A 70-year-old manufacturer’s proprietary test data may be a more defensible AI moat than software capability alone. In this episode of Technovation, Peter High speaks with Udit Mehta, Chief Technology Officer at Simpson Strong-Tie, about building an AI strategy on a foundation of structural engineering expertise. Mehta joined in 2024 from Carrier and Siemens, and has spent two years modernizing the company’s infrastructure, upskilling 1,200-plus employees on AI, and launching an integrated cloud-native software portfolio for component manufacturers. He describes how Simpson’s combination of hardware, software, services, and proprietary test data creates a position pure-play software entrants cannot match, and why AI must augment engineering judgment rather than replace it.
Key Highlights:
- Why Simpson’s hardware-plus-software bundling creates an AI moat pure-play entrants structurally cannot replicate
- How AI tools assist structural engineers without removing human judgment from high-stakes decisions
- Why workflow embeddedness, not technical feasibility, is the real adoption gate in construction
- How a three-pillar AI strategy spans individual productivity, enterprise value, and customer growth in parallel
- Why business owners, not AI teams, must remain accountable for every AI-enabled workflow outcome
This podcast episode is sponsored by Blitzy. Autonomous software development at enterprise scale.
