In this Leadership Viewpoint, Nick Stevens, the vice president of product at ACTIVE Network, details effective strategies for community rec centers to address staffing shortages and rising demand. Stevens shares how facilities struggle to hire and retain both seasonal and full-time staff, even as demand increase for programs, pickleball, dog parks, trails and flexible drop-in options. Also, potential members expect mobile-first, self-service registration and are increasingly discovering programs via AI chat tools instead of search engines. He emphasizes how leading organizations are recruiting earlier, strengthening school and community partnerships, experimenting with wages and benefits, and using software and AI to reduce administrative work.
Enjoy!
Key Takeaways
- Staffing is the Top Pain Point
Community rec organizations are struggling to recruit and retain both seasonal and full-time staff. Local wage competition and limited benefits make these roles less attractive, even as demand for services grows.
- Demand is Rising Faster Than Capacity
Facilities are busier, but there aren’t many new buildings or significant staff increases. Organizations are being asked to “do more with the same,” making efficiency and smart scheduling critical.
- Community Expectations Are Rapidly Evolving
Residents expect mobile-first, self-service experiences for registration, booking and payment. Discovery is shifting from Google and websites to AI chat tools — like ChatGPT and Gemini — and demand is rising for pickleball, dog parks, trails and flexible, drop-in style programs. - AI and Automation Are Key Levers
Tools, software and especially AI can offload repetitive administrative work, enabling staff to spend more time serving the community. Virtual “AI workforces” are emerging as a strategic focus for 2026 and beyond. - Maximize Existing Tools and Close the AI Gap
Most organizations are under-utilizing the technology they already have. Leaders are encouraged to pause, audit their current tools, and create intentional efforts — like working groups or innovation workshops — to experiment with AI and prevent an “AI gap” between early adopters and those falling behind.
