Commercial real estate believes in AI. The problem is that many organizations still aren't prepared to use it effectively.

Recent research from MRI Software found that 82% of commercial real estate professionals believe AI is important to the industry's future success. Yet 54% report that their organizations offer no AI training whatsoever. Nearly 600 commercial real estate professionals across the U.S. participated in the survey.

The findings suggest that commercial real estate's challenge is no longer deciding whether AI matters. Instead, the challenge is building the trust, skills, and processes needed to gain meaningful adoption and results.

Despite the consensus that AI has the potential to transform the industry, respondents expressed three major fears:

• AI will bypass human decision-making
• Returns cannot justify the investment
• Training is insufficient

How can building owners, developers, and facility managers address these concerns and reduce barriers to adoption?

Fear #1: AI Will Replace Human Judgment

One of the most consistent themes that emerged from the survey was a desire to keep people at the center of decision-making. Respondents expressed concerns about data accuracy, security, hallucinations, and overreliance on AI-generated outputs. Many emphasized that AI should support professionals, not replace them.

That perspective is especially understandable in commercial real estate, where decisions often involve nuanced tradeoffs, tenant relationships, regulatory considerations, and operational realities that cannot be reduced to an algorithm.

The most successful organizations are positioning AI as an assistant rather than an authority. AI can help analyze maintenance records, identify patterns in utility consumption, summarize inspection reports, surface potential risks, and recommend the best action to take. Some platforms can even autonomously execute the recommended action based on the rules and guardrails set up by the organization. But human experts are still essential to review the findings and make final decisions.

For facility managers and building owners, establishing clear governance can go a long way toward building trust. Defining when AI can be used, where human review is required, and who ultimately owns decisions helps employees view AI as a tool that enhances expertise rather than threatens it. AI can help get the work done, but accountability remains with the human.

When organizations reinforce the message that people remain accountable, many fears surrounding AI adoption begin to diminish.

Fear #2: The Benefits Feel Unclear or Too Small

Many commercial real estate businesses struggle to justify AI investments because they approach the technology as a transformational initiative from day one. When expectations are set too high, it becomes difficult to demonstrate value quickly.

Rather than pursuing large-scale transformation immediately, facility teams may see better results by focusing on practical, day-to-day applications that solve specific operational challenges and create measurable improvements. The survey points to several areas where commercial real estate professionals already see potential for AI, particularly in operational and administrative workflows.

For building owners and facility managers, that could mean starting with targeted uses such as:

• Automating maintenance requests and work orders by using AI agents to manage and route tenant requests, alert the technician, create the work order, and provide status updates to the requestor.
• Supporting proactive maintenance by identifying equipment performance trends and highlighting issues that may require attention before they become costly failures.
• Improving service delivery by reducing manual effort in routine administrative workflows, such as organizing documentation, preparing updates, and responding to common tenant inquiries.
• Streamlining reporting requirements by compiling information from multiple systems and helping teams produce more consistent operational reports.
• Enhancing vendor coordination by organizing communications, summarizing activities, and helping teams track follow-up items across service providers.
• Supporting portfolio planning through CAM reconciliation support, forecasting assistance, and trend analysis across properties.

These types of use cases are easier to measure, easier to govern and often easier for employees to understand than broad enterprise AI initiatives. They also help leaders establish practical benchmarks from the outset, such as time saved, fewer manual steps, faster reporting cycles, or improved consistency across assets.

The key is to start with problems that people are already trying to solve. When employees experience tangible improvements in efficiency and productivity, organizational confidence naturally grows. Small wins can create the momentum required for broader adoption later.

Fear #3: Employees Aren't Being Taught How to Use AI

Of all the barriers identified in the survey, the lack of training may be the most solvable and urgent.

Although 62% of respondents said their organizations are preparing for AI in some way, more than half reported that no AI training is available. Among organizations that do provide training, the most common focus areas are usage guidelines and responsible use rather than practical skills that help employees generate better outcomes. Only 16% reported receiving training on source validation, while 14% reported training on prompting techniques.

This gap matters because AI delivers value only when users understand how to work with it effectively.

Successful adoption requires more than putting policies in place. Employees need practical instruction that helps them apply AI in real business situations. For facility teams, training should focus on the workflows employees perform every day, not just general AI awareness.

Organizations should think about AI education in three layers:

• Responsible use, including privacy, security, and governance requirements.
• Practical application, including how to construct effective prompts and workflows.
• Critical evaluation, including how to verify information, recognize limitations, and validate outputs.

When employees understand not only what AI can do but also how to assess its results, confidence increases and risk decreases.

Building the Foundation for Long-Term Success

Commercial real estate professionals are not resistant to AI—they recognize its importance and see potential value across numerous business functions. What they want is confidence that the technology can be implemented responsibly, effectively, and in ways that support their work.

That is why successful adoption depends on more than technology alone.

Organizations need reliable data, connected systems, practical governance, and meaningful training. They need leaders who can communicate where AI fits into broader business goals and employees who understand how to use it productively. Most importantly, they need a clear understanding that AI is not a replacement for expertise, but a tool that can help experienced professionals work more efficiently and make more informed decisions. Ultimate accountability remains with the human, not the AI.

Commercial real estate has always evolved in response to changing technologies and market conditions. Organizations that can build trust in AI today through clear governance, meaningful training, and practical use cases will be better positioned to uncover new efficiencies, make faster decisions and adapt to future challenges.