never seen before. We've seen technology trends in the past and we've seen general public and management interest in things like blockchain but AI adoption is the first emerging technology that I can remember where the transformation is both business-driven and solution-led.

Traditional IT service management thinking has always focused on identifying a business problem or desired outcome and then understanding where technology can resolve that; this continues with the more recent ITSM focus on value stream mapping, experience measurement and end to end service governance.

What is different with AI adoption is that the business case and the investment is technology led and the question we (and our customers) are asking is “what can we do with this technology that we have access to?”

Rather than identifying the problem and developing a solution to remove or reduce it instead we are looking at technical capability and trying to work out where we can adopt it in organisations. This challenges our traditional service management ideas.

So how do we approach this as service managers? One of the main criteria will be how we judge the success of our efforts in adopting AI and associated technologies. We need to be able to measure the success of our initiatives and we need to ensure that the adoption of any new technology doesn't negatively impact some of the other areas that we're so focused on including digital experience and employee experience.

AI adoption is moving beyond buzzwords and hype

The second reflection is that the reality of AI adoption is starting to meet the hype of AI adoption, but it's not necessarily the brave new world people are expecting.

We've seen many use cases in the sessions that we've featured during AI month, and a large percentage of those are focused on productivity gains and increased efficiency, directed towards lower level and operational tasks and processes.

These are delivering real business benefits, but not necessarily the hyped expectations of what AI is going to enable us to do. We're also seeing pushback from organisations within the delivery network, for example customer organisations prohibiting the use of AI in tender responses. Any organisation that is adopting AI technologies will need to think carefully about the potential use cases and the art of the possible.

We were drilling specifically into the intersections between AI and SIAM in our community event this month and there were some interesting stories, use cases and recommendations. In a complex multi-supplier environment AI can absolutely deliver benefits. We've seen real examples of that associated with areas like incident management, major incident management, and knowledge management.

However, as with any organisational change we need to understand our starting position and our key principles, and the guardrails and constraints that we operate within. For example, security can't be an afterthought and particularly in a multi-supplier environment data security/who has access to what is key.

This to me is where ITSM and service managers have a key role to play, and should be an important focus area for anyone in the ITSM space.