AI will continue to change real estate at a dramatic pace: How to prepare our students for an unknowable future?
This is a preview of an opinion piece I contributed to the Cambridge University Land Society Magazine.
Love it or loathe it, the explosive growth of AI in the real estate industry will continue in 2025. The transformation isn’t just about automating existing processes, it’s fundamentally reshaping how we think about, use, develop and invest in physical spaces.
The changing nature of work is driving massive shifts in commercial real estate. While we’ll continue to hear calls for ‘return to office’, the reality is more nuanced. Many roles that have been streamlined or replaced by AI aren’t coming back in their traditional form. New ones are emerging. The seismic changes aren’t just about remote work and offices—it’s about a fundamental restructuring of what spaces we’ll need in the future.
Nobody knows how this brave new world will manifest. But three trends are certain:
First, the relationship between landlords and tenants is evolving into something more dynamic and service-oriented. Traditional passive tenancy models are giving way to fully integrated service offerings. Property owners are becoming active partners in their tenants’ success, using AI-powered systems to optimise everything from energy usage, leasing decisions, to space configuration and utilisation. This revolution promises higher returns, but demands more sophisticated management. Assets will work harder and more efficiently, but require more active input and oversight. The key to higher returns lies in understanding exactly how spaces create value for their users.
Second, the differences in skills exhibited by investors and operators will become more dramatic. The winners in this new landscape will be those who embrace these changes and use AI holistically, not just as a cost-cutting tool, but as a means to deliver better experiences and more value to their tenants. Property owners who stick to traditional, more passive approaches risk being left behind as the market increasingly demands smarter, more efficient, and more responsive spaces.
Third, speed will make all the difference. The real estate industry has historically been slow to adopt new technologies. AI needs to be put to work much faster. Its impact is simply too significant to ignore, and its benefits too substantial to dismiss. As we move through 2025, expect to see AI continuing to reshape every aspect of real estate, from how we design and manage buildings, deliver services, to how we structure leases and investments. All while some traditionalists keep insisting “it’s too early to know if this isn’t just another fad”. The laggards will find themselves in dire straits.
Teaching Real Estate in the Age of AI: Core Skills Matter More Than Ever
It’s easy to throw out bold ideas. But how can we prepare our students for an unknowable future? How can we prepare the next generation of industry leaders and policy makers? Counter-intuitively, the answer isn’t just about teaching new technologies. Equally important is it to double down on fundamental humanistic skills while adding critical technical understanding. In an era where AI can generate pages of plausible-looking ‘analysis’ in seconds, deep human skills become more valuable, not less. The ability to read critically, think deeply, and write clearly are becoming true differentiators. These skills are essential for evaluating AI-generated analyses, identifying subtle flaws in automated valuations, crafting nuanced strategies that consider human factors, and communicating complex ideas clearly to stakeholders. As AI makes content creation easier, fewer professionals are developing these fundamental skills—making them increasingly rare and valuable. These ‘old’ skills are developed in good supervision.
While core humanist skills remain crucial, real estate professionals also need enough technical knowledge to work effectively with AI tools. This means understanding the basic principles of data science and statistics, how machine learning models work and their limitations, common pitfalls in data analysis, and ways to validate and verify AI-generated insights. The goal isn’t to turn real estate professionals into data scientists, but to make them informed users of AI technologies who can effectively combine human judgement with AI capabilities. In the MPhil courses, we integrate AI-related research and tools into the curriculum: Traditional statistics is combined with machine learning; financial modelling in Excel with AI technologies. In a year, we plan to launch a new elective module on Data, AI, and the Built Environment, that will focus on exactly what’s stated on the tin.
The rise of AI also poses immediate practical challenges for universities. How do we fairly assess student work in an era where essays might be ghostwritten by AI? Simply returning to paper-based exams feels like taking the easy way out – akin to how the Amish chose to reject new technology. Instead, we need to fundamentally rethink our assessment methods. This means designing assignments that test deep understanding rather than just the ability to synthesise information – a task at which AI excels. For instance, exercises might require students to critique AI-generated analyses, combine real-world data sources, or simply defend their reasoning in oral presentations. As educators, we must become even more critical readers ourselves, looking not just for technical accuracy but for the genuine analytical insights and creative problem-solving that still distinguish human intelligence.
The challenge for real estate education is striking the right balance between timeless skills and new technical knowledge. We need to teach students to be both critical thinkers and technically literate, able to leverage AI’s capabilities while understanding its limitations. The most successful professionals will be those who can combine deep industry knowledge with strong analytical capabilities, technical literacy, excellent communication skills, and critical thinking abilities. In this AI-enhanced future, the goal of education isn’t to compete with machines, but to develop the uniquely human capabilities that complement them. The winners will be those who can harness AI’s power while maintaining the human judgement and insight that technology cannot replace.
Illustration: OpenAI. (2025). AI-generated image “Surreal skyline transitioning from library to computer models” [Digital image]. Generated using ChatGPT and DALL·E. Available from OpenAI’s ChatGPT.
