Centers Dynamic Partners has spent 28 years buying, repositioning, and managing neighborhood and community retail centers across the Western United States. It is a lean, principal-led firm, built on the experience of its founder, George Arce, Jr., and a small team. As the firm set out to chase more deals and build toward a fund, it hit a familiar wall: the underwriting behind each deal took too long.

Building a financial model and a financing package used to mean coordinating several outside vendors, each on its own schedule, with turnarounds that often ran one to two weeks per deal. For a small team, that pace capped how many opportunities the firm could pursue at once. Today, Centers Dynamic Partners underwrites its deals on Smart Capital Center, and the same work happens in days. This is what changed, and why it matters for any experienced firm trying to do more without hiring.

Why the Underwriting Was the Bottleneck

For a firm like Centers Dynamic Partners, finding good deals was rarely the problem. Getting them underwritten quickly was. Stabilized properties are fairly simple to model: you have income in place, a rent roll, and a cap rate, and that gets you most of the way. Value-add and redevelopment deals are harder, because the return does not exist yet. It has to be built over time, out of assumptions that all lean on each other.

Take the firm's core work, turning a vacant retail box into a modern retail or event space. That kind of deal has a lot of moving parts: the purchase, a construction budget spent down over months, an interest reserve that has to last until rent starts coming in, a lease-up period that decides when the property starts making money, and a sale at the end whose price depends on where the market sits by then.

Every one of those pieces depends on the others. If lease-up runs two months behind, the interest reserve has to cover a longer stretch before rent arrives, the construction draws shift, and the sale value changes too. One adjustment ripples through the whole model. That is what makes this work slow to do by hand and easy to get wrong, and it is also the part a sponsor most needs to get right, because a lender and an investor question these numbers first.

The takeaway: the deals with the most upside are the ones where the underwriting is hardest and slowest, which makes them the best candidates to speed up.

What the 2026 Retail Market Looks Like

The timing favors investors who can act quickly. According to JLL's U.S. Retail Market Dynamics (Q1 2026), retail vacancy held near 4.4% in early 2026, close to a multi-year low, with very little new retail being built. Good space is hard to find, so buying and improving an existing center is often the smarter play. Investors bought more than $15 billion of retail in the first quarter, the busiest start to a year since 2023 (JLL). With more buyers chasing a limited number of solid deals, the firm that can underwrite quickly and make a credible offer first has the edge.

CBRE's U.S. Real Estate Market Outlook 2026 tells the same story. It expects grocery-anchored, neighborhood, and strip centers to outperform on occupancy and rent growth, while older malls and weaker power centers lag because they need heavy, expensive work to bring back. Where big-box stores close, those empty boxes become prime targets for redevelopment.

This is the market Centers Dynamic Partners works in. Good retail is scarce, buyers are active, and repositioning an underused center is often the best way in. In that setting, the firm that can underwrite quickly and put a credible number on the table first is usually the one that wins the deal.

What Changes When Agentic AI Carries the Modeling

Agentic AI does multi-step work on its own instead of answering one question at a time. On Smart Capital Center, the firm shares its deal inputs, and the AI agents read the documents, pull in outside data on the property and market, and build the first full draft of the deal: the pro forma, a discounted cash flow with tenant-by-tenant projections, the construction draw and interest-reserve schedules, the debt structure, and the investor memo. From there, the team takes over, running its own versions and testing its own assumptions in the same workspace.

For a lean firm like Centers Dynamic Partners, that changes four things that matter:

More deals in front of investors at once.  When the first draft of a model takes a fraction of the time, a small team can work several deals in parallel instead of one at a time. The firm's capacity is no longer capped by how many people it employs.

A credible number, ready in time to compete.  In a market where good retail moves fast, being first with a solid, well-supported underwriting is often what earns a firm a serious look. Doing the same analysis in days instead of weeks is a real advantage.

One workspace instead of three vendors.  The back-and-forth across separate outside providers goes away. Every output stays editable, traceable to its source, and exportable, so the firm keeps one clean, current version of the deal from the first input to the final memo.

The founder's judgment on every deal.  The experience that tells George Arce which assumptions are too aggressive and which are too cautious is the firm's real edge. When the AI handles the mechanical modeling, that judgment reaches every deal the firm looks at, instead of being rationed across a few.

Does AI Replace the Analyst?

It is the first question most experienced investors ask, and it deserves a straight answer. On Smart Capital Center, the AI does the heavy modeling and the people make the decisions. Every number stays editable, and the sponsor keeps full control of the assumptions.

The research backs up that split. In a study from the University of Chicago Booth School of Business, researchers Alex Kim, Maximilian Muhn, and Valeri Nikolaev found that GPT-4, when asked to reason step by step, predicted the direction of a company's future earnings with about 60% accuracy, several points better than professional analysts in the low 50s. The AI did best in exactly the situations where human analysts tend to struggle.

Independent research points the same way. A study from the MIT Sloan School of Management concluded that AI is more likely to work alongside people than to replace them, and it names judgment as one of the capabilities machines still struggle to replicate. As co-author Roberto Rigobon, the Society of Sloan Fellows Professor of Management at MIT Sloan, framed it, the better question is “what technology can give us rather than what it might take away.” (MIT Sloan, March 2025.)

The lesson is to pair the two, not swap one for the other. The AI handles the heavy, data-driven first pass, which frees experienced people for the work that actually decides a deal: judgment, strategy, and the investor relationship. For a sponsor whose reputation rests on knowing the numbers cold, that keeps the relationship, and the final call, firmly in the firm's hands.

What Centers Dynamic Partners Is Building

On Smart Capital Center, Centers Dynamic Partners shares its vision and deal inputs, the AI agents build the first draft, and the team runs its own versions in the workspace. Because much of the firm's work involves repositioning vacant retail boxes, the platform models the full lifecycle, from purchase through stabilization and sale, so the firm can test scenarios and run sensitivities before it commits capital.

The payoff shows up in both speed and credibility.

“It's a lot easier now to have a team that helps me underwrite a deal in a week instead of a month. The end product is so detailed that the finance brokers were impressed. Sponsors usually don't hand over that kind of underwriting. The software and the scrubbing capability with the AI has been enormous. As a sponsor, you must know your numbers cold, and Smart Capital Center lets me do that.”

George Arce, Jr., President and CEO, Centers Dynamic Partners

For a lean firm building toward a fund, that is the whole point. Underwriting becomes a repeatable capability the team runs every deal through, and deal-by-deal modeling turns into a standing part of how the firm works.

How to Tell Whether AI Underwriting Fits Your Firm

If you run a lean shop and you are weighing this, four questions cut straight to whether it will pay off:

1. Where is your bottleneck?  If you pass on deals because you cannot model them fast enough, the constraint is capacity, and that is what automation addresses directly. If your issue is sourcing, this solves a different problem.

2. How complex is your typical deal?  The more your returns depend on construction cost, lease-up timing, and exit assumptions, the more you gain, because that connected modeling is the slowest and most error-prone to do by hand.

3. Do you keep control of the assumptions?  Good AI underwriting leaves every output editable and traceable, so your team owns the final number. Be wary of any tool that hands you a black box.

4. Does it hold up in front of a lender or investor?  The test of an underwriting is whether the people reviewing it trust it. Output detailed and clean enough to impress a finance broker is the bar worth setting.

Smart Capital Center sits at the execution layer of that workflow. It combines the everyday flexibility of Excel, built in, with institutional-grade modeling, and draws on data covering more than 120 million properties, over 1 billion real-time market signals, and more than $500 billion in analyzed transactions, so a lean team's assumptions get checked against real market data as they build. See how the platform is built for investors.

How to Get the Most Out of AI Underwriting

The firms that see the biggest gains treat AI underwriting as a way to amplify their expertise. A few habits separate them:

• Bring your best inputs. The model is only as sharp as the deal data behind it, so firms that feed clean, complete inputs get a first draft they can trust and build on right away.

• Pair the speed with your market read. Smart Capital Center surfaces comps and flags where an assumption looks aggressive, and a sponsor's feel for why a submarket behaves the way it does turns those signals into a sharper number.

• Stay selective as you scale. The ability to underwrite more deals faster is most valuable when it is pointed at the right ones, and the firms that win use the extra capacity to look harder, not just to look at more.

Used this way, agentic AI raises the ceiling on what a lean team can take on, with the firm's judgment guiding every deal.

The Bottom Line

The size of a lean CRE firm used to decide how many deals it could seriously chase, because the underwriting behind each one took weeks and often several outside vendors. Agentic AI changes that. It lets an experienced, principal-led team underwrite value-add and redevelopment deals in days, put more of them in front of investors, and build toward a fund without adding the analyst headcount that used to be the cost of growth.

Centers Dynamic Partners shows what that looks like in practice, with 28 years of judgment now reaching more deals instead of being stretched across a few. See more client stories to compare notes with firms like yours.

“Centers Dynamic Partners has decades of judgment about what makes a retail deal work. Our AI gives that judgment more power, so a nimble team can review deals with the rigor and speed of institutional juggernauts. That is what lets experienced investors scale and drive higher returns for their LPs.”

Laura Krashakova, CEO, Smart Capital Center

Dream Bigger. Invest Smarter.

Underwrite value-add and redevelopment deals in days, not weeks. See how Smart Capital Center’s AI gives your team institutional underwriting reach without institutional headcount.  

Book a demo today.  

Frequently Asked Questions

How is AI used for underwriting in commercial real estate?

AI reads the documents behind a deal, pulls in outside data on the property and market, and drafts the underwriting assumptions from patterns across many comparable deals. Smart Capital Center then checks those assumptions against its own data on submarket performance and on rent, occupancy, and expense comps, builds the financial model and projections, and drafts the materials a sponsor shares with investors, while the sponsor keeps control of every number.

What is agentic AI in commercial real estate?

Agentic AI completes multi-step work on its own instead of answering one prompt at a time. Smart Capital Center's AI agents take raw deal inputs, extract and standardize the data, gather more property and market information, and turn it into interactive financial analyses and deal narratives, with experienced professionals reviewing the output and making the final call.

Can AI underwrite value-add and redevelopment deals?

Yes. Smart Capital Center models the full redevelopment lifecycle, from construction draws and interest reserves through lease-up timing and exit assumptions. That makes it well suited to value-add and repositioning strategies, where returns depend on cost and timing more than on in-place income.

Will AI replace underwriters and analysts in commercial real estate?

No. AI handles the heavy modeling so experienced professionals can focus on judgment, strategy, and investor relationships. Research from the University of Chicago Booth School of Business found AI can match or beat human analysts at predicting earnings direction, and the strongest results come from pairing that speed with human oversight. On Smart Capital Center, every model stays editable and the sponsor keeps full control.

How does a lean investment firm scale deal flow without hiring analysts?

By turning underwriting into a repeatable, automated capability. When the first draft of each model is produced in a fraction of the usual time, a small team can pursue more deals at once and build toward a fund, without carrying the fixed cost of a full analyst bench. Centers Dynamic Partners is doing this today with Smart Capital Center.

How does Smart Capital Center help with value-add underwriting?

Smart Capital Center gives lean, principal-led firms institutional-grade underwriting on demand. Its AI agents build the pro forma, discounted cash flow, draw and interest-reserve schedules, debt structure, and investor memo from a firm's own inputs, checked against data on more than 120 million properties, so the team moves faster while keeping full control of the assumptions.

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