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Beyond Academia: Financial Times Chief Data Officer

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About this event

What to expect

Explore how the Financial Times turns data and AI strategy into organisational value with Chief Data Officer Kate Sargent at this University of Cambridge seminar.

From research to real-world AI

Taking place in person on Tuesday 27 October 2026, from 4:00pm to 5:00pm, this Beyond Academia seminar offers a practical perspective on deploying data science and artificial intelligence beyond the university environment. The session will be held at The Glasshouse @InnovateCambridge, 100 Hills Road, Cambridge, CB2 1LQ.

The Beyond Academia: AI & Data Science Applications series is designed to bridge the gap between high-level research and implementation inside organisations. Invited leaders and professionals examine the technical, architectural and operational realities of AI innovation while introducing attendees to career opportunities outside academia.

Hear from Kate Sargent

Kate Sargent, Chief Data Officer at the Financial Times, is responsible for the organisation’s Data and AI Strategy and for creating value from its data assets. Since joining the FT in 2023, she has led its award-winning Data & AI Governance, Data Science & AI, Analytics, Research and Business Intelligence disciplines.

Kate brings 30 years of experience across major consumer-facing organisations in retail, travel and media. Her work focuses on using data to understand and influence customer behaviour and generate commercial value. Alongside her executive role, she is an industry commentator, board adviser and mentor, with a particular commitment to early-years skills development and increasing awareness of careers in data and analytics.

Attendees can expect insight into:

  • How data and AI strategy operates within a global media organisation
  • The challenges and opportunities involved in implementing AI innovation
  • The role of governance, analytics, research and business intelligence
  • Translating data assets into practical and commercial value
  • Non-academic career pathways in data science and AI

The format is an engaging one-hour talk with plenty of opportunity for audience Q&A, giving researchers and students direct access to an experienced data leader.

Who should attend?…

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