Insights from our latest Operations Special Interest Group
What does it really take to implement AI in operations? How do you strike the balance between ambition and practicality, especially when internal resources are stretched thin and data foundations are shaky? These were some of the pressing questions debated in our latest member-only Operations Special Interest Group meeting.
Designed as a forum for TIN Network Members to share honest experiences and practical strategies between our main conferences, the session offered a deep dive into the twin challenges of delivering transformation at pace and managing the people dynamics that make or break successful change.
Here are some of the key themes and insights shared by participants from across the industry.
AI adoption: early-stage, fragmented and full of potential
It’s no secret that AI has become the topic of the moment, but the discussion revealed a stark contrast between perception and practice. While some organisations are experimenting with co-pilot-style tools or deploying AI for document summarization and sanctions checks, widespread adoption remains elusive. Most participants described their use of AI as minimal and exploratory.
One attendee summed it up well:
“We’re not lacking interest in AI, we’re lacking the foundational data and internal expertise to make it meaningful.”
The group agreed that AI should be treated as a tool, not a silver bullet. Without clearly defined objectives or clean structured data, organisations risk wasting time and money. Many have already learned this the hard way, by starting complex AI projects only to abandon them once the real complexity of their data or processes becomes clear.
Start small and get specific
A recurring theme was the importance of starting with focused, manageable use cases. Participants shared examples such as using AI to help locate policy documentation more quickly or to assist with bordereaux processing. These targeted problems offered clearer ROI and lower risk than more ambitious AI-led transformation projects.
As one contributor put it:
“It’s not about what AI can do, it’s about what you need it to do. Get that right and success becomes far more achievable.”
The message was clear: set a tight scope, define the outcome and resist the temptation to do too much at once.
Transformation requires more than technology
The session also surfaced deep reflections on the human side of change. Even with the right tools in place, transformation often stalls due to capacity issues, cultural resistance or fragmented leadership. Teams are overstretched, and the same key individuals are repeatedly relied upon for multiple projects, creating bottlenecks and burnout.
Many attendees highlighted the need for stronger governance, clearer prioritisation and better coordination between teams. In some organisations, global offices were each selecting their own vendors or pursuing separate automation initiatives, creating duplication and complexity.
Bringing transformation to life is not just about technology. It’s about people - their time, their mindset and their willingness to adopt new ways of working. Agile approaches have promise, but require cultural shifts that not everyone finds comfortable. Building buy-in, communicating purpose and adapting to individual change responses emerged as critical enablers of lasting impact.
Lessons from the room
From this rich exchange of ideas, a few golden threads stood out:
- AI works best when data foundations are strong and use cases are tightly defined
- Governance and coordination are critical to avoid overloading individuals and duplicating efforts
- Change needs to be inclusive, drawing in voices from across experience levels to create momentum
- Transformation should simplify, not complicate - success means improving clarity and process, not layering on more tools
Looking ahead
This member-only Special Interest Group meeting reaffirmed the power of peer-to-peer knowledge sharing. The honesty with which challenges were aired - and lessons exchanged - demonstrates the real value of this space. Whether you’re navigating complex legacy systems or trying to justify your next AI investment, you’ll find others grappling with the same questions.
Our next meeting will take place after TINtech on 17th June and will build on the insights from the conference.
If you're looking to connect with others facing similar operational challenges, share your experience and shape future discussions - join us. Membership unlocks access to these sessions and ensures your voice helps shape the industry's thinking.
What AI use case are you tackling first? How are you managing resource pressures while delivering transformation? We’d love to hear your perspective.
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