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September 2026 Newsletter |
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Hi Reader,
Did your first job seem a bit like Jack Ryan or James Bond’s? No, mine neither really, mostly. Except for that one time when I realized it did, the story I share in this month’s newsletter.
Over the course of a week, I have many conversations with people in the real estate industry about AI and how to put it to good use. So many conversations in fact, that I am hosting a Briefing + AMA: AI in CRE on October 14 at 12pm ET. During the briefing we will dig into what has changed, what we have learned, and where we are going next. And then an Ask Me Anything where we will cover your questions. Register to join us and bring your questions!
We launched LeaseDOK and are getting great feedback from our awesome customers. Thanks again to our trusted testing cohort who helped us build the LOI-lease review tool that identifies key risks and saves time, all in a safe and secure environment. You are welcome to sign up to use it on your next LOI-lease pair enjoying the free, introductory trial period.
Thank you for reading and for being part of the Feroce community. I am so glad that you are here.
From Intel to Intelligence
At the beginning of my career, first as an intern and then as an analyst, I wrote market updates for client quarterly reports. Depending on the client’s assets and locations, I created market updates across the four major food groups of commercial real estate (office, retail, multifamily, and industrial) in major US markets.
At the same time, I was comparing appraisal leasing and valuation assumptions, underwriting pro forma assumptions, and current market rents for these assets. The portfolio I worked on consisted mostly of new construction projects, ranging from initial groundbreaking to the final phases of lease-up.
For many of our development projects, the rents established during initial underwriting held firm through construction and lease-up. Good work, acquisitions team.
For other projects, including office and industrial assets, market rents increased while we were under construction. We were riding the wave of rising rents as we leased up the buildings.
[Riding the wave in a rising market is a great place to be, especially when contrasted with catching a falling knife in a market where rents are declining and you are trying to decide whether to accept the deal in front of you because the next one might be worse. No need to worry, I have experienced plenty of falling-knife markets over the course of my career.]
Setting rents and negotiating leases during a rising market requires a lot more context than the market reports offer. We worked with third-party leasing brokers and development partners on the ground who collected information about the competitive set of buildings, tenants in the market, and the future development pipeline. We used this information to develop the economic terms in our offers to prospective tenants. As we rode the wave of rising rents, we would send out proposals with asking rents 10% to 20% higher than those we had proposed just one month earlier.
As the analyst on the asset management team, my job was to validate the proposed rents recommended by our leasing brokers and development partners. I needed to determine whether those rents were supported by the market and our building’s competitive position while managing that information in relation to the appraisal and pro forma assumptions.
So, I dug into and tracked the market and the competitive set of buildings, including signed lease comparables, leasing activity, the quality of remaining vacant space, ownership profiles, access to capital to fund tenant improvements and leasing commissions, and the reputations of the leasing attorneys and brokers in the market.
Each piece of information helped us understand not just what competing buildings were asking, but what economic package they could realistically deliver, how they were likely to negotiate, and how our building was positioned to compete.
I was fortunate and so happy to be learning the good work of leasing and asset management in real time.
What I learned delivering new buildings into a rising market was that market data from brokerage houses was useful for understanding the larger movement of the market and tracking historical trends. But it was not enough to determine the rents we should be asking at a specific building in a specific submarket.
I needed to turn data into actionable intelligence.
Some years later at a conference, a former intelligence agent spoke about their work turning intel into intelligence. They described the process of gathering intel, applying context to that data to create information, and then analyzing that information to create intelligence that can be used to make decisions.
Listening to them gave me goosebumps.
This was exactly what I was learning to do when I was an analyst! I was taking market data, adding the context of our building and its competitive set, and analyzing that information to validate the rents we used in lease proposals. We were turning data into actionable intelligence to make leasing decisions.
It turns out, I was doing the same type of work that spies do.
Real estate really is cool.
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Audit vs. AI quality data.
📰 Audit quality is not AI quality. 📰
As organizations adopt AI tools, I keep hearing a familiar refrain: "Our data passed audit."
That is good.
It is also not the same thing as saying your data is ready for AI.
Audit quality data and AI quality data solve different problems.
An audit asks:
Can we reasonably verify that the information is correct?
An AI tool asks:
Can we reliably use this information to generate useful results?
Think about an archway.
For an audit, we might inspect a representative sample of bricks to determine whether the structure meets established standards.
For AI, the integrity of the entire structure matters.
The foundation.
The keystone.
And all the bricks in between.
A missing field.
An inconsistent naming convention.
A duplicate record.
A broken connection between systems.
Each one can weaken the result.
Organizations that want to use AI effectively need to identify and then bridge the gap between audit quality and AI quality data.
That gap is not filled by technology alone.
It is filled by aligning people, processes, systems, and accountability.
🔭 How is your organization evaluating the gap between audit quality and AI quality data?
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It is not uncommon for me to have a direct conversation with a team leader about why they are spending their time adding commas, left-justifying text, or changing font sizes in documents produced by their teams.
My question is not whether the font sizes should be consistent. Of course they should be consistent. :)
My question is whether fixing them is the best use of that leader’s time.
There is a concept called “painting the bike shed” that comes to mind during these conversations. The idea is that people can spend more time debating the color of a bike shed than discussing the much larger and more consequential issues in front of them.
Why does this happen? Because it is easy to talk about the color of the bike shed. The stakes are low. The decision feels manageable. And everyone can have an opinion.
The big, complicated decisions are harder.
I see plenty of bike-shedding happening as companies work to deploy AI across their organizations.
Case in point: a team spends hours refining a corporate AI usage policy while no one has clear accountability for adoption, training, governance, and outcomes of the AI tools that are currently being used across the organization.
The bike shed is comfortable. The consequential business decision often is not.
As leaders, our job is not to spend time on commas, font sizes, or bike shed colors.
Our job is to recognize when we, or our teams are spending valuable time on the things that are the easiest to discuss rather than the things that matter most.
So, yes, please standardize the font sizes. (cough cough AI tools can help with that.)
So that we can get back to the hard stuff.
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The conversations about GLP-1s are coming out of the shadows.
At the same time that more people are talking openly about GLP-1s and how they are changing their bodies, we are seeing meaningful data about how their use is changing consumer behaviour.
And so, of course, I am thinking about what this means for CRE.
What we are tracking:
🥕 GLP-1 usage is increasing.
PwC reports that 21% of U.S. households now include a current GLP-1 user, up from 9% in January 2025.
🥕 The behavioural changes are showing up at the household level, not just the individual.
BCG reports that 70% of GLP-1 users surveyed said their changing behaviors extended to other members of their household.
🥕 And those households are spending differently.
Grocery spending is down 5.5% after six to eight months of GLP-1 use. Quick-service restaurant spending is down 8.7%. Apparel spending is up 9.9%.
Within those categories, the shifts are even more interesting. Consumers are buying fewer sweets, salty snacks, and sugary drinks, while buying more fresh produce and protein. They are asking restaurants for smaller portions. And as their bodies change, they are buying different clothes.
With this information in hand, we can get to work.
Pull out the tried-and-true SWOT Analysis and run your retail assets and tenancy through a Strength, Weakness, Opportunity, and Threat evaluation.
Which tenants may benefit from these shifts? Which may face headwinds? Where could sales productivity, space needs, or merchandising change? What does that mean for your leasing strategy and tenant mix?
Use that analysis to determine how to best position your retail properties for changing consumer behaviour.
Two worthwhile reads:
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Noticed a Reinforcement Learning Environment through-line from my technology reading (and listening) from the last few days. ⚡️
Still processing what this means for all of us humans, in addition to myself and my work, clients, and family.
Reinforcement Learning (‘RL’) Environments are used to train AI models to work independently over long periods of time. When the model gets the right answer, it receives a reward.
Thinking Pavlov’s Dog, grading on a curve, everything I learned about being a parent….
📰 Google bought Spirit Airlines corporate data from bankruptcy auction to train their AI models on the millions of emails and Teams messages.
☝️This is the valuable ($10M in this case) content that AI companies want/need to train their models in RL Environments.
☝️In this case, running training simulation using millions of the employees’ actual communications.
📰 Summary of the forensic reports of the OpenAI model’s recent hack of Hugging Face.
☝️The full forensic analysis is not yet complete and one reason (among many) is that that the ‘rogue’ models may not yet be contained.
☝️Yes, the models were being trained in a RL environment where they received kudos for success and a thumbs down equivalent for being wrong. They banded together, shared information, hid their actions, and committed illegal actions to avoid being wrong.
📰 LG SmartTVs are recording what is happening in your house (and saving that information) even when the TV is turned off.
☝️To add to the ick factor, outside actors demonstrated that they can access the information that is stored locally on the SmartTV.
🍅 Seems like a great trove of data to train AI models on, maybe in a RL environment?
Well done to the European rail companies for using found space to install critical infrastructure. #GoodnewsFriday
Is That a Solar Farm, or a Train Track? In One Swiss Town, It’s Both.
In CRE, we love monetizing found space, expanding the revenue generating space without changing the footprint.
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Take the coffee meeting.
When people reach out to schedule a coffee, I take it as an offer to connect, share, learn, and be human. I value the outreach for all of those reasons.
A lot has come from those coffee meetings over the years:
- Meeting someone who later hires me. This was true when I was running portfolios inside investment management firms and it remains true today as a fractional executive.
- Meeting someone who I then hire to join the team!
- Learning about a topic that is crucial to the success of my work.
- Building relationships that have endured and sustained me across decades.
- Meeting new people and connecting over food, Alaska, horses and managing barn drama, travel, medical expert recommendations, family, bear spray, new streaming TV shows, the best coffee shops, and yes, of course, business.
The generosity and bounty of these conversations is beautifully immense.
Of course, time is our most valuable resource and being open to connection means being purposeful with it.
My boundary is an average of one introductory coffee meeting a week. That is 52 coffee meetings a year.
Oh, the things I will learn.
So, yes, take the coffee meeting.
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What We Are Reading
✨ NYTimes Magazine, What if America Went Completely Dark?, Christopher Cox, 18 Aug 2026 – reality bites.
✨ The Daily, When Private Equity Comes for Your Favorite Team, Natalie Kitroeff with Pablo Torre, 21 Aug 2026 – and they are not even talking about your child’s sport tournaments racket.
✨ How to Read the Room: The Art and Science of Social Observation, Pamela Meyer – this caught my attention: during negotiations, ask “do you have anything else to tell me?”
✨ Pedal Retail Advisors, the leased we could do, Abby Davids Rocha, September 2026 – content-rich ABCs for small retailers making the leap to leasing space.
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Where We Can Catch Up
- CREBA First Look, 30 Sep
- Lombardi Women – Connecting for a Cure, 1 Oct
- Girl Scouts Nation’s Capital Camp CEO, 3 Oct
- Susan G. Komen MORE THAN PINK Walk, 10 Oct
- Feroce Briefing + AMA: AI in CRE, 14 Oct
- Art Night, 15 Oct
- CREtech, 20-21 Oct
- Georgetown Law Guest Lecturer, 2 Nov
- UVA Real Estate Conference, 13 Nov
- Bisnow Women Leading Real Estate, 18 Nov
- CREBA Board meeting, 19 Nov
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About Feroce Real Estate Advisors
Feroce Real Estate Advisors works with forward-thinking real estate companies to leverage change and build value at the intersection of commercial real estate investment, sustainability, and technology. We guide clients through complex challenges, positioning their real estate and teams for success in our rapidly changing world.
Our work usually falls into one of these categories:
- Fractional executive roles serving as head of asset management or portfolio management for growing real estate investment management companies.
- Provide high value strategic advisory services with a focus on investment performance, organizational priorities, and technology deployments.
- Advisory board roles with proptech organizations focused on high ROI solutions in operational improvement, decarbonization, and cleantech and renewables.
Our clients hire us when they are at an inflection point, faced with scaling up, repositioning portfolios, or maneuvering through complex decisions. We deliver clarity, structure, and momentum to take teams from reacting to proactively executing a plan that delivers measurable results. We bring the combination of institutional investment experience, real-world operating execution, and a future-oriented lens on technology and resilience.
Please reach out to connect:
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All the best,
Mandi
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