The future of work survey 2026

Today, an overwhelming 78% of business and CRE leaders recognize that AI will significantly impact their portfolio strategies and CRE function over the next 3-5 years. Yet only 15% have progressed beyond exploration and initial deployment to actively optimize AI in their CRE operations and prepare for AI-driven organizational change. This gap reflects the complexity of assessing the impact of a technology still in the early stages of enterprise adoption, where the effects on the workforce are unclear and most companies remain in evaluation mode.

Capturing perspectives from over 2,200 C-suite executives and CRE leaders across 21 countries, our research reveals three critical challenges.

• First, portfolio decisions await clearer enterprise workforce strategies. Real estate transformation depends on CEO and CHRO decisions around which roles AI will transform, how collaboration patterns will evolve and where talent will concentrate.
• Second, skills gaps now exceed budget constraints. For the first time in 15 years of this research, the primary barrier to CRE value creation is not money; it’s a shortage of future-ready talent.
• Third, an aspiration-affordability disconnect. Organizations aspire to AI-enabled, premium-quality portfolios but face dual investment pressures—rising baseline costs (rental, energy, OpEx) layered with new AI infrastructure and technology demands.
   

The 15% of organizations that are successfully navigating these challenges are focusing on systematically resolving constraints within their control, while building adaptive capacity – at a portfolio and structural level – for forces they cannot predict.

Building for a different world of work

There is a pattern to how organizations approach AI transformation for their CRE operations. Most leaders are watching closely: 46% actively monitor AI trends and 40% are analyzing implications for their CRE function. But when moving from analysis to action, only 33% are actively modeling the potential effects on their portfolios across locations and asset types.

Those organizations further ahead in their transformation journey don't have greater certainty about their organizational future. They develop agile planning to bridge AI's rapid cycles with CRE's longer-term commitments. This is important in a context where real estate transformation depends on enterprise workforce decisions that happen at the CEO and CHRO level: Which roles will AI fundamentally transform? How will collaboration needs shift when certain tasks become automated?

The path forward requires dual capability building: developing organizational readiness and portfolio elasticity for rapid execution when direction emerges, while simultaneously building the market intelligence infrastructure to track labor transformation trends and forecast workforce needs - shifting CRE from reactive executor to strategic advisor.

A broadly positive outlook
 

Despite an environment where workforce composition continues to evolve, most organizations are anticipating net headcount expansion and prioritizing full-time employment, with AI redesigning roles and increasing talent accessibility by shifting the workforce toward higher-value activities.

This reflects the complex nature of AI-driven workforce transformation: targeted reductions in some areas, strategic expansion in others, with overall growth for organizations successfully navigating the transition.

Other critical decisions show no clear trend and reflect that different organizations and industries will have varied talent location strategies and business requirements. They will therefore develop distinct approaches to talent distribution, reliance on entry-level hiring and emphasis on in-person collaboration.

A look at the 15% who act differently: growth conviction, resilience culture, long-term perspective
 

While most organizations remain in the early or mid-stage of AI adoption for their CRE operations, with a long road to maturity still ahead, a distinct minority operates under different assumptions and organizational models. 15% of organizations have reached the "optimizing" phase of AI adoption in CRE operations and have different characteristics.

These companies have higher expectations for workforce expansion because they view AI as enabling growth opportunities, not just increasing efficiencies.

Their execution advantage comes from their ability to build adaptive capability, as well as technological sophistication. They are effective in cross-functional collaboration across a series of strategic dimensions: organizational resilience, employee productivity and performance, organizational innovation and vibrancy of organizational culture.

These organizations are able to absorb macro shocks into their business strategy. They are also more likely to have fully incorporated the impact of cyber and physical security threats into their CRE strategy.

This culture of preparedness creates operational resilience that enables faster transformation when enterprise direction becomes clearer.

CRE optimizing what's measurable vs what the C-suite values most
 

More than ever, CRE teams face a clear mandate from the C-suite that goes beyond optimizing costs: they are expected to deliver measurable impact on employee productivity, organizational innovation and organizational resilience. This highlights a significant shift toward stronger business enablement, further evolving CRE's role from cost manager to strategic value creator.

Yet CRE leaders face a measurement challenge. They can measure energy, space utilization and cost per square foot, but measuring how real estate enables productivity, innovation or organizational resilience requires longitudinal studies, employee surveys and the type of models which most CRE teams lack the capability to deploy today.

A tangible CRE contribution to these desired business outcomes is rapid portfolio reconfiguration - the ability to quickly adapt space as business needs evolve. CRE teams tend to focus more on this goal, which could eventually serve their C-suite’s agenda. Organizations that can reconfigure at speed through elastic CRE portfolios will enable their workforce to respond faster to market shifts and be able to test new work models without lengthy real estate lead times.

Skills gaps now exceed budget constraints
 

For the first time in 15 years of this research, skills gaps have overtaken budget challenges as the key constraint on real estate transformation, namely skills gaps in AI, analytics and emerging technologies.

The capability deficit also involves limited change management expertise to adapt to AI-driven transformation, operating within organizational silos and difficulties in reporting the right metrics to demonstrate CRE’s value to the business.

This helps to explain why so few organizations progress beyond monitoring and analysis to portfolio action. Even organizations with adequate budgets cannot drive change if they lack the AI expertise to guide technology selection, the change management capability to drive adoption, the cross-functional collaboration to align with business strategy or the measurement tools to demonstrate value.

Strategic aspiration toward premium, technology-enabled, experience-rich portfolios
 

When asked to choose between strategic trade-offs that will drive real estate investment in the future, clear patterns emerge. Organizations prefer long-term strategic positioning, AI-driven building optimization, building quality and amenities, customized user experience and "surplus" space to accommodate future growth.

These choices indicate genuine strategic aspiration toward premium, technology-enabled, experience-rich portfolios designed to attract talent and enhance performance as organizations pursue their AI transformation journey.

The technology dilemma
 

The productivity agenda creates a critical tension. Organizations are prioritizing advanced technology, AI support and reliable technology infrastructure to support employee productivity, with less investment in physical space elements like adaptable individual spaces, activity-based workplaces or wellbeing amenities. However, these workplace elements are equally critical to cognitive performance and to how people think, focus, connect and collaborate with each other. Natural light, acoustics, thermal comfort, movement and dedicated focus zones are functional requirements. Technology and workspace experience should not be competing priorities; together, they should form the foundation for sustained cognitive performance.

Technology also creates potential vulnerabilities - three of the top four risks threatening CRE portfolios are technology-related: cyber security and data privacy (47%), technology/AI disruption (41%) and uncertainty of AI impacts on space requirements (40%). This is the technology dilemma at the heart of the C-suite roadmap: organizations must invest heavily in technologies that simultaneously enable productivity and introduce new vulnerabilities—requiring strategies that mitigate rather than compound risk.

An affordability disconnect
 

AI transformation also reshapes the total cost of occupancy (TCO) equation, creating a mismatch between strategic aspirations and what organizations can realistically afford to do:
 

• External cost pressures dominate: Day-to-day running costs - energy and utilities, operating and maintenance - combined with inflationary pressures and labor/facilities management costs create unavoidable baseline TCO growth that constrains strategic investment capacity.7
• New technology investment layer on top: AI-driven workforce automation and technology infrastructure requirements represent new CapEx demands separate from traditional upgrade and maintenance programs, forcing reallocation of already-constrained capital budgets.
• AI-optimizing organizations accept higher TCO strategically: The 15% actively optimizing AI in their CRE operations expect higher TCO growth but frame this as strategic investment in technology, workforce automation and premium amenities rather than cost burden.

CRE leaders face competing priorities with incomplete information—workforce strategies remain fluid, AI's impact on space is unclear and cost pressures continue to intensify. Rather than waiting for greater clarity, the 15% who are at the AI optimization stage have been building the capacity to adapt.

Three strategic actions from leading organizations
 

Action 1: Address capability gaps while preserving future optionality

Leading organizations close skills gaps and build organizational resilience through three approaches:

• Strategic partnerships for immediate capability access
  Partner with trusted advisors for AI implementation and specialized analytics where internal expertise doesn't exist. Keep strategic control and governance internal and focus internal teams on CRE orchestration – while relying on external partners for execution.
• Capability building for sustained advantage
  Invest systematically in measurement infrastructure, scenario planning skills, cross-functional collaboration (e.g., CRE-HR-IT-Finance) and change management capabilities.
• Phased investment based on cyclical constraints
  Prioritize foundational capabilities that remain valuable regardless of future scenarios, while keeping capital-intensive space transformations flexible and reversible until workforce strategies crystallize.
   

Action 2: Prepare for multiple workforce futures

Make trade-offs that address today's constraints without ruling out tomorrow's options - avoid rigid commitments that assume a single workforce future.

• Map transformation requirements for multiple workforce models and location strategies E.g., automation vs augmentation, distributed vs. hub-based.
• Design work environments which balance technology-enabled productivity with cognitive performance: Design for both digital enablement and human connectivity and performance through physical space quality and high-quality amenities rather than optimizing one at the expense of the other.
• Build adaptability through elastic portfolios (e.g. different lease terms, use of satellite hubs, modular space designs)
   

Action 3: Create sensing mechanisms and decision agility

Plan for sustained uncertainty and build organizational capacity to sense changes quickly and pivot when needed:
 

• Strengthen cross-functional collaboration
  Establish systematic connections between CRE, HR, IT, Finance, and operations through shared dashboards, regular alignment sessions and joint scenario planning to enable earlier change detection and faster collective decisions.
• Track leading indicators through ongoing measurement
  Monitor employee utilization patterns, AI adoption rates and workforce preference shifts. Create feedback loops from pilot programs and build organizational capacity to adjust when conditions change.
• Set clear decision rules and thresholds for resource allocation
  When do cost pressures justify delaying transformation? What ROI justifies investment under constraint? Which capabilities must remain internal versus partnered?

JLL's 2026 Future of Work Survey captures perspectives from over 2,200 C-suite executives and corporate real estate leaders across 21 countries between January and April 2026. Respondents represent organizations across 15 industries, with 50% employing fewer than 5,000 people globally, 27% employing 5,000-9,999, and 23% employing more than 10,000. The survey explores how organizations are navigating AI transformation, productivity imperatives, risk management and portfolio strategy in an era of converging technological, economic and geopolitical pressures.