TINtech Data Jam 2026: Common ground, shared priorities and the challenges still to solve

Reflections, insights and thoughts from attendees at this year's TINtech Data Jam.

If there was one message that came through consistently at TINtech Data Jam 2026, it was that the conversation around data and AI has matured.

Throughout the event, leaders from across the insurance industry shared their experiences, successes and lessons learned. While perspectives varied, there was remarkable alignment on the opportunities ahead and the obstacles that continue to slow progress.

This article brings together the themes that surfaced repeatedly across the keynotes, presentations, panel discussions and workshops. It highlights both the areas where the market appears to have reached consensus and the practical challenges that organisations are still working to overcome.

Thank you to everyone who contributed to the discussions and helped make this year's TINtech Data Jam such a valuable exchange of ideas.

~Jeremy

The foundations of a data-driven organisation

Executive summary

This was not another discussion about investing in more technology.

Instead, the focus was on the foundations that make technology valuable. Several speakers highlighted that becoming data-driven is less about tools and AI and more about discipline, trust and culture.

There was broad agreement that data transformation is a long-term journey requiring consistent effort, clear ownership and strong governance. Governance itself was positioned as an enabler, helping people use data with confidence rather than restricting access.

Perhaps the strongest message was that AI will not fix poor data. Real value comes from building trusted foundations and embedding data into everyday decision-making.

Gourav Sharma | TINtech Data Jam 2026 reflections

Really enjoyed being at #DataJam2026 earlier this week—great to see leaders from across the insurance industry coming together to exchange ideas, explore innovation, and challenge how we think about the future of data and technology.

A big thank you to The Insurance Network and Jeremy Burgess for the opportunity to share perspectives on what truly defines a data-driven organisation—moving beyond tools to mindset, governance, and culture.

My top 5 reflections from my session with Charles Whatling and Aron Tai:

1) Data transformation requires discipline, dedication, and consistency—it’s a marathon, not a sprint

2) Trust must be earned through evidence—demonstrate value and reliability every day

3) Governance shouldn't be a constraint; it’s about empowering people to confidently use and explore data

4) AI and technology alone won’t fix data challenges—foundations matter

5) True impact comes from embedding data into decision-making and operational efficiency, shifting from intuition-led to evidence-based outcomes

Building trust in AI

Executive summary

The discussion highlighted a shift taking place across the industry. The question is no longer whether AI can perform a task. Increasingly, organisations are asking whether it should and how they can use it responsibly.

Trust emerged as a central theme. Participants stressed the importance of trusted data, clear accountability and appropriate human oversight as AI becomes more deeply embedded within business processes.

There was broad agreement that governance should not be viewed as a barrier to innovation. Instead, it provides the framework needed to scale AI confidently, manage risk and ensure decisions remain transparent and explainable.

As AI adoption accelerates, building trust is becoming just as important as building capability.

Karthik Srinivas | TINtech Data Jam 2026 reflections

It was a privilege to be part of the panel discussion on Bias, Ethics and Governance in the Age of AI at #TINtech #Datajam 2026 alongside Chris Collings (Amplifi (Europe) and Mark Blake (Stibo Systems).

One theme stood out throughout the discussion: the challenge is no longer building AI, it is building trust in AI.

The conversation is increasingly shifting from “Can AI do this?” to “Should AI do this, and who is accountable when it does?”

There was strong engagement throughout the session, with valuable perspectives shared on trusted data, accountability, human oversight and the practical realities of scaling AI across the enterprise.

Thank you to Jeremy Burgess, Phil Middleton and The Insurance Network for bringing together such a diverse group of leaders and practitioners for an open and thought-provoking discussion.

Moving from experimentation to practical AI adoption

Executive summary

Discussions around Agentic AI reflected a growing desire to move beyond hype and focus on practical application.

While the potential of AI is widely recognised, the emphasis was on identifying sensible, strategic use cases that solve real business problems and deliver measurable outcomes. Success depends not just on the technology itself but on understanding where it can genuinely enhance decision-making, productivity and customer outcomes.

There was a clear recognition that organisations are still at different stages of maturity. As a result, sharing experiences, lessons learned and practical examples remains critical to helping the industry unlock value while avoiding common pitfalls.

The conversation reinforced the importance of balancing ambition with pragmatism as organisations look to scale AI adoption responsibly.

Paul Butler | TINtech Data Jam 2026 reflections

It was a great TINtech DataJam conference this year.

I really enjoyed meeting a lot of enthusiastic folks and also talking on stage and being on the Agentic AI panel.

Hope my advice was useful and helpful - and others can begin to unlock the potential of strategic and sensible uses of AI.

A big thanks to Jeremy Burgess and the#TINtechDataJam team for organising such a great event too.

Building AI foundations for long-term flexibility

Executive summary

The discussion highlighted the importance of designing AI strategies that can evolve alongside a rapidly changing technology landscape.

Rather than focusing solely on individual tools or models, the emphasis was on creating the architectural foundations, operating models and data capabilities needed to support AI at scale. Flexibility emerged as a key theme, enabling organisations to take advantage of future innovations without becoming dependent on today's technologies.

There was also recognition that successful AI adoption must be commercially sustainable. Achieving the right balance between innovation, cost efficiency and alignment with business objectives remains a critical consideration for organisations seeking to scale AI effectively.

The message was clear: lasting success comes from building foundations that support continuous adaptation rather than chasing the latest technology trend.

Usha Badrinath | TINtech Data Jam 2026 reflections

At The Insurance Network TINTech DataJam 2026, sharing how Mosaic Insurance is building the AI foundations that allow us to scale our AI capabilities without locking in to today's tech - while keeping our unit economics sensible, and our architecture aligned to our unique business model.