This post is authored by Ross Leibowitz, a seasoned expert with over 25 years of experience in real estate and workplace solutions. As a founder of Centerstone Software and former CTO of Manhattan Software, Ross has spent his career building and innovating workplace products. As Tango’s Senior Director of Workplace Products, he continues to drive product strategy and shares his unique perspective on how AI is reshaping the modern workplace.
In my first two posts, we explored the early stages of AI adoption: acknowledging disruption and then helping teams build confidence through safe, comfortable experimentation. That comfort phase is essential – the moment people stop feeling intimidated by AI, they get curious, they start trying small tasks, they begin seeing opportunities, and organizations start to see the impact. And if you look at how quickly consumer AI has evolved – think about how outdated our old Alexas suddenly feel now that generative AI assistants exist – you can see why expectations in the workplace are shifting just as fast.
As I’ve experienced when presenting this topic at IFMA World Workplace and CoreNet Global Summit these past few weeks, I can anticipate the next question everyone’s thinking:
“Okay, Ross… so what can AI actually do for workplace strategy right now?”
Not in ten years. Not in some hypothetical future. But today, with the data most organizations have available to them.
The good news is that AI has moved well beyond simple chatbots and automation toward being a strategic accelerator for workplace and real estate teams. And while we’re still early, the use cases that are emerging are real, practical, and already making an impact.
In this next step of our AI in the workplace blog series, I’ll walk through five of the most meaningful applications I see right now – shaped by what we’re building at Tango, what I shared in my recent webinar, and what I’ve observed across the industry (including examples I saw discussed at CoreNet by OpenAI’s workplace team).
1. Automating the Manual Work That Consumes Workplace Teams
Every workplace or real estate leader I talk to has the same reality: their teams are overwhelmed by repetitive, administrative work. Lease data abstraction. Invoice processing. Space planning exercises that start from scratch every time and feel reactive, not proactive. While these tasks are essential, they pull people away from the strategic work their time is better spent on.
AI is already easing that manual burden in meaningful ways.
Take lease abstraction. Traditionally, it means searching through page after page of dense PDFs to locate key terms, dates, clauses, and obligations. Earlier generations of OCR tools tried to speed up the process, but they never reached the level of accuracy teams actually needed. With generative AI, that gap has closed. Today, AI can process a lease end-to-end in seconds and produce a structured first draft for review with accuracy rates north of 90%. The human role shifts from “doing all the work” to “validating the work”, which is faster, less at risk of human error, and thus, more accurate and far less painful.
The same is happening with invoice processing. Legacy OCR solutions struggled with inconsistent document formats, multi-page invoices, and the kind of unique cases that facilities and real estate teams deal with every day. AI is able to handle these variations far more effectively. Whether it’s utility bills, maintenance invoices, or project documents, AI can extract the relevant data, classify it, and route it appropriately. Teams regain hours each week, and data consistency improves dramatically.
Even blocking and stacking – a task that historically required space planners to use multiple spreadsheets, acquire stakeholder inputs, and spend hours of trial-and-error trying to keep up with ever-growing requirements – can now begin with an AI-generated first pass. Instead of reinventing the wheel each time, workplace teams start from a viable plan and spend their energy refining the details.
These kinds of workflows are where AI tends to provide the fastest return. They aren’t flashy, but they add up to meaningful time savings, better data quality, and far fewer headaches.
2. Turning Fragmented Workplace Data into Forward-Looking Insight
For years, workplace decisions were made almost entirely on retrospective data: yesterday’s badge swipes, last month’s reservation trends, quarterly utilization averages. That may have been somewhat helpful, but it is lagged and limiting.
AI is finally changing that. For many organizations, especially those with large or complex portfolios, it’s easy to focus on individual locations or business units and lose sight of opportunities that exist across the entire portfolio. With models combining multiple data sources – badge, Wi-Fi, sensors, visitor logs, even HR and team-level context – they can surface insights humans would struggle to find on their own. They can detect trends across locations, identify patterns that weren’t obvious, and forecast what future utilization might look like across days, teams, or space types.
This shift toward predictive intelligence is one of the most important developments I’ve seen in workplace technology. Leaders can now ask questions like:
- “How many workstations will this team need three months from now?”
- “Which days are likely to be highest demand based on historical patterns?”
- “Where do we expect congestion as hiring increases?”
And AI can generate a data-driven answer – not a guess, not an average, but an insight built on patterns within the data.
At CoreNet, OpenAI’s workplace team shared how they use AI to analyze peer hybrid work policy trends and model workplace patterns across tech companies using verifiable public sources. Hearing that reinforced something I’m seeing across the entire industry: workplace data is finally being used for forecasting, not just reporting. Now we can unlock smart and dynamic planning powered by data-backed predictions.
3. The Rise of AI Agents for Real Estate and Space Optimization
If automation helps with tasks and predictive analytics helps with insight, AI agents represent the next major evolution: systems that can pose solutions, plan, and take multi-step actions toward a goal.
Agents should be thought of as digital teammates. They don’t just answer questions – they evaluate information, retrieve data, decide what to do next, and then are able to execute that next step.
For real estate and workplace strategy, this opens a ton of possibilities. Imagine an agent that reviews your portfolio every week, looks at utilization patterns, headcount forecasts, reservations, seasonal shifts, and lease timelines – and then generates recommendations on where to consolidate, which floors could be downsized, what seating ratios are no longer aligned with actual behavior, or where you may need additional space to support growth. In other words, AI can help ensure the business has the right amount of real estate at the right time.
Or consider an agent that performs ongoing desk audits, identifying unused or abandoned spaces and returning them to circulation. At CoreNet, OpenAI’s workplace team described experimenting with exactly this type of automation – not as a futuristic ambition, but as early proof that agents are already reshaping how facilities teams operate.
Agents are still emerging, but it’s clear we’re moving toward a world where continuous optimization happens in the background, with humans deciding when and how to act on those recommendations. For large, complex portfolios, that’s a transformational shift.
4. Personalizing the Workplace Experience in a Way Employees Actually Feel
One of the biggest frustrations employees have with workplaces is friction. When they enter the workplace, they’re asking themselves or others, “where do I sit today?”, “which room is available for this meeting?”, “how do I submit an IT or maintenance request?”, or “what’s the policy for visitors?”
AI helps remove that friction and makes the workplace seamless for employees. Modern workplace chatbots can answer routine questions, make bookings, provide wayfinding guidance, surface policies, and recommend the best spaces for specific tasks.
The value here isn’t just convenience, it’s confidence. When employees can easily find what they need, the workplace feels more intentional, more supportive, and easier to navigate.
The industry is moving this way quickly. At CoreNet, OpenAI shared how they built an internal “Workplace Office Bot” to help their employees navigate buildings, policies, and services. That example stood out not because it seemed highly helpful, but because it was relatable. Many organizations want to offer this level of experience – AI finally makes it achievable. We’re seeing the same in our own product development. Early results from “Ask Tango”, our new reservation chatbot, show meaningful reductions in the number of clicks required to complete complex reservations compared to traditional workflows. It’s a small but powerful signal of where the workplace experience is headed – and something I’ll share more about in the next blog.
5. Accelerating Scenario Planning and Strategic Workplace Decisions
If there is one area where AI will fundamentally and monumentally reshape workplace strategy, it’s scenario planning. Space planners, CRE leaders, and workplace teams are constantly asked to run rapid-fire evaluations pertaining to hyper-specific questions:
- What happens if we grow headcount?
- What if we shift to three days in office?
- What if we close a floor or open a new location?
- What if we reorganize teams and organizational structure?
These scenarios typically require slow, manual analysis and back-and-forth with multiple stakeholders. Over the past year, we’ve all seen what happens when organizations make major workplace or return-to-office decisions without a deeper understanding of their workforce and without a strategy in place to support it.
AI changes the pace entirely by synthesizing utilization data, portfolio information, lease constraints, hiring plans, and team behaviors. With all this data, models can produce multiple scenarios in minutes – each with documented assumptions and a clear rationale. Leaders can compare options, stress-test ideas, and make more confident decisions with far better visibility.
This isn’t AI replacing strategic thinking. It’s AI enabling deeper strategic thinking by removing the heavy lift. In other words, AI doesn’t eliminate the planner. It elevates the planner.
Why These Use Cases Work Today
None of this requires an AI lab or cutting-edge infrastructure. These use cases work because:
- modern models can summarize, classify, forecast, and reason with remarkable accuracy,
- workplace data is increasingly structured and available,
- and teams who are comfortable experimenting can now take advantage of the tools in practical, low-risk ways.
The organizations that move fastest in this next phase won’t be the ones with the largest budgets – they’ll be the ones with the most curiosity and the least fear.
And if your teams followed the comfort-building approach from the last blog, they’re already equipped to take this next step of turning experiments into impact.
Want to dig deeper?
I recently walked through several of these scenarios in a live webinar. You can watch the full session, “How AI Is Shaping the Future Workplace”, here: https://event.on24.com/wcc/r/5028374/75A0F499CF1D7AD3024102EB792AD6E4
