Artificial Intelligence (AI) has rapidly moved from buzzword to boardroom agenda across most industries. Yet in Commercial Real Estate (CRE), adoption remains modest. Despite the sector’s deep reliance on information (leases, valuations, occupancy data, and market comparables, etc.) many firms still struggle to manage their data effectively, let alone put it to work in advanced analytics or AI.
Our CRE Analytics Maturity Survey confirms this lagging position. Compared to sectors like Financial Services and Retail, which monetize both BI and AI at two to three times the rate of CRE, the industry remains behind in every tier of maturity. Stabilization has improved year over year, but optimization and monetization lag significantly, especially among mid-market firms.
For CRE executives, this is both a challenge and an opportunity. Falling further behind carries risk; but because the industry is still in the early stages, forward-looking firms have a rare chance to seize advantage. This guide offers practical steps to prepare your organization for AI, starting with the foundation that will determine every future success: your data.
Elevating Data Treatment in CRE
The first and most critical step is to recognize data as a strategic asset, not an operational byproduct. Too often, data entry is treated as a back-office requirement – something done to satisfy reporting obligations rather than to power insight and innovation.
CRE companies generate enormous data streams: property performance, tenant interactions, energy use, maintenance, valuations, and financing. But this information often lives in disconnected systems, captured inconsistently and at varying levels of quality. Without intervention, it remains unusable in practice, its value untapped.
The foundation of an AI strategy requires elevating how data is treated across the enterprise. That means:
- Centralizing it in a single warehouse or data lake to break down silos and create a unified source of truth.
- Cleansing it to remove errors, duplicates, and inconsistencies that undermine trust in analytics.
- Enriching it with contextual attributes, from external market data to IoT feeds from smart buildings, that expand its insight potential and industry coverage.
This work is not glamorous. It will not appear in a pitch deck or investment brochure. But it is the bedrock for every advanced use-case that follows.
Advanced BI as a Gateway to AI
Business Intelligence (BI) represents the natural first payoff for these efforts. Many CRE firms already use dashboards, but according to our survey, most are still at a “descriptive” stage: presenting past performance, but not predicting or prescribing future action.
With clean, centralized, and enriched data, BI can advance into true decision support:
- Predictive occupancy analytics that forecast vacancy trends.
- Scenario planning for acquisitions, dispositions, and refinancing.
- Portfolio benchmarking to identify outlier properties by performance.
- Automated alerts that embed responses directly into workflows.
These advanced BI capabilities can deliver real value quickly and build organizational confidence in data-driven practices. They also start momentum for the key cultural shift that is necessary to take the next step into AI.
Identifying Impactful AI Use-Cases
The temptation with AI is to chase what is flashy rather than what is valuable. CRE leaders should resist the allure of proof-of-concept projects that demonstrate technical novelty without business impact.
A better approach, and one we recommend, is to start with the business, not the algorithms. That means:
- Assessing where the company generates the most value and where it incurs the most cost.
- Mapping pain points and opportunities across functions – leasing, asset management, operations, finance.
- Scoring potential AI use-cases by feasibility and impact.
This disciplined method surfaces projects that matter – ones that executives will support and frontline teams will embrace because they improve business results.
In CRE, high-potential use-cases often include:
- Automated underwriting to accelerate deal flow and reduce manual review.
- Tenant retention prediction that highlights at-risk leases before renewal deadlines.
- Counterparty risk models to evaluate financing and joint venture partners.
- Predictive maintenance that cuts operating costs and improves tenant satisfaction.
- Valuation modeling that updates dynamically as market conditions shift.
These are not futuristic concepts. They are practical applications with clear ROI potential, provided the data foundation is in place.
The Role of Leadership
Technology alone cannot transform a CRE company. Senior leadership support and vision is essential. AI initiatives touch core operations, require investment, and demand behavioral change across the organization. Without sponsorship from the top, they risk stalling at the pilot stage.
Leaders set the tone by:
- Articulating why AI matters and has real ROI as a driver of revenue, valuation, and competitive advantage.
- Setting realistic expectations about timelines and ROI, avoiding hype but maintaining urgency.
- Ensuring cross-functional collaboration so that data, IT, and business units align around shared objectives.
AI is not just an IT project! It is an enterprise-level strategic initiative. And like any strategic initiative, it succeeds only when leadership treats it as such.
Addressing Staff Concerns
Equally critical is how AI is communicated to staff. In CRE, many employees worry that automation could replace them, or that they will be asked to do more without receiving tangible benefits. These concerns are natural, and if ignored, they can derail adoption.
The solution is to deliver value in exchange for responsibility. Asking staff to enter cleaner, richer data should come with a payoff: AI-enabled tools that make their jobs easier, not harder.
That might mean:
- Providing leasing teams with AI-driven lead scoring so they focus only on the most promising prospects.
- Giving asset managers predictive dashboards that simplify portfolio oversight.
- Equipping property managers with maintenance alerts that reduce emergencies and improve tenant experience.
When employees see that AI makes them more effective, their perspective shifts. They stop viewing it as a threat and start viewing it as an ally.
The Fastest-Expanding Frontier
Among all aspects of business today, AI is changing the fastest. It is also the area with the highest risk and reward. Unlike accounting or compliance systems that evolve slowly, AI capabilities and use-cases are advancing monthly. What was impossible last year may be standard next year.
For CRE firms, this dynamism creates both opportunity and risk: the opportunity to leapfrog competitors who remain hesitant, and the risk of falling further behind if the window is missed.
If Outside Expertise Makes Sense Anywhere… It Makes Sense HERE
Given this accelerating pace of change, CRE leaders should consider where internal teams can reasonably build capability and where outside expertise is required. AI is not like traditional IT projects. The skills, tools, and frameworks evolve too quickly, and the consequences of missteps can be costly.
Outside expertise provides not only technical knowledge, but also cross-industry perspective on what has worked elsewhere and how to adapt it to CRE’s unique dynamics. And when that expertise can be accessed affordably, through models like our flagship CIO IQ® offering, which delivers enterprise-level IT and AI strategy guidance at affordable pricing… the case becomes compelling.
Rather than attempting to build all expertise in-house, CRE firms can leverage external specialists to guide strategy, establish the roadmap, and mentor internal teams through the transition. This hybrid approach balances affordability with effectiveness.
Moving from Lagging to Leading
Our survey findings paint a picture of an industry that has stabilized, but not yet optimized or monetized, its data and analytics capabilities. CRE lags well behind Financial Services and Retail, and is closer to the slowest-moving sectors such as Education and Residential Real Estate.
But the story is not finished. CRE still has the chance to catch up, and even to redefine what AI means in the built environment. Firms that elevate their treatment of data, build advanced BI, and identify impactful AI use-cases will discover that technology is not just a back-office tool, but a growth engine.
The opportunity is wide open. The firms that act decisively, with leadership support, employee engagement, and external expertise, will not just close the gap. They will set the pace.
