The AI Effect : Beyond the Hype - What’s Next for AI in Real Estate?

Where is AI genuinely delivering value in real estate, how can organisations move beyond experimentation, and what needs to happen before AI can transform the way the sector operates?

For our 'AI Effect: Beyond the Hype' event a few weeks ago, hosted by Box as part of our Tech & Innovation Programme, we brought together perspectives from across real estate, technology and professional services to explore the opportunities and challenges shaping AI adoption.

Moderated by Paul Armstrong, Founder of TBD Group, the panel featured Ayça Martinez, Director - Data & AI, Real Estate Technology & Transformation at Deloitte, Neil Milburn, Director of Business Platforms & Products at SEGRO,Nikos Papapesios, Head of Innovation Analytics at Knight Frank, James Shaw, Head of Real Estate at Box, and Chris Read, Building Automation, Digital Services and Software Client Manager at Siemens.

The discussion moved beyond the hype to examine where AI is already delivering measurable results, why strong data foundations and organisational readiness matter, and where the next wave of opportunity lies for real estate.

For PropTech companies, the conversation offered important insights into what potential customers are looking for, the problems worth solving and how to demonstrate the commercial value of AI.

Key Takeaways

1. Demonstrate measurable business value, not just technological capability

AI adoption needs to be driven by tangible business outcomes, not simply the technology itself.

For PropTech companies, the opportunity is to demonstrate exactly how their solutions save time, reduce costs, improve productivity or generate revenue. Buyers want evidence of return on investment, not simply another AI-enabled feature.

2. Strong data foundations are essential to scaling AI

AI is only as effective as the information it can access. Fragmented data disconnected systems and inconsistent document management can all undermine the accuracy and reliability of AI outputs.

Before organisations can scale AI, they need to address the fundamentals: data quality, accessibility, integration, version control and governance.

For PropTech companies, this creates opportunities to solve some of the underlying data and infrastructure challenges holding the sector back.

3. AI adoption is a business transformation challenge

Successful AI implementation requires more than introducing new tools. It involves rethinking existing processes, securing leadership buy-in, investing in staff training and ensuring employees are equipped to use the technology effectively.

One example discussed was a four-day innovation sprint involving asset managers and IT teams, which helped identify a practical use case for checking final lease agreements against approved Heads of Terms.

For PropTech companies, understanding customer workflows and involving end users early is essential. The strongest solutions will address genuine operational challenges rather than assume what customers need.

4. The next opportunity lies in embedding AI into workflows

The biggest opportunities may lie beyond standalone AI assistants, with technology increasingly embedded into everyday business processes and decision-making.

Examples discussed included AI agents supporting investment decisions by analysing historical transactions and project outcomes, as well as using AI to improve property valuation and investment analysis.

For PropTech companies, this means thinking beyond individual tools and features. Solutions that integrate into existing systems, automate complex workflows and support better decision-making could deliver greater long-term value.

5. Governance, security and responsible AI matter

As AI becomes more accessible, organisations face growing challenges around data security, confidentiality and the use of unapproved tools – often referred to as shadow AI.

Businesses need clear policies, appropriate safeguards and confidence that AI outputs can be trusted. Industry guidance, including the RICS Responsible Use of AI Standard, is also helping shape expectations.

For PropTech companies, demonstrating how data is protected, how outputs are validated and which governance standards are followed can help build trust with prospective customers.

What Should PropTech Companies Be Thinking About?

The discussion offered several practical considerations for PropTech businesses looking to develop, position and commercialise AI-enabled solutions:

1.Lead with the problem, not the technology. Understand the operational or commercial challenge your customer is trying to solve before positioning AI as the answer.

2.Build a compelling business case. Demonstrate measurable outcomes, whether through reduced operational costs, improved productivity, energy savings or better decision-making.

3.Understand your customers' existing systems. Consider how your solution will integrate with legacy infrastructure, existing data platforms and established workflows.

4.Prioritise trust and governance. Be prepared to explain how your technology manages data, protects sensitive information and ensures reliable outputs.

5.Design for adoption and scalability. Consider how your solution will fit into day-to-day operations, who will use it and what support or training customers will need.

6.Think beyond standalone AI tools. Explore opportunities to embed AI into existing processes, connect different systems and automate more complex tasks.

Looking Ahead: Where Is AI Going Next?

To close the discussion, each panellist shared their predictions for the next 6-12 months.

A recurring theme was the move towards agentic AI, with agents becoming increasingly embedded in business workflows and capable of completing tasks with less human intervention.

The panel also anticipated greater use of orchestration platforms to coordinate different AI agents and models, alongside continued investment in building management optimisation, data foundations and AI literacy.

However, perhaps the most important prediction was that the organisations seeing the greatest benefits will be those willing to rethink how they operate, rather than simply adding AI to existing processes.

For PropTech companies, this presents both an opportunity and a challenge. As real estate businesses become more sophisticated in their approach to AI, the expectation will increasingly be for technology that delivers demonstrable value, integrates seamlessly and supports better business outcomes.

The message from the panel was clear: AI is just the beginning. The real opportunity lies in how it is applied to solve real problems, transform workflows and unlock greater value across real estate.