Real Estate’s AI Problem Is Not Interest. It’s CEO Absence.

Real estate does not have an AI interest problem. It has a leadership problem.

Brokerages talk about AI constantly. They test tools. They run pilots. They assign someone to explore vendors. But too often the work gets pushed downstream as a tech initiative instead of led from the top as a business transformation. That is exactly how urgency gets diluted, training gets fragmented, and measurable impact gets delayed.

The new data is getting harder to ignore. BCG reported on May 14 that only 25% of real estate firms qualify as AI leaders. The same research says the sector is investing roughly half the cross-industry average in AI. In BCG’s 2026 AI Radar, organizations overall expect to invest 1.7% of annual revenue in AI in 2026, but the combined industrials-and-real-estate segment sits at just 0.8%, far behind technology at 2.1%, financial institutions at 2.0%, and insurance and energy at 1.9%.

That gap matters because AI advantage is increasingly being captured by companies that treat it as a CEO agenda, not a side project. BCG’s 2026 AI Radar found that 72% of CEOs now say they are the main decision-maker on AI in their organization, up roughly 2x from last year. Half of CEOs surveyed say their job stability depends on getting AI right. That is what priority looks like. In many brokerages, by contrast, AI is still treated as something to delegate to operations, marketing, or an “innovation” lead without the authority to reshape budget, training, accountability, and workflow design.

Alex Gustafson, CEO of Oppy, puts it bluntly: “100% of Oppy customers achieve ROI when the CEO owns AI strategy and actively participates in regular check-ins. The problem is many operators look at AI as tech and delegate decision making, training and resource prioritization downstream where urgency, decisive action and impact loops are watered down. For best chances of success, AI should be kicked off as if onboarding a cofounder more than a new SaaS platform.”

Delegated AI is usually slow AI

When AI gets delegated downstream, the pattern is predictable. A brokerage buys software before it defines a business outcome. Training becomes optional. Metrics stay fuzzy. Human owners are not explicit. Pilot programs get judged on anecdote instead of pipeline movement. The result is not failure because the technology is weak. It is failure because the operating system around the technology is weak.

Craig McClelland, President of LOCAL Realty, sees the issue from both sides of the table: running a brokerage and building AI into the industry. In his view, the CEOs who treat AI like a vendor evaluation tend to get vendor-evaluation outcomes: a tool, a login, and a slide in the next all-hands. The CEOs who treat AI like an operating decision are the ones who actually change how their companies execute, and the gap between those two postures compounds weekly.

That framing helps explain why delegated AI tends to move slowly. Brokerages do not need more surface-level excitement about AI. They need executive ownership, weekly operating rhythm, and a willingness to reorganize how work gets done around the systems that actually move leads, listings, showings, and follow-up forward.

Underinvestment creates an opening for disruption

The risk is not just mediocre implementation. It is strategic exposure.

Technology companies, financial institutions, and other forward-looking incumbents are investing at materially higher levels because they expect AI to change the economics of execution. They are funding systems that can compress response time, automate coordination, improve decision quality, and learn across workflows. Real estate firms that keep treating AI as a low-budget experiment are effectively giving faster-moving players a larger head start.

That matters in brokerage because small execution gaps compound quickly. If another operator responds faster, nurtures better, books more appointments, and keeps more pipeline momentum alive through AI-assisted workflows, the advantage does not stay theoretical for long. It shows up in conversion, recruiting leverage, operating margin, and client experience.

Colby Lampman, CEO and Designated Broker of Homes of Idaho, makes a similar point: one of the biggest misconceptions in real estate is that AI adoption is mainly a software decision. In practice, it is an operational leadership decision. The firms creating real momentum are the ones where leadership stays directly involved in implementation, accountability, workflow design, and training cadence. The gap between firms that operationalize AI and firms that casually experiment with it is likely to widen quickly.

BCG’s broader conclusion is the right one for broker-owners: capturing full AI value requires CEO-led transformation. That does not mean the CEO personally runs every implementation detail. It means the CEO makes AI an operating priority, allocates real budget, defines the business outcomes, joins the review cadence, and forces the organization to move faster than its default habits.

Real estate does not need more pilots. It needs a command decision.

Most brokerages are still early enough to close the gap, but not if they keep treating AI adoption as an optional software rollout. The firms that win this cycle are likely to do three things differently.

The harder truth for the industry is that real estate may not be losing on AI because agents are resistant. It may be losing because leadership is not acting like the moment is urgent enough. In other sectors, CEOs are already treating AI as a structural bet. In real estate, too many firms are still treating it like a tool demo.

Conclusion

Real estate’s AI problem is not lack of interest. It is lack of executive ownership. An industry investing below the broader market and delegating core AI decisions downstream should expect the maturity gap to widen. The brokerages that change course fastest will be the ones whose CEOs stop treating AI like software procurement and start treating it like a cofounder-level operating decision.

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