By Sudie Sengupta
The debate surrounding the merits of deploying enterprise platforms versus specialized real estate applications such as Integrated Workplace Management Systems (IWMS) has added a new contender, AI. With technology continuing to disrupt markets across industries, AI offers an opportunity to revolutionize how real estate services are managed and delivered. For corporate real estate leaders, adopting AI isn’t just about modernization; it is about positioning their functions as strategic partners in the C suite and driving enterprise-level value. Those who fail to act risk being left behind as AI reshapes operating models, roles, and business strategies.
Traditionally, corporate real estate has lagged in adopting advanced technologies. This hesitation stems from being perceived as a non-core function, challenges in coordinating multiple stakeholders, and a focus on routine operational tasks rather than strategic initiatives. Real estate has often been treated as a cost center, with decisions about portfolio strategy and capital investments made by finance or procurement teams. This has frequently led to missed opportunities to harness real estate’s potential to influence broader business outcomes.
Adopting AI strategically can help real estate leaders shift this narrative. Advanced technologies enable insights into critical factors like portfolio performance, occupancy trends, and market shifts—factors that directly impact business performance. By leveraging AI, real estate can transform from an operational necessity to a strategic differentiator, demonstrating clear links between real estate decisions and business impact.
The Evolution of Real Estate Technology
Real estate technology has evolved significantly, starting with enterprise ERP systems designed to manage data across finance and operations, which later incorporated basic real estate functions. The limitations of one-size-fits-all solutions led to the development of specialized real estate platforms such as IWMS, which integrated lease administration, space management, and other core capabilities.
Over the years, these systems have matured, offering additional functionalities like hybrid workspace management, regulatory compliance, and ESG tracking. Real estate service providers have also added their solutions, leading to a diverse ecosystem of technologies tailored to client needs. However, despite these advancements, barriers such as fragmented data, complex technology stacks, and organizational inertia remain significant challenges.
Challenges to Adopting Modern Real Estate Solutions
A survey by a leading consultancy revealed key challenges in adopting integrated real estate solutions:
- Integration Issues: 36 percent of respondents cited the lack of interoperability across enterprise systems as a significant barrier.
- Data and Process Standardization: 23 percent struggled with standardizing processes and data.
- Skilled Resource Deficiency: 12 percent faced challenges due to a lack of skilled personnel, impacting system performance.
Despite these hurdles, software vendors and service providers are making strides with SaaS solutions, collaboration tools, and automation to bridge gaps. Tools such as predictive analytics and performance dashboards are helping organizations streamline adoption and demonstrate the business value of advanced real estate technologies.
Real estate leaders today are prioritizing collaboration tools, smart building technologies, and immersive workplace solutions. The emphasis has shifted from cost-saving measures to enhancing employee experience, brand perception, and market competitiveness. This broader focus aligns with emerging trends in hybrid work, ESG goals, and digital transformation.
AI: The Next Frontier for Real Estate
The integration of AI into real estate technology offers transformative potential across three key areas:
- Growth and Scaling: AI can analyze workforce and space requirements, integrating market research and financial data to inform location strategies and site selection. This supports proactive growth planning and ensures alignment with business objectives.
- Capital Efficiency: AI-powered analytics can monitor market conditions, geopolitical trends, and energy prices to inform investment decisions and prioritize high-performing assets. Automation can also accelerate decision-making, reducing response times to market shifts.
- Operational Productivity: AI enhances operational efficiency through tools like Building Information Modeling (BIM) and Digital Twins. These technologies enable precise asset management, safety enhancements, and sustainability improvements, extending to lifetime asset performance and user wellness.
AI also offers solutions for challenges like right-sizing portfolios, forecasting future needs, and optimizing spaces for hybrid work models. For example, AI-driven data collection and predictive modeling can provide leaders with actionable insights, reducing the reliance on reactive decision-making.
Building the Foundation for AI Success
While the potential of AI in real estate is immense, its success depends on a robust digital core and data infrastructure. Leaders must address fundamental issues in their technology stacks and business processes before reaping AI’s benefits.
Key steps include:
- Streamlining Technology Stacks: Ensure interoperability and integration across existing systems.
- Standardizing Data and Processes: Create a unified data model that facilitates seamless analysis and insights.
- Upskilling Teams: Equip teams with the skills to adopt and operate AI-driven tools effectively.
AI in real estate is still in its early stages, with more questions than answers about its full potential. However, one certainty is its inevitability. Organizations that embrace AI early, invest in their digital infrastructure, and align their strategies with broader business goals will be the ones to succeed.
Corporate real estate leaders have a rare opportunity to lead from the front, redefining their roles and demonstrating their strategic value. By leveraging AI, they can ensure their function is not just a participant in the transformation but a driver of enterprise-level innovation. To succeed, they must act now, starting with a solid foundation in technology and a clear vision for AI’s role in their future.
About the author
Sudie Sengupta, Principal Director of Strategy and Consulting at Accenture, has spent over 22 years building expertise in the evolving interplay between people, real estate, and technology. His work spans Fortune 500 companies and government organizations.