The hybrid workplace is clearly the future of business property management. A vast majority of companies (over 90%) anticipate implementing a “Hybrid 2.0” model for their real estate operations within the next five years, encompassing strategies for space utilization, occupancy, and lease management. In contrast, reliance on purely manual or fully automated approaches remains niche, with only a small fraction of firms pursuing those paths.
This analysis will examine the contemporary deployment of artificial intelligence within commercial real estate, delineate the impediments to its efficacious adoption, and propose a methodical framework for optimizing its utilization.
The Climb Toward the Unknown Future
Gartner’s “hype cycle” diagram depicts the evolution of a technology’s acceptance and excitement levels. When a new technology’s buzz intensifies, it’s often seen as a perfect, effortless answer to all problems. In commercial real estate (CRE), AI is currently approaching the point of maximum expectations, where 89% of executives are convinced it can tackle significant industry obstacles.
This enthusiasm is backed by concrete actions: approximately 65% of businesses have begun testing AI applications in CRE and have launched professional development opportunities. Moreover, seventy-three percent of industry leaders are stepping up to integrate AI into their practices as pioneers in the field, incorporating AI to improve their everyday tasks. Simultaneously, a dynamic network of over 700 PropTech firms is actively creating AI-based solutions tailored for the real estate market.
On the verge of a harsh reality
The inherent pressure placed on emerging technologies often results in a period of letdown when real-world application proves challenging. This decline in optimism isn’t always rooted in the technology’s flaws, but rather in inflated hopes and the tangible obstacles that emerge during initial deployments, particularly in AI trials. These setbacks can stem from unclear strategic direction, impractical application scenarios, inadequate digital foundations, or inefficiently handled data assets
A recent Future of Work (FOW) study indicates that the Commercial Real Estate (CRE) sector is approaching a phase of unmet expectations. The study’s findings highlight a divergence between executive-level optimism and the realities of practical deployment. Specifically, while nearly 70% of top executives claim to have established an AI strategy for their CRE operations and are conducting pilot projects, only 33% of senior management confirm the existence of such a strategy. This disparity between strategic intent and actual implementation is also evident when comparing global and local organizational levels.
Instead of strategically implementing AI within commercial real estate (CRE), numerous organizations are impulsively launching AI initiatives and training programs, driven by current trends and lacking a well-defined plan. This haphazard deployment, devoid of a structured framework, will almost certainly result in setbacks and a subsequent decline in confidence regarding AI’s potential within the industry in the near future.
Cutting Through the Noise: A Methodical Approach to AI’s True Value
To avoid the common pitfalls of AI implementation, particularly in commercial real estate (CRE), a robust and deliberate strategy is crucial. CRE executives should shift their focus from mere technological buzz to a pragmatic methodology that prioritizes the practical application of AI, thereby unlocking its true value.
JLL advocates a phased implementation model, designed to guide CRE practitioners through the noise and directly towards the concrete advantages of artificial intelligence. This framework enables the identification of relevant AI applications, the development of compelling business justifications, and the establishment of firm buy-in from key stakeholders.
Correct misconceptions, recalibrate views, foster clarity
Misconceptions surrounding artificial intelligence are prevalent, often manifesting as anxieties like job displacement, expectations of effortless decision-making, or dismissals of its practical utility in commercial real estate (CRE). Although these beliefs may stem from partial truths, they frequently depict AI as an enigmatic entity with purely speculative potential.
Instead, a more accurate view of AI recognizes it as a tangible tool integrated into specific software solutions, each with defined boundaries. Organizations should develop their grasp of AI by focusing on existing products that deliver measurable benefits to CRE. This approach helps dispel the prevailing misconceptions that have hindered AI integration and fosters a realistic framework for creating effective AI-driven initiatives.
Within the CRE sector, AI tools are generally divided into two main categories:
- Businesses are adopting powerful AI-driven productivity platforms, which include generative language models comparable to ChatGPT, AI integrations within CRM systems, and AI-enabled communication aids. These deployments are fundamental to the broader enterprise AI strategy and are typically managed by the IT division.
- Specialized AI applications are emerging, tailored specifically for commercial real estate (CRE) operations. These solutions address a wide spectrum of CRE needs, from strategic capital project forecasting and asset portfolio optimization to enhancing occupant experiences and streamlining daily building maintenance, including energy and resource utilization. These areas represent prime opportunities for CRE professionals to leverage the transformative power of AI.
After examining more than 300 technological platforms utilizing artificial intelligence within the property sector, JLL determined that AI primarily serves as an integrated component within software architectures to refine issue resolution. Its function can be generally segmented into four domains: foundational proficiencies, like visual identification and creation; improved statistical analysis, such as more precise temporal forecasting; novel user interaction methods, including conversational systems for information and analytical inquiries; and streamlined operations, like automatic data input and normalization.
Optimal AI platforms crafted for Commercial Real Estate are built to emphasize intuitive interfaces and streamlined adoption, harmonize smoothly with established infrastructures, and possess the capability to manage limited information while providing avenues for information creation. Fundamentally, these tools enable CRE specialists to overcome their complex obstacles.
Spot valuable applications and rank them through a cyclical method
During periods of intense excitement surrounding artificial intelligence, numerous organizations incorrectly perceive the integration of AI as the ultimate objective, instead of a tool to address their operational hurdles, frequently resulting in disappointment. A cyclical method, encompassing repeated rounds of examining both internal and external elements—like operational difficulties, institutional AI competence, existing technology frameworks, and the accessibility of AI solutions—is necessary to recalibrate anticipations, eliminate unfeasible implementations, and sharpen the emphasis on enduring and impactful deployment.
Real estate specialists must weigh their chief concerns, present operational routines, established frameworks, accessibility and proficiencies of available solutions, alongside implementation expenses and fiscal resources. This utility-driven approach will pinpoint the most valuable artificial intelligence applications among practical options and rank them based on the organization’s unique circumstances.
Strategic placement involves tailoring to the customer base, examining emerging patterns, evaluating expenses, securing advantageous funding, and efficient property acquisition. Asset refinement encompasses uniform data organization and presentation, hazard evaluation, area projection, hypothetical planning, and rigorous portfolio strategy evaluation. Building development and execution entail rapid conceptual revisions, vendor network improvement, expense projections, flexible timeline adjustments, and building site oversight. Rental management includes uniform rental agreement summarization, computerized file management, regulatory adherence monitoring, and automated financial reviews. Ecological planning incorporates power usage analysis and simulation, adaptable energy procurement, model-driven carbon footprint reduction plans, and automated climate control systems. Office space and usage involve floor layout digitization, presence detection, spatial usage trend identification, and adaptive workspace arrangement. Operational upkeep entails proactive servicing and cleaning, stock examination and procurement improvement, and computerized documentation. Staff satisfaction includes tailored climate regulation, user-friendly room and workstation reservation with automatic schedule synchronization.
Be at the forefront of crafting a persuasive case for AI adoption
A significant portion of present-day artificial intelligence expenditures focus on corporate-scale deployments or the modification of fundamental organizational procedures. Consequently, commercial real estate groups must be forward-thinking in proving that allocating resources to AI within the CRE sector will enable it to more effectively aid the larger entity. This entails actively demonstrating the prospective value and strategic benefits of AI adoption to secure necessary funding and support.
Specifically, it is crucial to exhibit how artificial intelligence can generate novel understandings, improve judgment calls, simplify data gathering and examination, advance the office atmosphere, boost procedural effectiveness, and produce power conservation. Navigating the step-by-step method outlined earlier will assist them in comprehending the commercial rationale and advocating for it. This structured approach facilitates a clear understanding of the potential return on investment and strengthens the argument for AI integration.
When constructing the financial justification for AI within commercial real estate, specialists should encourage executives and collaborative divisions to contemplate the workspace of tomorrow that bolsters and facilitates Hybrid 2.0—the combination of human and computerized techniques. They must illustrate how AI could strengthen a forward-looking CRE squad and the repercussions it will have on diverse departments across the company. This involves articulating a vision for the future, highlighting the transformative potential of AI, and demonstrating its broad impact on the organization’s operations and strategic goals.
Strengthen C-suite involvement to propel AI efforts in commercial real estate
A prior assessment by JLL, the Worldwide Property Technology Analysis, conducted the previous year, revealed that choices regarding the integration of technological solutions within a corporation’s commercial real estate division constitute an intricate procedure, necessitating input from various participants. Around 50% of the individuals surveyed indicated that those responsible for technology and pioneering initiatives participate in the decision-making; about a third also reported the participation of building operations, 31% environmental stewardship, and 30% accounting groups.
Within this interconnected network of interested parties, executive level sponsorship represents a pivotal component for positive outcomes. The analysis of technological solutions determined that organizations are three times more apt to achieve a prosperous commercial real estate tech initiative when top executives were actively associated with it and participated in monitoring advancement, rather than merely receiving the final outcomes.
Regarding artificial intelligence, backing from senior management is particularly indispensable. It aids in harmonizing competing financial demands, obtaining essential assets, and granting authorization for the initial expenditure required. Furthermore, this sponsorship guarantees organizational endurance throughout the preliminary experimentation period, which is fundamental prior to the profitability becoming apparent.
Recasting obstacles as opportunities for improvement
Those surveyed by the Future of Work study pinpointed several obstacles hindering AI integration within commercial real estate; however, these difficulties can be reframed as chances to strengthen CRE’s electronic proficiencies across an extended period. Regarding financial outlay and fiscal constraints, employing a repetitive evaluation method for AI tools will yield data on expenses and advantages, substantiating use cases where the merits exceed the expenditures. Concerning information integrity and accessibility, AI platforms can be utilized to refine data procedures and procure premium information, consequently bolstering justifications for expanded AI adoption. Lastly, concerning information and online defense hazards, CRE executives must collaborate with technology departments and reliable third-party vendors to cultivate a secure and regulation-abiding setting.
With enterprises embracing the next phase of blended work arrangements, the heightened potential of artificial intelligence platforms could spark revolutionary advancements in commercial real estate and the broader marketplace. To capitalize on this strength, property managers should confront the hurdles of AI integration directly, collaborating with specialists, pinpointing optimal resources and systems, and gleaning insights from leading sector methodologies to develop their tactical approach.
