Executive summary
Multifamily firms are accelerating their AI investments, and increasingly, those investments are moving toward front-office use cases. But in a sector that buys rather than builds its technology, vendor-driven adoption is outpacing governance. This article explores the most valuable front-office AI use cases, the governance challenges firms need to get ahead of and what separates the firms already seeing measurable returns.
Vendors embed AI into platforms faster than firms can govern
The multifamily sector is building its next chapter, and AI is at the center.
After several years of record construction, rising operating costs and a challenging capital environment, most owners and property managers have been focused on navigating disruption.
“The companies we work with have spent the last few years just trying to keep up. Now that market conditions are stabilizing, multifamily leaders are focusing on upleveling the ways they meet stakeholders’ evolving expectations,” said Greg Ross, Grant Thornton’s Head of the Construction and Real Estate industry. “They’re juggling investors who want greater transparency and better returns, residents who expect more personalized service and property teams who are being asked to manage increasingly complex portfolios with the same resources.”
AI is where many firms are turning to meet those expectations. Grant Thornton’s 2026 AI Impact Survey shows that: half of construction and real estate leaders surveyed said they’re already piloting AI in select use cases, and 36% are scaling it across multiple functions.
But scaling AI is more challenging than it may seem. Most construction and real estate firms buy their technology rather than build it, and vendors are moving fast, embedding AI tools into existing platforms without equipping property managers with the tools or best practices on how to govern them properly across their organization. As a result, property teams are adopting tools before the underlying processes, data and governance structures are ready to support them.
That creates a significant gap between capability and governance, and that’s where risks emerge. Only 13% of construction and real estate leaders surveyed are confident they could pass an AI governance audit in the next 90 days. And in a sector that heavily relies on third-party technologies, governing those technologies is critical, and across multiple owners and properties, it can be challenging.
The firms seeing real returns aren't the ones adopting AI the fastest. They're the ones investing with intention, building the right governance foundation, and establishing clear ownership and measurement definitions from the start.
Moving toward front-office AI use cases
For most multifamily firms, AI started in the back office, automating accounting, procurement and accounts payable activities. That’s why 63% of construction and real estate leaders report efficiency gains as a primary benefit of using AI. However, only 28% named revenue growth and 36% cited cost reduction. To drive better returns with measurable business outcomes, multifamily firms are beginning to shift their AI investments toward more front-office use cases.
High-value AI use cases in multifamily real estate — and how they’re being measured
- Leasing and lead conversion to drive faster response times and improve conversion rates
- Resident engagement and retention including streamlining key workflows
- Portfolio-level analytics and reporting to enable faster, more informed decision-making across disparate data sources
- Automating key operational workflows at properties allowing more time to focus on value-add activities
- End-to-end workflow automation, where agentic AI not only supports decisions but also executes core operational workflow steps
Each use case should tie directly to KPIs such as:
- Leasing → lead response time, conversion rate, cost per lease
- Maintenance → resolution time, cost per work order, resident satisfaction
- Revenue → occupancy rate, rent growth, delinquency trends
“Firms have been talking about back-office automation for years. AI just makes it more accurate and efficient,” said Cody Root, Grant Thornton Tech Strategy Manager. “Many front-office use cases are genuinely new, with advanced capabilities like agentic automation for leasing, guided AI tours, instant response to leads and generating renewal packages automatically.”
Client example: AI improves leasing and resident engagement for multifamily firm
A national multifamily property management company was facing increasing demand across its portfolio and needed a more scalable way to manage leasing inquiries, resident communications, renewal activity and maintenance-related follow-up. Grant Thornton worked with the company to implement an AI-enabled leasing and resident engagement solution to improve response times, support faster lead conversion, streamline renewal communications and provide more timely resident support. The implementation led to higher lead-to-lease conversions and a more consistent renewal experience, allowing site teams to shift from administrative tasks to higher-value resident retention activities.
To pursue these front-office opportunities, most multifamily firms are turning to third-party technology vendors, and those vendors are quickly embedding AI into platforms and pushing for expedited implementation. That speed creates its own set of challenges.
Third-party AI vendors add complexity
More than any other industry, construction and real estate companies buy their AI technology, with 87% saying they mostly buy rather than build, compared to 32% across all industries. But after an AI tool is selected and purchased, third-party vendors embed property technology capabilities into firms’ platforms with limited transparency into how the tools are embedded into the firm’s existing data and systems and how they’re governed. And while the vendor owns the tool, the operator owns the liability.
"Vendors are approaching companies with AI as a way to increase returns, especially on the front-office side," said Molly Whyte, Grant Thornton Tech Strategy Managing Director. "They’re selling the idea that property managers can layer in AI capabilities without doing any of the development themselves. That can be a great model, but you still have to account for the significant lift required internally to make the technology perform as designed."
That internal work is where many get caught off guard. Vendors focus on going live quickly, but there's a significant gap between implementation and effective operation. Property-level employees may never have worked with AI tools before. Governance decisions need to be made around access controls, communication standards and model oversight, which many firms may have never had to consider.
As a result, leadership may decide to invest in tools before the underlying processes are ready to support them. "The processes these firms are running aren't set up to allow AI to fit on top in a governed way," said Cody Root, Grant Thornton Tech Strategy Manager. "They're being pressured by the market and investors to implement these tools, but when the foundation isn't there, they're not seeing ROI."
Getting the foundational elements right is what separates firms that are getting results from those running AI they can’t control. And for most in the multifamily sector, building it requires confronting some governance gaps they may not have known they had.
Getting AI governance right in multifamily
To realize value from AI, and manage the risks that come with it, leaders need to address three interconnected governance areas: data, regulatory compliance and accountability.
1. Data architecture
When implementing an external AI tool, firms are layering them on top of already complex data and platform environments.
“With any new technology implementation, every industry has to deal with connecting the dots between data and systems,” said Tony Dinola, Grant Thornton Tech Strategy Partner. “In multifamily, that problem multiplies: with fragmented property management systems and ERPs across multiple owners, properties and vendors they’re working with.”
Fragmented data is one of the most common reasons AI investments underperform. When property management systems and ERPs are inconsistent across owners and properties, AI can't operate reliably. More importantly, firms can't audit what their AI is doing or why. Without a clean, consistent data foundation, there's no way to know whether AI decisions are accurate, compliant or even traceable. When managing portfolios across multiple owners and platforms, establishing that foundation should be a prerequisite for everything else.
2. Regulatory compliance
AI makes data more accessible and decisions faster but it doesn't change the regulatory environment firms are operating in. Fair Housing requirements, state and local regulations around pricing and fees, disclosure obligations and lease agreement standards vary by state, city, and in some cases, property type. They're also evolving rapidly as regulators begin to address AI-driven decision-making specifically.
“Companies often expect vendors to own compliance, but that’s not enough,” Whyte said. “The regulatory responsibility still sits with the decision-maker. This means working with vendors who take compliance seriously and building internal monitoring processes to stay ahead of what's happening across the portfolio.”
When AI is interacting directly with prospective and current residents at scale, the regulatory exposure is happening real time, across every interaction.
3. Accountability
When a vendor implements an AI-enabled platform, they'll ask the firm to make configuration decisions: how should the AI communicate with residents? What access controls are in place? How is the tool governed as property information changes? These are questions most organizations have never had to answer before.
“Vendors ask clients how they want to configure everything, including governance decisions most have never had to consider,” Whyte said. “Organizations may need to rethink their operating model, especially how they monitor risk, especially when AI is interacting directly with residents or driving key business decisions.”
Addressing these areas with a sound governance foundation not only reduces risk, but also determines whether AI investments actually deliver the returns firms are expecting.
How we can help you
INDUSTRY
SERVICES
How to achieve AI value in your front office
Multifamily firms are increasingly investing in front-office AI, and the momentum isn't slowing down. To get the most out of those investments, especially as they pursue partnerships with third-party prop tech vendors, they should focus on data, governance and accountability:
- Track value realization from day one. AI investments need to be tied to measurable outcomes from the start. Multifamily property managers that define success metrics upfront and monitor them continuously are better positioned to course correct, demonstrate AI ROI and make the case for continued investment.
- Invest in the data and governance foundation before scaling. Fragmented property management systems, inconsistent data across owners and properties, and weak data quality are among the most common reasons AI investments underperform. Firms that address these foundations early are able to scale faster and with less risk.
- Build vendor oversight into your AI program from day one. Vendors will drive much of your AI adoption, but regulatory responsibility and accountability stay with you. Firms that establish clear oversight processes, rather than relying on vendors to manage compliance, are better positioned to scale without unexpected risk.
- Align leadership across business, operations and technology. AI success requires clear ownership and an organizational structure that can support process redesign and adoption across the portfolio.
The multifamily industry is clearly moving toward broader and more sophisticated AI adoption. Those getting the most out of it are enabling safe scaling and measurable outcomes.
Contacts:
Content disclaimer
This Grant Thornton Advisors LLC content provides information and comments on current issues and developments. It is not a comprehensive analysis of the subject matter covered. It is not, and should not be construed as, accounting, legal, tax, or professional advice provided by Grant Thornton Advisors LLC. All relevant facts and circumstances, including the pertinent authoritative literature, need to be considered to arrive at conclusions that comply with matters addressed in this content.
Grant Thornton Advisors LLC and its subsidiary entities are not licensed CPA firms.
For additional information on topics covered in this content, contact a Grant Thornton Advisors LLC professional.
Share with your network
Share