The AI in Business Podcast How Data Ownership Drives Trustworthy AI Models - with Joe Lang of Comfort Systems
Aug 27, 2025
Joe Lang, Vice President of Service Technology and Innovation at Comfort Systems USA, dives into the intersection of data strategy and AI in the field services sector. He emphasizes the importance of a robust data strategy before investing in AI technologies, warning against the pitfalls of relying solely on cloud solutions. Joe discusses the need for organizations to view AI initiatives as long-term R&D projects and addresses the skills gap in the industry. He advocates for responsible data ownership to foster trustworthy AI models while maximizing scalability and efficiency.
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Storage Isn’t A Substitute For Data Ownership
- Storage alone won't fix messy data or produce reliable intelligence.
- Organizations remain responsible for structuring, labeling, and governing their own data.
Don’t Outsource Data Cleaning To Cloud Vendors
- Avoid assuming cloud providers will clean and fix your data automatically.
- Prepare to invest internal effort into data cleaning and governance before expecting useful AI outputs.
Treat AI As R&D First
- Treat AI programs as R&D efforts rather than immediate ROI plays.
- Expect many iterations and invest in data preparation before expecting measurable returns.