Beyond the Hype: Real-World AI Implementation in Real Estate and Construction Project Management

The real estate and construction industries stand at a pivotal moment where various forms of artificial intelligence (AI)  are rapidly transitioning from experimental novelty to operational necessity and even strategic advantage. While much of the conversation around AI in real estate and construction remains focused on theoretical possibilities, the reality is that several practical applications are already reshaping how projects are planned, managed, documented, and delivered.

At Real Projectives, we’ve moved beyond the hype to hands-on implementation, discovering both the transformative potential and practical challenges of integrating AI into real estate and construction project and program management. We’ve learned that successful AI adoption isn’t about trying to use every new tool that emerges—it’s about thoughtful trial and strategic implementation  to build organizational capability for the technological and human transformations that lie ahead.

AI Applications

Most professionals are becoming familiar using generative AI chat bots and note-taking tools for meeting minutes.  Additionally, we’re seeing AI applications unfold in:

• Document Analysis: Agentic AI tools can quickly review reports, contracts, and other documents to summarize key elements and to suggest clearer language. They can also help to simplify the responses and analyses about requests for information (RFIs)—those critical Q&As between contractors and design teams that can make or break project budgets and schedules.  This increases efficiency and reduces errors.
• Site Documentation and Progress Tracking: AI-enhanced tools can automatically process construction photos and videos to identify items, track progress, document as-constructed conditions and create visual and data-enhanced records of the infrastructure behind walls and within floors and ceilings before they’re closed. This has the potential to better track work and provide valuable information to be used in the maintenance phase of a property.
• 3D Scanning and Modeling: For renovation projects laser scanning tools with AI interpretation can automatically and quickly locate and measure walls, doors, windows,  and other building elements of existing conditions.  This saves an incredible amount of time, allows for better designs and fewer surprises during construction.
• Digital Twins: One of the most promising and challenging applications of AI in construction involves creating comprehensive digital twins—complete digital replicas of physical assets that contain all data about design, construction, and operational performance throughout the life of the property. The value proposition is compelling for current and future owners. Instead of struggling to locate documents about the property to address maintenance or emergency issues, the facilities team can plan for contingencies and capital renovations and pursue predictive maintenance over reactive maintenance (fixing things when they break). Scheduled preventive maintenance AI agents can monitor systems and space use continuously, analyze performance data, and predict when equipment might fail, or even act before problems and negative impacts occur.

Preparing Teams for AI Integration

Successfully leveraging AI for business requires more than just purchasing and using the popular tools—it demands rethinking how work gets done and a myriad of organizational changes to the present and future.

While AI technology is challenging on its own, how organizations deal with the human experience will be even more important.  Knowledge itself will become less valuable when a query by an AI agent can find and process large data sets in short order.  What should humans do vs. what should AI agents do?  And how do we help our colleagues, even those well-educated, not get left behind?

Real Projectives’ current approach to AI includes:

• Ongoing training sessions on both AI potential capabilities and realistic limitations
• Raising awareness on how and where sensitive and proprietary data is used by AI providers
• Hosting monthly lunch-and-learn sessions where team members share their AI experiences, excitement, fears, successes and frustrations
• Establishing guidelines on when to use what AI tools versus human judgment; and the need to check all generative documents before releasing them to clients or the public
• Creating custom AI agents for internal and external use cases
• Challenging ourselves as to how we have been doing work to advance our methods toward more valuable and effective services for our clients and our colleagues
• Charting a strategic path forward incorporating AI tools and associated human oversight

AI Vendor Selection: Critical Questions You Should Ask

When evaluating AI-enabled real estate and construction technology vendors, we’ve learned to focus on several key factors that extend beyond immediate functionality:

• Long-term Viability: Will this vendor be around in five years? Can they clearly articulate their product roadmap? We’ve ruled out several vendors simply because they couldn’t explain where their technology was heading.
• Data Security: Where will our data be stored and processed (U.S. or oversees)? How will they use and protect our data? Will our data be used to train their models and therefore, become public in any way?  To what extent do they have reliable data backup and recovery methods? Our data belongs to us, and we don’t want any personal, confidential or proprietary data to be compromised.
• Exit Strategy Planning: We now start vendor evaluations by understanding how to end the relationship. If we can’t easily get our data back without excessive cost or complexity, we don’t move forward. Doing so can be more painful than switching banks or doctors. This “exit planning” first approach has proven invaluable.
• Integration Capabilities: How easily will their solution talk with or integrate with our other existing technology stack? We’ve found many vendors want to control and possess client data, making it difficult interface with other essential vendors. But no single vendor provides the best of all breeds, so that’s not how modern business is done.  The best AI tools are those that enhance rather than replace our current workflows.

Practical Implementation Strategies

Based on our experience, successful AI implementations require:

• Start Small and Focused: Begin with clearly defined use cases rather than attempting comprehensive transformation. We recommend starting with tools that address specific pain points and expanding gradually based on proven success.
• Maintain Parallel Processes: During transition periods, run both traditional and AI-enhanced processes to ensure continuity and validate results.
• Ensure Data Security: Be particularly careful with meeting recording tools and other AI applications that might expose sensitive or confidential information to foreign entities or unsecured systems.
• Invest in Team Training: Successful AI adoption requires changing how people think about their work, not just learning new software interfaces.
• Conduct Regular Evaluation: Continuously measure results and adjust approaches based on real-world performance rather than theoretical capabilities.

The Competitive Imperative

The incredible pace of evolution in AI capabilities and what is anticipated over the next decade, means that waiting for the technology to fully mature isn’t a viable strategy. However, jumping in without caution could cause your firm to lose time, money and reputation.  Firms that begin intentional experimentation and purposeful implementation now will develop the expertise and organizational capabilities needed to leverage more advanced tools as they become available.

The question isn’t whether AI will transform real estate and construction project management—it’s whether your organization will either be ready to take advantage of that transformation or be left behind.