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AI in real estate at Battersea Power Station: data first, then results

Downloads | AI case studies

Making AI work in real estate starts with the data. At Battersea Power Station, the first small AI tests surfaced colleagues’ bonuses and the CEO’s pay. Alton Hassan, its former Digital Solutions Director, told the story at aiblLIVE London 2026.

The team went back to its data foundations and treated AI as a culture change. Then it used AI to audit years of lease changes against finance. Here is how it worked.

Battersea Power Station in numbers

  • About 3 months was the longest a hire once spent working through contracts by hand.
  • An afternoon is how long some of that work can take with today’s AI tools.

All figures as stated on stage by Alton Hassan.

What went wrong when Battersea first tested AI?

AI search exposed data people should never have seen. Documents had been saved any which way, so searches surfaced HR data, colleagues’ bonuses and the CEO’s pay. The company rolled back what it was willing to do. Hassan says it showed how much data foundations work was needed before moving on.

What we discovered is that everyone was already using AI. They were just using their own AI and not any kind of enterprise AI.

Alton Hassan, Former Digital Solutions Director, Battersea Power Station

How did Battersea use AI for lease data?

It loaded years of lease documents into a bespoke system and found the gaps. For the first time, the data fed a financial model of all the lease changes. The team then checked it against what finance had reported to shareholders. Fields were extracted to tables and compared before AI was trusted to read and write.

What is an AI concierge for a large estate?

It is conversational search for visitors, tied to maps and wayfinding. Battersea piloted one to help people navigate a large, confusing estate and find what is on offer. The aim was to lift average spend, which marketing spend cannot measure on its own. It runs as a web app opened by QR code.

How do you get staff behind AI in real estate?

Treat it as a culture change. Hassan ran sessions he likens to therapy, where finance, legal and other teams talked only about everyday problems, including ones shelved for years. Technology came later. He also ties GDPR and consent work to real use cases, so compliance stops feeling like admin.

My years of digital transformation have really taught me that technology is really a culture piece more than anything else.

Alton Hassan, Former Digital Solutions Director, Battersea Power Station

Key takeaways

  • Test search permissions early. Small pilots expose access problems safely.
  • Roll out approved tools quickly. Slow rollouts push staff to personal AI.
  • Extract, compare, then automate. Check AI data against your own models first.
  • Stay model agnostic. Models change often, so build to switch between them.

About the speaker

Battersea Power Station logo

Alton Hassan is the former Digital Solutions Director at Battersea Power Station, where he led digital transformation and CRM from residential through to consumer experience and marketing. He spoke on the AI Infrastructure track at aiblLIVE London on 20 October 2026.

What’s in the full case study

If your AI plans keep running into messy data, this is a grounded place to start. The full PDF goes deeper than this page, in the speaker’s own words.

  • What the first AI tests exposed, and why the company rolled back.
  • The lease audit, step by step, from documents to financial model.
  • The AI concierge pilot and why it runs on a QR code, not an app.
  • Five actions to take back to your own organisation.

For real estate, property and operations leaders, and digital or data leads. Five pages, about a seven-minute read.

Make AI work in real estate

AI in real estate at Battersea Power Station: data first, then results
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