Common Pitfalls When Real Estate Boards Evaluate AI.

In a sector as capital-intensive as real estate, strategic clarity and financial diligence are paramount. Yet when it comes to artificial intelligence (AI), many property boards find themselves in unfamiliar territory—uncertain about how to evaluate proposals, measure return on investment, or even define success. Below are five common pitfalls that real estate boards can fall into and how to avoid them.

1. Confusing “Innovation” with “ROI”

The Pitfall: AI is a powerful buzzword. Many boards face pressure to show they’re “innovating,” but forging ahead without a solid business case can leave an AI project in limbo.

Why It Happens: Real estate traditionally deals in brick-and-mortar investments with tangible assets, so intangible AI benefits can feel vague. There’s a tendency to say “yes” to AI because it sounds forward-thinking.

How to Avoid It: Treat AI like any major capital investment. Require a thorough financial model, including scenario analysis and sensitivity testing. Ask for measurable outcomes—like lower operating costs, improved tenant retention, or faster leasing cycles.

2. Relying Too Heavily on Vendor Claims

The Pitfall: While there are excellent AI vendors in PropTech, boards often take supplier promises at face value, overlooking the fine print on deployment timelines, training data needs, or post-implementation support.

Why It Happens: Vendors present polished demos or success stories from ideal conditions. Real-world buildings and property portfolios can be far more complex.

How to Avoid It: Conduct independent due diligence. Perform proof-of-concept trials or pilot studies. Scrutinise vendor claims about ROI and gather references from similar real estate portfolios. And don’t sign off on large-scale deployment until you’ve seen tangible results.

3. Ignoring the Human-Centric Element

The Pitfall: AI may handle advanced analytics, but its impact on day-to-day property management or tenant interactions is profoundly human. If the people who must use or maintain these solutions aren’t on board—or well-trained—adoption can stall.

Why It Happens: Real estate boards focus on financial returns, missing the need for organisational change management. They underestimate how much front-line staff, from leasing agents to facility managers, must adapt to new tools.

How to Avoid It: Incorporate a human-centred approach from day one. Involve end-users early. Build training and change management into the project scope. Measure user adoption as part of your KPI set—because if staff aren’t using the tool, ROI will suffer.

4. Failing to Align AI with Broader Strategy

The Pitfall: Implementing AI in a silo—say, an occupancy analytics tool for one property but not across the portfolio can lead to fragmented data and missed synergies.

Why It Happens: Different teams often pursue point solutions to address immediate pain points. Without a portfolio-wide perspective, these initiatives remain disconnected.

How to Avoid It: Develop a strategic AI roadmap that aligns with overall business objectives, whether it’s boosting property values, improving tenant retention, or meeting ESG targets. Start with pilot projects, but plan how they’ll scale across other assets if they succeed.

5. Neglecting Post-Investment Governance

The Pitfall: Many boards sign off on AI budgets but never set up the governance structures needed to track performance over time. AI projects can drift, with costs spiralling beyond forecasts if no one is monitoring them.

Why It Happens: Because AI can feel like “IT spend,” some boards assume the internal tech team will handle oversight. But AI investments deserve the same rigour as acquiring or refurbishing a property.

How to Avoid It: Incorporate financial governance frameworks from the start. Define accountability, specify performance metrics, schedule regular reviews, and ensure cost attribution remains transparent. If an AI project isn’t meeting benchmarks, have a plan to course-correct—or to exit if necessary.

Final Thoughts

Real estate boards don’t have to be AI experts but they do need to ensure AI investments pass the same capital discipline and strategic alignment tests as any property purchase or development. By avoiding these five pitfalls, you can steer AI initiatives toward meaningful outcomes like higher valuations, improved tenant satisfaction, and operational efficiencies that truly impact the bottom line.