Every pricing team eventually walks into the same room, the one where next year’s budget gets built. For 49% of the operators ApartmentIQ surveyed, that meeting starts in summer. For 40%, it’s a fall exercise. The remaining 11% never really leave the room, treating budgeting as rolling and ongoing. But wherever it lands on the calendar, the question at the center of the table is never “what did rents do last year.” It’s “what are they going to do next.”
What’s the biggest challenge in building next year’s budget?
That’s the real bottleneck, and the data backs it up plainly. Sixty percent of operators named forecasting demand as their single biggest budget-building challenge, far ahead of data accuracy and availability (20%), time and resource constraints (13%), a lack of forward-looking supply and demand data (4%), and justifying increases to ownership (2%). It’s the same confidence gap from part one, showing up right on schedule. Operators aren’t struggling to find last quarter’s numbers. They’re struggling to trust next quarter’s.
Where does AI actually stand in pricing decisions?
It’s the kind of problem that practically begs for an AI-shaped answer, and the industry knows it. But the survey shows an industry standing at the edge of the pool rather than diving in. Just 31% are actively using AI-driven pricing or forecasting tools today, 40% are evaluating, 13% are piloting, and 16% aren’t considering it at all. More than half are watching closely without putting it into production.
What’s holding AI adoption back?
The hesitation isn’t really about money. Cost was cited by only 13% as the main concern. What’s actually holding people back is trust: 31% pointed to trust and accuracy concerns, another 18% said they don’t have clean enough data to feed a model, and 16% said the recommendations they’ve seen aren’t transparent enough to act on. That skepticism holds even though the tools are already sitting on people’s desks, 27% have enterprise access to Claude, 24% to Copilot, 18% to Gemini, 11% to ChatGPT. The access is there. The trust to point it at next year’s rent roll isn’t, yet.
What do operators want most for 2026-2027?
So what do they actually want. Twenty-nine of the 45 respondents answered that question in their own words, and the same theme kept surfacing: better, more accurate market data, cited by 11 people. “Better market data that focuses on accuracy of supply, market rents, and concessions,” wrote one Owner/Asset Manager already using AI tools actively. A Revenue Manager/Analyst overseeing a 10,000-plus-unit portfolio wanted the same thing paired with better tooling: “Accurate data, and suggesting software to help.”
Concessions came up almost as often, with 9 mentions. “Eroding upfront concessions that have become prevalent in the marketplace,” a VP/Director of Operations wrote bluntly, describing a line item that’s actively reshaping effective rent, one most teams say they still can’t see clearly.
Six respondents pointed to a software or platform change on their roadmap, and one Owner/Asset Manager piloting AI tools named the endpoint a lot of teams are quietly working toward: “A holistic platform: acquisitions underwriting, revenue management, asset management, supply, market research.”
Put both parts of this survey together and the throughline is hard to miss. The infrastructure of modern pricing, the software, the daily cadence, the tech stack, is genuinely mature. What’s still catching up is confidence, and closing that gap isn’t about more automation for its own sake. It’s about better underlying data. Get that right, and the confidence in the number tends to follow.
Download The Proactive Operators Guide to Budget Season for a data-backed look at how to build next year’s numbers with more confidence.