Francois Lamy is the SVP of Product Management – AI and Integrated Product Engineering at PTC. He leads the company’s AI strategy, governance, and internal enablement, while driving the integration of AI into PTC’s product portfolio to enhance customer value and operational insight. Francois also leads the strategic initiative of Integrated Product Engineering - an initiative that bridges ALM and PLM to create a unified, collaborative model-based digital thread across software and hardware development. Since joining PTC in 1998, Francois has held multiple product and people management roles spanning MCAD, ALM, PLM, SLM, UX and SaaS platform development. He holds a Bachelor of Sciences in Mathematics and an MS in Mechanical Engineering from Arts & Métiers, France.
There’s been a lot of buzz around the MIT “State of AI in Business 2025” report, which found that 95% of GenAI initiatives fail to deliver measurable value. That finding has sparked debate across industries, and for good reason. It underscores the urgency and complexity of deploying AI effectively.
At PTC, we view this statistic not as a setback, but as confirmation. The report validates our GenAI strategy, which is designed to help customers overcome the very challenges that derail most AI efforts. In the sections that follow, we’ll explore the common failure points identified by MIT and demonstrate how PTC’s approach enables customers to succeed where many others fall short.
What’s going wrong in the market?
MIT’s research highlights four recurring issues that commonly undermine GenAI success:
- Brittle workflows: AI tools that aren’t integrated into real business systems break easily when scaled
- Weak contextual learning: Generic AI lacks domain-specific knowledge and forgets what it learns
- Misalignment with operations: AI pilots often target flashy use cases that don’t match actual user needs
- Stalled at pilot: Most projects never make it past the demo phase due to scalability and security concerns
These failures aren’t just technical—they’re structural. They reflect a lack of integration, context, and enterprise-grade delivery.
How PTC enables customer success
We’ve built our GenAI offerings to directly address these challenges:
- Embedded in workflows: Our AI features are integrated into the tools our customers already use, including Creo, Windchill, Codebeamer, ServiceMax, and more, to ensure AI works in context and in alignment with existing business rules and processes
- Trusted data foundation: Our AI is powered by high-quality product data, not generic internet content, guaranteeing outputs that are relevant, reliable, and grounded in the customer’s own reality
- Domain-specific intelligence: We build AI for engineers, service teams, and product managers with immediately useful solutions aligned with real-world tasks that reflect deep industry expertise
- Enterprise-grade delivery: Our GenAI features are rigorously tested, validated, and supported, leveraging managed, enterprise-grade models that are continuously improved by leading AI providers—allowing us to focus on delivering targeted, cost sensitive, and high-impact AI capabilities
- From pilot to production: While most GenAI projects stall out, PTC’s integrated approach helps customers move from pilot to production with confidence by not just promising AI but delivering it responsibly and at scale
These capabilities distinguish PTC’s GenAI strategy and enable our customers to be part of the 5% of initiatives that succeed. By combining deep domain expertise, trusted data, and enterprise-grade delivery, we help customers implement AI that works effectively, reliably, and at scale.