The Reality of Building AI at Scale
About this session
AI has moved beyond experimentation, yet many organizations still struggle to turn AI investments into products that customers adopt and businesses value. After building AI products across Microsoft, AI startups, and enterprise healthcare, I learned that technology is rarely the hardest part. The real challenge is moving from promising prototypes to AI that delivers measurable value at scale.
In this keynote, I’ll share the lessons that have shaped how I think about building AI at scale: starting with the right customer and business problems, designing AI-native experiences rather than adding AI to existing products, building the data and technology foundations to scale, and creating governance that enables innovation and earns customer trust. I’ll also explore what happens when the technology evolves faster than traditional product development and why scaling AI ultimately requires organizations to rethink their culture, skills, roles, and ways of working.
Through real-world successes, failures, and lessons learned, attendees will gain practical insights they can apply to move beyond AI experimentation and build products and organizations that deliver lasting customer and business value.
Speaker
Key takeaways
- Start with customer and business value, not AI.
- Build the foundations and adaptability required to scale.
- Transform the organization alongside the technology.