— By Sandeep Ahuja —
Turning vacant big box stores into assets with AI.
Redeveloping these stores has always been costly and slow. AI is starting to change that by giving owners and developers faster ways to rethink these large spaces and plan for their next chapter.
Big box vacancies can quickly erode the value of an entire shopping center. With AI, owners no longer have to rely on guesswork about what comes next. In one Florida redevelopment, analysis showed how an empty 82,000-square-foot anchor could be repositioned to generate nearly $770,000 in new NOI, adding $12 million in value and producing a first-year yield well above industry benchmarks.
The Problem: Why Big Box Spaces Are Hard to Repurpose
Big box stores like Target, Walmart or The Home Depot were designed for one thing: rows and rows of merchandise under a single roof. Their size and single-purpose layouts make them hard and costly to convert into anything else. Wide floors, endless concrete and fluorescent lighting do not easily translate to housing, offices or healthcare.
The size is only part of the problem. The infrastructure adds more roadblocks. Loading docks are built for trucks, not people. Parking lots are laid out for quick in-and-out shopping, not the steady flow of a clinic or the overnight needs of apartments. Oversized mechanical systems are tuned for retail, not classrooms, gyms or housing.
The result is a property that is hard to lease and costly to reimagine, leaving owners and developers with a stubborn challenge.
AI for Existing Big Box Buildings: Faster Analysis, Smarter Scenarios
As more big box stores sit vacant, owners and developers are under pressure to find ways to make them productive again. The issue is not a lack of ideas but knowing which ones will actually pencil out. AI helps by speeding up the analysis, testing more options at once and pointing to strategies that make sense both practically and financially.
Traditionally, feasibility studies are slow and manual, often stretching over months. A team might test a few reuse ideas, but each requires combing through layouts, parking, utilities and code requirements. With AI, those same studies can run in parallel, cutting weeks or months of work down to just a few days.
AI goes beyond basic square footage. It can account for zoning, ceiling heights, structural limits and site access, then weigh those against demographics, rental rates and demand. The result is a clearer view of which ideas are not only possible but likely to succeed.
The payoff is clarity. Instead of betting on guesswork, owners and developers can see which options will drive returns with the least risk. That makes it easier to move ahead quickly and with confidence.
Case Study | Big-Box Store, Florida
When an 82,000-square-foot big box store shut down in Florida, it left a gaping hole in the middle of an otherwise busy shopping center. Vacancies that large can drag down overall foot traffic, put pressure on nearby tenants and make new leasing much harder.
Looking for a way forward, the owner turned to AI modeling to test reuse ideas. In just a few weeks the team compared dozens of options, pulling in real market data and flagging issues like ceiling heights or site access. That same process done the traditional way would have taken months.
The analysis pointed to a clear solution: rework the front 23,000 square feet for a junior anchor tenant and convert the remaining 59,000 square feet ready for storage, recreation or fitness.
The payoff was clear. The mix generated close to $770,000 in new NOI and added about $12 million in value from a $4 million investment. That worked out to a 19.25% first-year yield, well above industry norms.
By speeding up the process and testing more scenarios, AI helped the team move from an empty box to a solid plan more quickly and with greater confidence, while keeping flexibility for future changes in demand.
AI for Future Big Box Designs: Designing with Adaptability in Mind from Day 1
AI is not only useful once a store sits empty. It can also shape new construction so big box buildings are easier to reuse in the future. By testing scenarios before the first tenant signs a lease, developers can design shells with flexibility built in and ready for a second or even third life.
Picture a 60,000-square-foot store working as retail today, shifting to self-storage tomorrow and becoming medical offices 10 years from now. AI can point out the structural capacity, HVAC needs and wall layouts that would make each change possible with only minor adjustments. The idea is to build in flexibility from the start so you are not stuck paying for major retrofits later.
If this Florida big box had been designed that way, contingency plans could have been in place before it ever opened. Features like flexible entrances and modular utility systems would have made the eventual conversion much simpler and much less expensive.
Best Practices Checklist
As AI reshapes how these properties are planned and redeveloped, a few practical strategies are starting to stand out. They apply whether you are bringing an older building back to life or designing a new one with its next chapter in mind.
For Existing Big Box Properties
• Use AI to test multiple reuse options side by side instead of studying them one at a time.
• Look for tenants that strengthen the overall retail mix rather than compete with it.
• When renovating, add flexible entrances and separate utility systems so the next conversion is less costly.
• Balance traffic-driving tenants, like gyms or retail, with steady-income tenants such as storage or healthcare.
For Future Big Box Developments
• Run AI simulations during design to explore second-life scenarios before construction begins.
• Plan layouts with open floor plates, higher ceilings and modular systems that can adjust as needs change.
• Design walls, utilities and facades so they can be reworked later without heavy costs.
• Build adaptability into the financial plan from the start instead of treating it as an afterthought.
The Business Case: ROI, Resilience, Sustainability Benefits
Redeveloping a big box store is not just about filling a vacancy. With AI, it becomes a financial strategy. Owners and developers can quickly see which reuse options deliver the best returns while cutting both risk and time to market.
The Florida project shows the impact. A mix of retail and storage created nearly $12 million in added value from a $4 million investment, with a first-year yield far above industry norms. It is a clear example of how careful analysis can turn an empty store into a profitable asset.
AI also lowers the risk of long vacancies by modeling how a property might perform with different tenant mixes. Rather than depend on one large tenant, owners can plan for a range of futures and build more stability into their portfolios.
There is also a sustainability benefit. Reusing existing structures avoids the carbon and waste tied to demolition and new construction. In many markets, that environmental upside strengthens community support and aligns with the expectations of regulators and investors.
Adaptive Reuse as a Proactive, Tech-Enabled Strategy
Big box stores do not have to sit empty when demand shifts. With the right tools, they can be turned into assets that keep producing income, whether that means retail, recreation, storage, healthcare or something else. The Florida example proves the point. When decisions are grounded in real data, reuse moves faster, costs less and generates stronger returns.
The bigger opportunity is to design for flexibility from the very beginning. Buildings planned for multiple futures keep their value longer, are cheaper to convert and continue generating income as markets shift.
Retail demand will always change faster than the buildings themselves. That is why planning with technology is no longer optional. It is how developers protect investments, reduce risk and build assets that continue to perform over time.
— Sandeep Ahuja is a technologist, entrepreneur, author, architect and building scientist, as well as the co-founder and CEO of cove, an innovative, AI-powered architecture practice dedicated to streamlining the entire design and construction process. cove leverages AI to achieve efficiency, collaboration and transparency, fundamentally reshaping the built environment.