Leveraging AI for Growth: Practical Lessons for Multifamily Industry Leaders
Jun 12, 2025
In a recent episode of Walker Webcast, Willy Walker interviewed Jeff Bussgang, Co-Founder and General Partner at Flybridge Capital and Senior Lecturer at Harvard Business School, discussing actionable insights from his latest book, The Experimentation Machine: Finding Product Market Fit in the Age of AI. Here’s how multifamily owners, operators, and developers can leverage these insights to enhance growth and operational efficiency.
Embracing AI Disruption
AI isn't just for tech startups—it's reshaping industries, including multifamily real estate. Traditional competitive advantages, such as location or historical brand strength, are now susceptible to rapid disruption. Multifamily businesses must proactively integrate AI-driven strategies to streamline operations, enhance resident satisfaction, and remain competitive.
Accelerating Innovation with AI
Bussgang emphasizes AI’s ability to rapidly accelerate product-market fit. Multifamily companies can apply this approach to quickly test leasing innovations, resident services, and operational efficiencies. AI allows swift prototyping of new services, immediate resident feedback, and rapid adjustments, significantly reducing the cycle from idea to implementation.
New Scalable Models
AI redefines scalability. Multifamily companies can now scale operational capabilities—leasing, marketing, resident engagement—with leaner teams. By leveraging AI-driven virtual leasing agents, automated marketing tools, and predictive maintenance systems, organizations can significantly reduce overhead while enhancing resident experiences.
Case Study: Topline Pro's Multifamily Parallel
Bussgang highlighted Topline Pro, a startup automating small-business marketing and operations using AI. Multifamily companies can similarly employ AI tools to:
Identify potential residents via personalized, data-driven outreach.
Automate targeted marketing campaigns to specific demographics.
Provide tailored resident communication and services, significantly improving conversion rates and resident retention.
Implementing AI through Reverse Mentorship
Reverse mentorship can help multifamily leaders adopt AI effectively. This involves pairing senior executives with younger, AI-native employees who provide hands-on training, insights, and practical demonstrations. This dynamic partnership encourages continuous learning, bridging generational gaps, and rapidly integrates AI-driven practices into everyday business workflows.
Evaluating Opportunities: The HUNCH Framework
Flybridge Capital’s HUNCH framework can be particularly valuable for multifamily leaders evaluating technology investments or new services:
Hair on Fire: Ensure the AI-driven solution addresses urgent operational or resident needs.
Usage: Measure consistent adoption by residents and staff, rather than superficial engagement.
Net Promoter Score (NPS): Confirm that residents or staff genuinely value and recommend the solution.
Churn: Carefully track retention of residents and team satisfaction to ensure long-term success.
High Unit Economics: Evaluate the ROI rigorously, ensuring financial sustainability and scalability.
Capitalizing on the AI Dividend
The multifamily industry is uniquely positioned to capitalize on the "AI dividend"—productivity gains from significant investments made by technology giants. Practical AI solutions are now accessible for streamlining property management, enhancing resident experiences, and increasing profitability.
Final Thoughts
As the multifamily sector navigates an AI-driven future, adaptability, continuous experimentation, and learning are crucial. Whether improving leasing processes, enhancing resident satisfaction, or optimizing operations, integrating AI into strategic initiatives is essential for sustained success.
This blog was inspired by insights from the Walker Webcast featuring Jeff Bussgang, Co-Founder and General Partner at Flybridge Capital and Senior Lecturer at Harvard Business School.