It’s a topic that’s been cropping up a lot in our discussions recently, so it feels right that at our last London event of the year we’ll be focussing our attention on AI. Not only is it transforming how people work with data, it’s reshaping the skills, career paths and organisational responsibilities that underpin a strong Data Culture. Join us on 6 October as we explore how to help colleagues remain capable, curious and accountable in a world where generating an answer is no longer the hardest part.
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The Data Culture Club brings together the pioneering professionals who are shaping their organisations’ attitude to data. In a discipline that is relatively new, it gives members an opportunity to explore new ideas, share insights, and support each other on what can be a challenging journey.
We believe the key to developing best practice is simple: sharing what we know.
Our quarterly London events allow us to get together in person to hear fresh perspectives from industry leaders, engage in open discussions and enjoy some convivial networking. For our Q4 event we’ll be in the cosy Drawing Room of a new boutique hotel near the British Museum, shining a Data Culture light on the topic that’s on everyone’s mind: AI.
With speakers from the outside the world of Data Culture sharing their insights, and plenty of time for discussion with peers, we’ll be considering the impact of AI on people, their careers, and Data Culture teams.
Everyone is having to learn new capabilities – although with AI replacing technical know-how, and natural language processing overtaking prompt engineering, should we now be focussing our training on the critical thinking and softer skills required to frame the question and challenge the answer?
Talent paths are also shifting, with fewer opportunities for junior workers to learn their craft and experienced staff finding their hard-earned knowledge becoming obsolete or getting rusty. And this affects the whole organisation – so where do we draw the line between Data Culture and HR responsibilities?
Meanwhile, data is becoming more important and less transparent. AI allows more people to analyse data, but access doesn’t create understanding. Tracing data lineage to comply with regulation is more complex when AI is synthesising information rather than simply retrieving it. Will the initial excitement for AI result in frustration with the underlying data management or give it a boost?
Join us to explore what a strong data culture looks like in the age of AI.
Dan is one of our DCC members and has spent the past four years working in Data Risk at Compare the Market, with a broader career in Risk Management. He’s particularly interested in the opportunities AI creates, but also in the new risks that come with LLMs, AI and agents. His focus is on the bigger picture too: how AI will change the way organisations manage data, how businesses operate and how people work.
Charlotta is an Executive Director at Morgan Stanley, working across strategy, talent and non-financial risk within Global Capital Markets (GCM). She is also responsible for supporting the integration of AI tools across the GCM division in EMEA, giving her a practical perspective on the opportunities and challenges of AI adoption in the financial services industry.
We’d love to see you at our last in-person event for 2026 this October!
As we try our best to create the best community get-together, we do ask that you only register with the best intention to be there on the day. If your plans change, we’d appreciate that you let us know in advance to release your spot to another member.
Kindly note: While we do our best to welcome everyone, we reserve the right to make final decisions on registrations.
2-7 Montague St, London WC1B 5BP
We’ll be holding our event at this chic new boutique hotel just next door to the British Museum. The Drawing Room is a cosy space full of sofas and armchairs, perfect for our informal talks and friendly discussions. (And two proper fireplaces, so if by then the weather is suitably chilly and we can use them to toast our toes!)
