The 2026 landscape highlighted a number of shifts.
AI is no longer a track, it is the spine of the conference embedded across every discipline.
Governance and trust are now centre stage. Multiple sessions explicitly focused on trusted AI foundations, AI governance maturity, scaling AI safely, data governance as the prerequisite for AI and observability for AI systems.
Agentic AI is emerging as a major theme. This is the first year agentic AI had a dedicated theatre signalling a shift from the previous experimentation phase to operationalisation.
AI plus organisational transformation is the new battleground asking questions like how do we scale AI safely, modernise legacy environments, demonstrate measurable business value, and improve governance without slowing innovation. This is a change from asking which model to use towards to how do we run an AI enabled organisation.
Data governance is finally being treated as strategic and it was the strongest governance representation BigDataLDN has ever had.
AI for societal impact is gaining traction with talks now covering climate change and humanitarian impact broadening AI use beyond commercial use cases.
The keynotes were AI centric which created a conference theme of AI first.
I think the BigDataLDN conference has quietly repositioned itself an AI governance, AI strategy, AI engineering and AI transformation conference.
AI governance seems like the new cloud migration in that it requires a change of mindset. The agenda showed a pattern where
- AI adoption is assumed.
- AI scaling is the challenge.
- Governance is the bottleneck.
- Data foundations are the dependency.
- Operating models are the differentiator
The conference was packed with people and exhibitors and many people spent their time queueing to get into rooms to get to listen to talks.
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