Disrupting Real Estate: How AI Is Reshaping Roles Across The Sector

AI is reshaping every industry, and real estate is no different. It’s opening up new ways to streamline operations, support better decisions, and improve customer experiences — while also creating new challenges for leaders dealing with legacy systems and rising expectations.

Our latest real estate session brought together technology leaders from across the sector to look at how AI is changing the way teams are built and supported. 

The discussion explored where real estate firms sit on the AI adoption curve, from chatbots and assistants through to early agents and agent ecosystems. While many teams are experimenting with tools like Enterprise ChatGPT and Copilot, the group agreed that adoption is uneven, often overstated at board level, and heavily constrained by data quality, security requirements and regulation.

Where are organisations on the AI journey:

Most firms are operating between assistants and early agents, using AI to support tasks rather than full end-to-end automation. Progress isn’t linear, and complexity increases quickly as tools gain more autonomy.

Practical AI use cases in real estate:

Examples ranged from chat response management for residential procurement issues, to site analysis combining land-bank data with local demographic and employment insights, and reusable AI code modules that automate repeatable workflows.

Data, security and regulation:

Strong constraints remain around HR, committee meetings, investment decisions, PII and SARs. Many firms are banning AI recordings and transcripts entirely, driven by investor restrictions and concerns around books and records. Trust in tools is still fragile, particularly where hallucinations increase through multi-agent systems.

Driving adoption inside organisations:

Successful teams are investing in dedicated AI owners, continuous training, internal champions and sharing small, visible wins. Usage data is becoming a key signal of real impact, not just experimentation.

The future workforce:

AI is reshaping task complexity and experience levels. Early-career employees can now take on more complex work, while experienced professionals handle junior tasks more efficiently. This raises fundamental questions around organisational design, middle management exposure, graduate hiring, and how firms maintain learning, judgment and standards as entry-level work is automated.

💡 Check out the key takeaways here 💡

If you're keen to learn more or hear how you can be involved in future sessions, reach out to our event coordinator and Senior Director, Tom Dunford.