Before you make your next decision, ask AI this
Net Effective
Title: Before you make your next decision, ask AI this
"What is it we should be looking at? What is it we should know? What is it we need to do given what's in front of us?"
That's Robert Salwasser on the question AI is forcing real estate owners and operators to ask.
Robert is the founder and president of Income Property Specialists (IPS), where he has spent nearly four decades helping individual investors and family offices manage and grow their real estate portfolios. He co-founded IPS in the mid-1980s after studying economics and law, initially representing Bay Area landlords in property tax appeals and rent control hearings. He also developed an early web-based MLS for income property.
Today, Robert leads IPS with a focus on combining first-class property management with investment profitability and cash flow. He also serves as a Multifamily Venture Partner at Shadow Ventures, sits on the Executive Council for Multi-Housing News, and serves on the Advisory Council for Blueprint.
Robert and Jonas get into a central question for anyone managing or investing in property: what happens when AI can bring together all the information about a building and identify things you did not know to look for?
In this episode
From property management to asset management. Robert explains how IPS is evolving beyond traditional property management into asset management, with AI providing a new ability to bring data together, ask questions, build models, and look for things the team may be missing. For Robert, the opportunity is not simply more technology. It is improving the odds of success for the owners and family offices they serve.
AI is still in kindergarten. Robert describes today's AI as being in "kindergarten or first grade," while pointing to companies such as Palantir as being much further ahead. He believes the real transformation comes when AI can move beyond analysis and start understanding and interpreting information well enough to make decisions. He is interested in what happens when AI, computing power, and robotics develop together.
Why AI could change the way you diagnose a vacancy. A vacant apartment does not necessarily mean the rent is too high. Robert describes how AI could look across rental data, tenant information, maintenance records, and other factors to identify the real reason a unit is sitting vacant. If maintenance is taking six days to complete work orders, for example, lowering the rent may be solving the wrong problem.
The power of seeing the whole picture. Robert sees the greatest opportunity in bringing together information that traditionally sits in separate places. Leasing data, tenant longevity, rents, demographics, employment, maintenance, expenses, and other property information can all contribute to a much more complete picture. The challenge is making sure AI interprets that information correctly and combines it with the experience and judgment of people who understand the business.
Exception management and missed revenue. One of Robert's most compelling examples is AI reviewing leases and rent ledgers to find missed opportunities. If a lease says a tenant has a pet and should be paying a pet fee, but that fee never appears on the ledger, AI can identify the discrepancy. Run that process regularly across thousands of units and small missed items can turn into meaningful improvements in revenue and net operating income.
AI that tells you what needs attention. Robert does not want another report sitting in an inbox. He wants software that monitors the business, identifies something important, and alerts him. He gives the example of tracking an underlying interest rate index and receiving an alert a year in advance when a property's mortgage costs could become a problem. For him, the next step is AI that takes action when it sees something rather than simply producing paperwork.
Why the right question matters more than the data. Robert returns to a lesson from a business class he took years ago: everyone wants data, but the real question is what that data is telling you. Forty years of experience can provide context that a number on a spreadsheet cannot. Robert's concern is that AI may have access to enormous amounts of information without yet understanding the context required to interpret it correctly.
Robots are coming too. The conversation moves beyond software into robotics. Robert sees robots eventually handling repetitive physical tasks such as vacuuming hallways, landscaping, painting, and construction work. He points to Amazon warehouses that can operate without lights because robots are doing the work and argues that the implications for property operations and labor could be enormous.
What AI can uncover that you do not know to look for. For Robert, one of the biggest benefits of AI is discovering things that would otherwise remain hidden. Instead of having people spend hours going through paperwork looking for anomalies and errors, AI can do the initial investigation. The condition is that the data must be good, the system must be trusted, and sensitive information must remain private.
AI and the move toward predictive asset management. Robert is experimenting with simulations and looking at how AI can help owners think further ahead. He wants systems that can monitor factors such as interest rates, rents, and lease terms and show owners where they are likely to stand a year from now. The goal is not perfect prediction. It is getting enough advance warning to make better decisions.
Don't build an expensive AI tech stack just because you can. Robert's advice to people getting started with AI is to learn the technology and become comfortable using it, but avoid chasing every new product. He warns that it is easy to end up with eight different companies doing eight different things, while the owner is simply paying for an increasingly complicated technology stack. Every tool needs to have a clear payoff for the management company or the property owner.
Why Robert is moving from Google to Perplexity. In his personal use of AI, Robert says he is almost done with traditional Google search and has moved toward Perplexity because he likes getting sources with his answers and does not feel he is simply being directed toward paid links. He also uses Claude Pro to test ideas and explore different possibilities. His advice is to be explicit about what you want, ask for reliable sources, and tell the AI not to make things up.
The AI aha moment is getting bigger. Robert says his realization about AI has not been one single breakthrough. Instead, it has grown as he has understood more of what the technology can do. AI is forcing him and the industry to step back and ask better questions about what they should be looking at, what they need to know, and what actions they should take. He sees tools such as Yardi's Virtuoso opening up a future where owners and managers can simply ask questions of the huge amounts of data already sitting inside their property management systems.
Mentioned in this episode
Robert Salwasser · Income Property Specialists (IPS) · Shadow Ventures · Palantir · Claude · Claude Pro · Perplexity · Yardi · Yardi Matrix · Yardi Virtuoso · Dwellsy · Google · Waymo · Amazon · Multifamily · Asset Management · Property Management · AI Agents · Robotics · Rent Control · Net Operating Income (NOI) · Debt Service Coverage Ratio (DSCR)
Net Effective is a conversation with the people running residential rentals about how they are actually using AI. New episodes weekly, about 30 minutes. Subscribe at neteffective.show.
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