What is an AI stacking plan for office leasing? An AI stacking plan is a floor-by-floor visual of a multi-tenant building, generated or maintained with artificial intelligence, that shows which tenant occupies which suite, how much square footage each holds, and when every lease expires, so an owner can see rollover risk and contiguous vacancy at a glance. AI stacking plan office leasing analysis takes the same rent roll data you already have and renders it as a picture of the building's future, turning a dense spreadsheet into a map of where income is concentrated and where it is about to roll. For the full toolkit behind this workflow, see our guide to AI tools for real estate investors.
Key Takeaways
- A stacking plan is a floor-by-floor diagram of a building's tenancy, and its power is showing lease rollover concentration and contiguous vacancy that a flat rent roll hides.
- AI builds a stacking plan from rent roll and lease data, then color-codes floors by expiration year so a dangerous cluster of leases rolling in the same window is obvious.
- Contiguity matters in office leasing because large tenants need blocks of adjacent space, so AI can flag where expiring suites could be combined into a marketable full-floor or multi-floor block.
- The office market in 2026 is sharply split between prime and commodity space, so knowing your rollover timing helps you position for renewals, capital, and repositioning.
- AI reads the underlying leases for the terms that drive the stack, including expirations, renewal options, expansion rights, and rights of first refusal.
- A stacking plan is a decision tool, not a legal record, so verify the AI output against executed leases and estoppels before you act on it.
What a Stacking Plan Shows That a Rent Roll Does Not
A stacking plan shows the geometry of your income, while a rent roll only lists it. Both hold the same facts, but the stacking plan places each tenant in physical space, floor by floor and suite by suite, so patterns that hide in spreadsheet rows jump out. The most important pattern is rollover concentration: three leases expiring in the same year look like three ordinary rows in a rent roll, but on a stack they may light up an entire wing of the building rolling at once.
This is why the stacking plan is the office investor's native view. It answers questions a rent roll cannot: if these two suites expire together, do they combine into a full floor a larger tenant would want? Is my prime high-floor space locked up for a decade while my rollover risk sits in hard-to-lease low floors? AI is what makes the view current, because it can rebuild the stack automatically whenever a lease is signed or amended. If your source data arrives as a messy scan, our guide to AI tools to extract data from scanned rent roll PDFs covers getting clean inputs first.
How AI Builds the Stack From Your Rent Roll
AI builds a stacking plan by parsing your rent roll and lease abstracts into structured fields, then arranging them by floor and suite. The workflow starts with clean data: tenant name, suite, floor, rentable square feet, lease start, lease expiration, and base rent. A frontier assistant such as Claude or ChatGPT can take a rent roll and return a normalized table, group it by floor, and even output a simple text or table-based stack you can drop into a report.
The same approach that powers AI apartment rent roll analysis applies here, though office adds complexity that multifamily does not: partial-floor suites, load factors, and expansion or contraction options that change the picture over time. The practical output is a color-coded stack, usually keyed by expiration year, with vacant suites highlighted. That single artifact drives leasing strategy, capital planning, and the rollover conversation with a lender or a buyer. CRE teams that want a standardized stacking-plan template built around their own rent rolls can get hands-on help from The AI Consulting Network.
Reading Rollover Risk From the Stack
Rollover risk is the danger that too much of your income expires in too short a window, and the stacking plan is where you see it clearly. When you shade the stack by expiration year, a healthy building shows leases staggered across many years, while a risky one shows a wall of the same color rolling together. AI can quantify what the picture implies, calculating the share of rentable area and base rent expiring in each of the next several years.
This connects directly to deeper portfolio work; our guide to AI lease rollover risk analysis covers predicting renewals and modeling the NOI impact of different outcomes. The stacking plan is the front end of that analysis for a single asset. In the 2026 office market, where CBRE reports overall vacancy near 18.6 percent and a widening gap between prime and commodity buildings, knowing exactly when your space rolls is the difference between planning a repositioning and being surprised by one. For market context, see the CBRE U.S. office outlook and JLL office market data.
Data Quality and Tool Choice
The stacking plan is only as good as the data behind it, so the first discipline is clean, verified inputs. Office rent rolls are notorious for mixing rentable and usable square feet, applying different load factors across floors, and burying expansion or termination options in the lease rather than the summary. AI can normalize these fields, but you must confirm that the square footage totals on the stack reconcile to the building's rentable area and that no suite is double counted.
On tools, a general frontier assistant such as Claude, ChatGPT, or Gemini is enough to parse a rent roll and produce a text or table stack for a single asset or a quick screen. Dedicated commercial platforms such as VTS, CoStar, and Argus maintain live stacking plans and lease data at portfolio scale, and the pragmatic approach is to use AI to check and enrich that platform data rather than replace it. Whichever path you choose, a human should spot check the AI output against a handful of executed leases before any leasing or capital decision rests on it.
From Picture to Plan: Using the Stack to Act
A stacking plan earns its keep when it changes what you do next, and AI shortens the distance from picture to plan. Once the stack reveals a rollover cluster, the questions become tactical: which expiring tenants should you approach early for a renewal or blend-and-extend, which suites should you hold vacant to assemble a contiguous block, and where should tenant improvement dollars go to win the leases that matter most.
AI supports each of these moves. It can draft renewal outreach timed to lease expirations, model the cost of carrying a suite vacant to create a full-floor block against the higher rent that block might command, and rank tenants by renewal probability so leasing effort goes where it counts. CRE owners who want a repeatable version of this workflow can reach out to Avi Hacker, J.D. at The AI Consulting Network for hands-on implementation support.
Frequently Asked Questions
Q: What is a stacking plan in commercial real estate?
A: A stacking plan is a visual, floor-by-floor diagram of a multi-tenant building that shows which tenant occupies each suite, the square footage, and the lease expiration. It is most common in office assets and is used to see rollover timing, vacancy, and opportunities to assemble contiguous space.
Q: How is a stacking plan different from a rent roll?
A: A rent roll is a list of tenants and lease terms, while a stacking plan places those same tenants in physical space by floor and suite. The stacking plan makes rollover concentration and contiguous vacancy visible in a way the list cannot.
Q: Can AI create a stacking plan automatically?
A: AI can generate a stacking plan from a clean rent roll and lease abstracts, arranging tenants by floor and color-coding by expiration year. You still need to verify the output against executed leases, because a stacking plan is a decision tool, not a legal record.
Q: Why does contiguity matter in office leasing?
A: Larger office tenants usually need blocks of adjacent space on the same or stacked floors. When AI flags expiring suites that could be combined into a contiguous block, an owner can plan to capture demand that scattered small vacancies would miss.