AvalonBay Communities has been at the forefront of technology disruption in the multifamily industry, launching its Kanso brand, designed around a self-service, digitally driven experience, four years ago. The real estate investment trust (REIT) also has embraced centralization and artificial intelligence (AI) to improve experiences and create efficiency.
In the REIT’s latest earnings call, president and CEO Benjamin Schall said the firm will continue to utilize its scale, particularly its investments in technology and centralized services, to drive incremental growth from its existing portfolio.
“We’re now 60% of our way toward a target of $80 million of annual incremental net operating income (NOI) from our operating initiatives, with an incremental $7 million of NOI slated for this year,” he said.
Multifamily Executive caught up with Michael Coyne, vice president of operating initiatives, and Kurt Conway, senior vice president of corporate strategy, to discuss AvalonBay’s recent technology strategies.
How has the company’s approach to operational technology evolved over the past few years as the multifamily tech landscape has matured?
Coyne: Our approach has shifted from solving discrete problems to building a coherent operating system. A few years ago, we were piloting tools to address specific pain points. Now the question we ask is: How do these tools work together to support a consistent, scalable model?
Much of our recent progress has been around strengthening processes and experiences by focusing on integration, data quality, and clear ownership. That’s been critical as we’ve expanded centralization and the neighborhood model, where technology needs to support coordination across teams rather than add complexity.
Technology is most effective when it’s aligned to clearly defined processes and roles, and when it enables our associates to deliver better outcomes, not just faster ones.
What technology has made the most impact on operations?
Coyne: The biggest impact has come from technology that improves visibility and continuity across the resident and associate experience—specifically, the ability to create a single interaction thread that our whole team can see, whether that interaction happened with an on-site associate, a centralized team, or an AI-supported channel.
That continuity changes how work actually gets done. Teams respond more consistently, share context more easily, and can focus attention where it’s most needed. It also cuts friction and duplication, which matters more the larger you get. No single feature does that. It’s really about supporting coordinated decision-making across communities while preserving a local, human experience.
Centralization has been a big focus for AvalonBay. What has been centralized, and what have the results been so far?
Coyne: It’s been a long-term effort, not a single initiative. We started with back-office functions and have expanded thoughtfully into customer-facing work, including support for new leases and renewals. This was a concerted focus on areas where scale and specialization genuinely improve consistency, efficiency, and service.
That centralized model works hand in hand with our neighborhood model, where work is shared across a group of nearby communities. The result is a tiered experience spanning self-service and AI-enabled support, centralized associates, and neighborhood teams, which gives us more consistent coverage without losing accountability or the relationships that matter to residents.
How is AvalonBay leveraging AI?
Coyne: We see AI as a real opportunity to improve experiences and capabilities, and we’re approaching it with a focus on real-world applications rather than experimentation for its own sake. That means starting with known friction points where AI can manage volume, extend coverage, and offer insights across both overhead functions and operations.
We’re also identifying opportunities that simply weren’t practical or cost-effective before AI, including how we support prospects. Through our smart access platform and proprietary touring platform, we can now use AI to tailor and support the leasing experience in a much more personalized way.
We always provide a human touchpoint when it’s needed, but the ability for AI to surface real-time options and information specific to each prospect is becoming a genuine differentiator.
The Kanso model is four years in. How has it evolved from the first opening, and what lessons were learned from Kanso Twinbrook?
Conway: Kanso is our apartment brand designed around a clear premise: deliver high-quality, modern apartment homes without the amenity overhead that a segment of renters don’t need or use. We focus investment on the apartment home itself and on an efficient, self-service resident experience.
Four years in, the model has matured significantly. Early on, we were still validating the concept and learning what this customer segment truly valued. We’ve learned from resident feedback that they appreciate the modern finishes, attractive layouts, spaciousness, and the quality of our maintenance and remote staff.
What we’ve had to focus on is the shared-living experience, including noise management, trash, and common area upkeep. That’s not unique to Kanso, but, in a model with limited on-site staffing, you have to be more intentional about how you solve for it.
Operationally, we’re also continuing to make progress by optimizing our tech stack, sharpening our centralized service model, and getting smarter about where shared staffing works best across properties.
Tell me about the other Kanso developments that have opened or are in the pipeline.
Conway: We’re strategic about expansion. We’re not just looking for sites that pencil. We’re targeting markets where there’s a real gap between what’s available and what renters can afford, and where Kanso’s value proposition resonates strongest.
We have three communities open and operating in Maryland and Massachusetts. We have another six in construction or active pre-construction development in California, Massachusetts, New Jersey, and Florida.
The pipeline reflects our confidence in the model but also our commitment to scaling thoughtfully in the right markets.
What has been most surprising about this model?
Conway: The degree to which residents have embraced the self-service, digitally driven experience. We designed the model around it, but there’s always a question of whether residents will actually engage with it the way you hope. But the answer has been clear: When the technology works well and the remote teams are responsive, residents adapt quickly and appreciate the efficiency and caliber of service.