ASHRAE AI Roadmap
The American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) is a global professional association committed to advancing the arts and sciences of heating, ventilation, air conditioning, refrigeration, and related systems. ASHRAE develops widely recognized technical standards and guidelines and provides education and certification programs for engineers and industry professionals. Its mission is to serve humanity by promoting sustainable technology and improving indoor environmental quality and energy efficiency.
ASHRAE technology leaders asked Heller to help them clarify where AI could responsibly add value—without risking member trust or intellectual property tied to their Standards. Through a structured AI preparedness assessment and collaborative workshops, we co-created an actionable roadmap to move from exploration to measured incorporation of AI.
ASHRAE, like many nonprofits without an AI roadmap, had a ban on AI use in the organization. This led to the use of “shadow AI”—staff experimenting with tools without policy or oversight. At the same time, data lived in silos, governance was informal, and teams held differing views on when and how to use AI.
Leaders were excited about AI’s capacity to serve their members better but hesitant to adopt AI across the organization because they were concerned about losing control of proprietary information. The organization needed a unifying strategy that prioritized privacy, fairness, and member value while aligning staff across departments.
Discovery & alignment. Heller conducted four AI workshops to document goals, current maturity, and AI Guiding Principles; we identified ASHRAE’s AI maturity to be Exploration, with a plan to advance to Incorporation.
Data review. We inventoried data sources, mapped systems, and evaluated the feasibility and impact for each proposed use case—pinpointing gaps in governance, data management and integration, and processes that would limit AI success.
Governance-first roadmap. We recommended standing up an AI Governance Committee, defining permitted uses of AI, formulating an Acceptable Use policy and AI reference style guide, and establishing third-party risk and monitoring practices.
Platform and rollout planning. For near-term productivity, we proposed a phased Generative AI approach inside their current tools and using the Copilot function they already had access to (with Purview monitoring), then expanding to Copilot Studio for power users—paired with training and permission reviews.
Change management. We advised proactive communications, role-based training, and a clear “why statement” to reduce fear, build buy-in, and improve adoption.
This approach actively guides mission-driven organizations to align AI adoption with their organizational goals. We start by establishing clear guardrails, identifying low-risk productivity gains, and designating a single, monitored GenAI entry point to reduce shadow AI and unnecessary risk.
From there, organizations can move deliberately into high-value use cases—such as member, patient, or student services, and content or licensing workflows—using responsible, human-led testing to ensure AI reduces manual work, improves efficiency, and better aligns staff time with mission-critical needs before anything is launched.
If you’re ready to turn AI from adhoc experiments into a safe, mission aligned program, we can help you replicate this roadmap. Share your goals and systems, and we’ll shape an adoption plan your stakeholders can support.
If you work at a nonprofit, education, or healthcare org and you need help with your technology project, get in touch!
