How AI is reshaping portfolio time horizons

AI adoption is already changing how organizations use and manage their real estate, but we’re just at the beginning of a journey that’s rapidly shifting how people work and businesses operate. Consider lease renewals: Most are still evaluated against seven-to-ten-year business assumptions. As AI compresses planning horizons to 12–24 months, CRE teams have an opportunity to evolve their planning processes to reflect a more dynamic operating environment.

Our latest Future of Work research surveyed 2,200 C-suite executives and CRE leaders across 21 countries. The findings reveal that 78% of business and corporate real estate (CRE) leaders believe AI will significantly impact their portfolio strategies and the overall CRE function over the next three to five years. However, only 15% are actively transforming their operations today. 

AI ambition is moving faster than AI execution. If you're managing space, headcount or facilities decisions right now, that gap is where the risk sits. Not in some future AI rollout, but in the leases and space commitments you're signing this year based on assumptions that may not hold next year.

The stakes are clear when you look at portfolio risk factors. Three of the top four risks to CRE portfolios are now tech-related: cyber security and data privacy (47%), technology and AI disruption (41%), and uncertainty of AI impacts upon space requirements (40%).

"Real estate decisions are long-term commitments, but businesses no longer have the luxury of thinking seven years in advance. The decision-making model needs to evolve,” says Ram Srinivasan, Managing Director, AI Adoption, AI Integration & Future of Work Advisory at JLL.

CRE leaders who take a wait-and-see approach or focus on small AI experiments will soon find themselves left behind. To guide their organizations through this period of rapid transformation, they must simultaneously navigate how widespread AI adoption is changing what the business needs from real estate, while figuring out how to harness the power of AI to manage an increasingly complex portfolio, according to our latest report on how AI is impacting jobs and real estate.

Here's what our Future of Work research says you need to know before your next portfolio decision.

Your headcount and space assumptions need to change

Most companies are still planning space around multi-year headcount forecasts. But our research shows that innovation-intensive sectors are shifting their planning to 12–24 months out. That acceleration is an issue when you're locked into a 10-year lease. 

Contrary to workforce reduction fears, most organizations surveyed anticipate net new headcount growth, expecting AI to shift employees toward higher-value work rather than simply to reduce their workforce

The fix isn't abandoning long-term commitments. Instead, it’s time to build more "liquid" capacity into your portfolio: space that can expand, contract or convert faster than your old planning cycle assumed.

AI is already cutting portfolio analysis time from weeks to minutes.

“We ran a client's full portfolio analytics two ways: the traditional manual process took four weeks. The AI-assisted version took minutes,” says Daniel Rooney, Managing Director, JLL Consulting. 

At first glance, this feels like an efficiency play, but the real benefits go deeper. Our teams partnered with the client to sit down with stakeholders and learn more about what their people needed from the portfolio transformation.

The skills gap is now your biggest barrier.

For the first time in 15 years of Future of Work surveys, talent shortage outranked budget constraints as the top obstacle to CRE value creation.

Many CRE teams lack the critical skills, capabilities, and change management required to execute at scale. Companies are struggling to secure the essential talent and expertise in AI, analytics, emerging technologies, change management and strategic performance measurement.

If your team doesn't yet have someone who can turn AI output into portfolio strategy, that's the conversation worth having before your next planning cycle.

The organizations successfully navigating AI adoption share four characteristics:

• A commitment to growing their workforce
• Embedded organizational resilience
• Long-term strategic vision
• HR, IT and real estate collaboration

The data shows that success increasingly comes from aligning cross-functional teams around a shared understanding of how AI will reshape their space needs and developing the organizational capacity to respond accordingly.

A five-minute portfolio check

Pull your five largest active leases. Next to each one, write down the planning horizon your business operates on right now. Not the horizon your real estate team assumed when the lease was signed, but the one your strategy team is using today.

If the sector benchmark holds, that's likely 12–24 months for a fast-moving business, three to five years otherwise. Any lease extending beyond that horizon becomes a liquidity constraint. It ties up capital in space that no longer reflects your business’s planning assumptions.

One more thing worth checking

Life sciences is the clearest example of how fast the "what we need" question can flip. AI has fundamentally changed the economics of drug discovery by shifting more work into in silico environments. That meant strategic rebalancing of the footprint of traditional bench‑heavy wet labs, dry labs and high‑performance computational infrastructure. Real estate strategies now balance different types of lab space with on‑site computing, power and cooling capacity to support AI‑driven workflows.

Whatever your sector, ask your team whether a similar shift is already underway, and whether anyone's tracking it. 

Does AI actually save time on portfolio management, or is that overstated?

In a real client engagement, the same portfolio analysis took minutes with AI versus four weeks manually.

What's the biggest obstacle to getting value from AI in CRE right now?

Talent, not budget. This is the first time that's been true in 15 years of this research.

Who should own this on our team?

Whoever can turn AI output into a portfolio decision, not just a report. That's the skill gap most CRE teams haven't closed yet.

If the test above turned up a gap, the next step is figuring out which of your leases can flex and which can't, and what that's worth doing something about now versus at renewal. That's a portfolio strategy conversation, not a real estate transaction one. 

See what a full portfolio liquidity review would find. JLL Consulting can analyze your entire portfolio and show you exactly where the gaps are, and what your options are for each one.

[Get a portfolio liquidity review →]