The AI Lifelines That Property Investors and Managers Are Grabbing

A recent survey of 505 real estate and multifamily professionals — including property managers, asset managers, developers, leasing specialists, and owners — uncovers critical areas of concern and highlights a pivotal industry shift: the accelerating adoption of artificial intelligence as a strategic lever to address long-standing operational hurdles.

The survey from my organization, the Center for Real Estate Technology & Innovation, illuminated several key areas where inefficiencies persistently erode operational performance. Topping the list? Delinquent management and collections. It was cited by 21 percent of respondents, and highlights an acute pain point. As inflation and housing affordability pressures persist, timely rent collection has increasingly become a critical driver of net operating income (NOI), demanding significant managerial bandwidth and exposing properties to financial risk.

Equally pressing, lead conversion and leasing performance were identified by another 21 percent of respondents as major inefficiencies. Despite considerable investments in property marketing technologies, operators consistently struggle to optimize the resident acquisition funnel. High lead attrition rates, inconsistent follow-up processes, and suboptimal closing ratios directly undermine occupancy targets and revenue growth.

A third significant operational concern is budgeting and forecasting, indicated by 16 percent of respondents. Finance teams remain tethered to manual spreadsheets and legacy systems, processes that are inherently cumbersome, error-prone, and incapable of dynamically adjusting to shifting market conditions. As investor scrutiny grows, such operational fragility poses reputational risks and impairs accurate financial reporting.

Notably, despite their centrality to property financial management, lease and rent roll accuracy issues emerged prominently in the survey. Operators reported recurring discrepancies arising primarily from manual data entry errors and incompatible data systems. These inconsistencies not only result in direct revenue leakage but also exacerbate compliance vulnerabilities, creating exposure in regulatory audits and tenant relations.

The survey’s demographic insights reveal that operational challenges transcend portfolio size. Approximately 33 percent of respondents managed portfolios exceeding 10,000 units, underscoring that even well-resourced enterprises grapple significantly with operational inefficiencies. 

Similarly, the smaller operators managing portfolios of 100 to 499 units, accounting for one-fifth of respondents, reported parallel challenges, highlighting systemic inefficiencies irrespective of scale. This suggests that operational problems are deeply structural rather than merely a function of resource availability.

Further, the survey suggests that AI is an essential tool for operators big and small. Over half (53 percent) of respondents indicated taking personal initiative to explore or implement AI solutions in their daily roles, signaling a bottom-up momentum driven by front-line professionals recognizing AI’s immediate benefits. At the organizational level, 27 percent of respondents affirmed that their companies had formally integrated AI tools within operational workflows. Moreover, 20 percent of respondents reported a dual approach: individuals proactively using AI concurrently with their organizations’ broader strategic investments.

When asked specifically about challenges in lease and rent roll reconciliation, respondents overwhelmingly cited manual data entry errors (60 percent) and system incompatibilities (33 percent). These findings underscore a clear vulnerability: The industry’s continued reliance on manual processes and fragmented technology stacks has created persistent data accuracy challenges that undermine operational integrity and compliance efforts.

AI solutions, such as automated lease auditing and real-time financial reconciliation platforms, offer an immediate path forward. By systematically eliminating manual data entry and enabling real-time error detection and correction, AI addresses the core of these structural challenges.

Qualitative responses regarding the market and AI’s role reflected cautious but pervasive optimism. Operators frequently described AI technology as “exciting,” “emerging” and “still maturing,” indicating broad recognition of AI’s potential yet a measured perspective on its current state. One respondent notably described AI as “just becoming a toddler, poised to take its first steps,” vividly capturing the collective sentiment of cautious anticipation.

This tempered optimism also acknowledges recent economic pressures, yet operators widely view AI as critical to enhancing efficiency, bolstering NOI, and maintaining competitiveness amid turbulent market conditions.

The survey’s findings offer critical guidance for real estate professionals evaluating AI investments. With operational inefficiencies clearly identified as systemic, AI adoption represents a logical and necessary progression. Operators should prioritize technologies that automate and integrate previously fragmented systems, reduce manual reliance, and embed accuracy into financial operations at scale.

For forward-looking operators, AI integration is increasingly fundamental to operational success, NOI growth, compliance robustness, and investor trust. Real estate leaders who delay embracing AI could risk continued erosion of financial performance, compliance and competitiveness in a market where precision and margins have become non-negotiable.

Ashkán Zandieh is the founder and managing director at the Center for Real Estate Technology & Innovation.