Table of Contents

• Where AI offers the greatest efficiencies
• Case studies: early adopters seeing real impact
• Broader functions where AI will play a transformative role
• Strategic implications & positives for the job market
• Key challenges & what companies must do now
• What the future may look like
• Conclusion

In 2025, the real estate sector stands on the cusp of a sweeping transformation driven by Artificial Intelligence. Long seen as a labor‑intensive industry, real estate, from commercial to residential, from self‑storage to asset management, is increasingly embracing AI not just as a novelty, but as a tool for serious operational leverage. According to a recent analysis by Morgan Stanley Research, AI has the potential to automate 37% of the tasks currently performed in REITs and commercial real estate (CRE) firms, generating upward of $34 billion in operating efficiency gains by 2030.

In this article, we explore where AI delivers most value in real estate, how companies are already reaping benefits, and what organizations should do to prepare for this wave of change.

Where AI offers the greatest efficiencies

Morgan Stanley’s analysis of 162 REIT and CRE firms, together responsible for roughly $92 billion in labor costs and some 525,000 employees, identifies several domains where task automation is most feasible. Key among them:

• Management: Strategic oversight, scheduling, portfolio analytics.
  
• Sales and related activities: Lead qualification, customer interaction, and even parts of outreach and marketing.
  
• Office & administrative support: Document generation, data entry, scheduling, reporting.
  
• Installation, maintenance, and repairs: Predictive maintenance, automated repair scheduling, and remote diagnostics.
  

In each of these areas, a substantial portion of recurring, rule‑based, or predictable tasks is amenable to automation or augmentation via AI systems.

Case studies: early adopters seeing real impact

Real-world examples already illustrate the magnitude of productivity gains:

• A self-storage company reports that 85% of customer interactions are now handled through customer-selected digital channels. Using AI‑powered staffing optimization, they have reduced on‑property labor hours by 30% while maintaining or improving client satisfaction.
  
• In the residential real estate sector, firms have reduced full‑time headcounts by about 15% since 2021, yet report increased productivity, enabled by AI tools assisting in operations, customer service, leasing, and maintenance.
  

These aren’t marginal improvements. There are structural shifts in how real estate businesses operate.

Broader functions where AI will play a transformative role

Beyond the examples above, generative AI (GenAI) is poised to make a significant impact across various dimensions of real estate operations. Some of the most promising include:

These use cases are not futuristic fantasies; many are already being piloted or deployed in leading firms.

Strategic implications & positives for the job market

While automation often raises concerns about job losses, the picture in real estate may be more nuanced and even positive.

• By automating repetitive, low-value tasks, human staff can shift their focus to higher-value work, such as strategy, relationship building, customer experience, and creative problem-solving.
  
• For clients, the experience improves: faster responses, more accurate forecasts, better property maintenance, and more consistent service.
  
• Internally, companies see gains in staff satisfaction when tedious work is reduced, and when teams can engage in more meaningful, skilled tasks.
  

Also, as AI tools scope more value in real estate, this may catalyze investment in adjacent industries: PropTech startups, data infrastructure, and intelligent building technologies. That, in turn, may create new jobs and markets.

Key challenges & what companies must do now

To capture the $34 billion opportunity by 2030, real estate firms will need to overcome several obstacles. Here are critical actions to consider:

1. Data readiness & infrastructure
   AI thrives on quality data. Many firms have silos: property datasets, maintenance records, customer‑service logs, and financials. Making data accessible, clean, and interoperable is foundational.
   
2. Change management & culture
   Automation changes roles, workflows, and expectations. Leadership needs to communicate clearly, train staff, and ensure that AI is seen as an enabler, not simply a cost‑cutting measure.
   
3. Choosing the right tools & partners
   Not all AI solutions are equal. Firms should evaluate based on domain fit (real estate), integration capability (existing property systems, leasing, maintenance), compliance and privacy, and vendor reliability.
   
4. Regulation, ESG, and ethics
   AI systems will need to comply with data privacy laws, labor regulations, and fairness and transparency norms. Also, in the growing focus on environmental, social, governance (ESG) standards, AI can both help (e.g., energy optimization, ESG reporting) and hinder (if data is opaque or biased).
   
5. Scalability & iterative deployment
   Pilot projects often deliver proof of concept; the challenge is scaling while maintaining quality and reliability. Iterative development, feedback loops, and measurement of ROI are essential.
   

What the future may look like

Looking ahead toward 2030, here are some of the emerging trends likely to shape the future of AI in real estate:

Intelligent, Sustainable Buildings: Buildings engineered from the ground up to be AI‑ready, with embedded sensors, dynamic energy management, adaptive climate control, access control, and predictive maintenance. Net‑zero performance and carbon tracking may become default features

“Space as a Service” models: Flexibility in how tenants lease, use, and pay for space. AI will help forecast usage, optimize layouts, and deliver personalized experiences for occupants.

Smarter transactions and predictive underwriting: AI will enable more accurate risk assessments, quicker and more transparent due diligence, scenario planning for acquisition or development.

PropTech ecosystem maturation: More startups scaling up with specialization (AI for maintenance, tenant experience, ESG, etc.), better capital flows, and increasing deployment of VC‑backed solutions.

Conclusion

For real estate firms, the message is clear: AI is not just an efficiency enhancer—it’s a strategic lever. The estimated $34 billion in potential gains by 2030 represent real opportunities for those who act now. As we’ve seen in self-storage, residential firms, and across CRE/REITs more broadly, AI’s impact is already being felt in productivity, customer satisfaction, and leaner operations.

At Neodata, we believe embracing AI with clarity, integrity, and foresight will unlock new heights of innovation and value in real estate. For companies willing to invest in data infrastructure, culture, and strategic deployment, the gains are not just financial; they’re transformative.