A nationwide study of 3,662 real estate management professionals, released by IREM and AppFolio on November 5, found that AI adoption in property management has nearly tripled since 2023 — rising from 21% to 58%. Among those using AI, 85% report productivity gains. But only 48% say those gains have reached net operating income or profitability. AppFolio calls the gap the "Efficiency Trap," and it may be the most important concept in enterprise AI right now.
The disconnect between productivity and profitability isn't new, but the IREM-AppFolio data puts hard numbers on it at a scale that's difficult to dismiss. It's also a story that extends well beyond property management. Across industries and geographies, organisations are discovering the same uncomfortable truth: making people faster at their existing tasks is not the same as making the business more valuable.
The Efficiency Trap, Defined
The term is AppFolio's, but the concept is universal. When AI is deployed to speed up existing workflows without rethinking what those workflows are for, the time savings evaporate into the organisation. People complete tasks faster, but the business doesn't capture that capacity as revenue, reduced cost, or better outcomes.
The study's data illustrates this clearly. Among AI users, 85% report productivity gains, while just 48% see that reach NOI or profitability. Owner and investor satisfaction sits at 58%, and resident satisfaction at 62% — both better than the profitability number, but still trailing productivity by a wide margin.
"Being faster at the to-do list is not the same as performing at a higher level," the AppFolio report notes, "and this year's data shows that gap hasn't closed."
Depth Beats Adoption
To understand why some operators pull ahead, IREM and AppFolio built an AI Maturity Index scoring respondents across three dimensions: understanding, openness, and active use. The results split into four tiers — Dormant (15%), Curious (40%), Engaged (29%), and Proficient (16%).
The gap between the tiers is dramatic. As operators climb from Dormant to Proficient, positive NOI impact rises from 15% to 67%, resident satisfaction from 15% to 75%, and owner satisfaction from 13% to 72%.
James Scott, IREM's Innovator-in-Residence and Director of Industry and Professional Programs at the MIT Center for Real Estate, described the threshold this way: "The shift happens when you stop treating AI as something to consult occasionally and start assigning it a consistent role in your workflow. The difference isn't incremental; it reflects a clear threshold where consistent use starts to compound."
The largest group — the 40% classified as Curious — represents both the biggest risk and the biggest opportunity. These are professionals who see AI's potential but haven't built it into daily operations. They're experimenting, not embedding. And the data suggests that's precisely the zone where productivity gains fail to convert into business results.
The Governance Vacuum
Perhaps the most striking finding isn't about adoption or ROI — it's about oversight. Only 8% of organisations have a formal written AI policy, and 74% of professionals have received no formal AI training. Fifty-four percent of companies neither encourage nor discourage AI use — unchanged from the previous year, even as adoption surged 13 percentage points.
"People are moving ahead, but many organisations are not," said Scott. "When organisations remain neutral, the effect is not truly neutral: it shifts responsibility to individuals who may not have clear policies or guidance."
This governance gap has direct consequences for the Efficiency Trap. Without clear direction, employees default to using AI for individual task acceleration — drafting emails faster, summarising documents quicker — rather than embedding it into business-critical workflows where it could move financial metrics. Stacy Holden, Vice President and Industry Principal at AppFolio, put it plainly: "The operators pulling ahead have a system that does the work with them, and the judgment to anticipate what a resident needs before they ask, or bring an owner a plan instead of a problem."
This Isn't Just Property Management
What makes this study valuable beyond real estate is how precisely it mirrors findings across every other sector in 2026.
McKinsey's 2026 Global Survey on the State of AI, covering 1,719 respondents across 97 countries, found that 80% of employees report AI has improved their individual productivity. But only 37% of organisations can attribute any positive EBIT impact to AI — a figure that hasn't moved since 2025. Just 6% qualify as "high performers" who attribute at least 5% of earnings to AI. Adoption is sprinting. Returns are barely crawling.
Bain's research tells the same story from a different angle. Across 951 companies and 63 enterprise processes, organisations are converting roughly 38% of AI's expected value into deployed, measurable results. Bain calls this the "realisation rate" — and it's lower than traditional automation, which clocks in at 52%. Nearly 40% of companies that measured AI cost savings realised less than 10%, despite targeting 11-20%.
The pattern holds in Australia too. CPA Australia's 2026 Business Technology Report found 88% of Australian businesses use AI, but only 10% have deeply embedded it across their operations — the lowest level of broad AI integration among all surveyed markets. Roland Berger found that 37% of Australian companies remain stalled on generative AI despite significant investment, with the firm concluding bluntly: "Australia does not have an AI adoption problem, but it does have a value conversion problem."
At Heygentic, we've been tracking this gap for months, and the evidence keeps converging on the same conclusion: the companies seeing real returns aren't the ones that adopted AI first — they're the ones that redesigned their operations around it.
What This Actually Means for Your Business
The IREM-AppFolio study offers a practical framework that applies well beyond property management. Here's what it suggests:
Stop measuring time saved. The Efficiency Trap exists because time saved is the default metric, and it doesn't correlate with profitability. Measure what you'd measure without AI: revenue per employee, customer satisfaction scores, cost per transaction, error rates.
Move from Curious to Proficient. The 40% in the Curious tier are the cautionary tale. Occasional AI use for individual tasks produces productivity gains that don't convert. The operators seeing 4.5x better NOI outcomes have AI embedded in how their business runs — in workflows, not just in individual prompts.
Write the policy. Only 8% of organisations in the study have one. But companies that actively encourage AI use see twice the adoption rates. A policy isn't a constraint — it's a signal that the organisation takes this seriously enough to provide guidance, training, and direction.
Redesign the workflow, not just the task. Bain's finding that only 7% of companies run fully autonomous agents, despite building business cases around full-autonomy economics, captures the mismatch perfectly. AI doesn't fix a broken process — it locks it in, speeds it up, and makes it more expensive to unwind.
The property management industry is useful as a case study precisely because it's so ordinary. These aren't cutting-edge tech firms. They're mid-market operators managing buildings, leases, and tenant relationships. If the Efficiency Trap is visible here, with this much data, it's visible everywhere. The question for every business leader isn't whether their team is using AI. It's whether AI is changing how the business operates — or just how fast people finish their to-do lists.
Sources
- New IREM & AppFolio Research: Top Property Management Firms Have Cracked the Code on Driving Performance with AI — AppFolio Newsroom
- IREM and AppFolio AI Insights Report: Performance Gains Go to the Most Proficient AI Users — AppFolio Blog
- AI use is growing fast in property management. Are your guardrails keeping up? — IREM Blog
- The State of AI: Global Survey 2026 — McKinsey & Company
- Realization Rate: The Metric Reshaping Enterprise AI — Bain & Company
- Aussie businesses risk falling behind in AI race — CPA Australia
- Australia's AI journey: From broad adoption to value — Roland Berger
