Professor Vijay Gurbaxani makes a bold claim: most companies are approaching AI myopically, treating it as an efficiency tool rather than the next industrial revolution. Drawing on his transformation flywheel framework and examples from Reuters to a two-clinic veterinary startup that caught the attention of a 700-location PE firm, he argues the winners will be those who rethink their entire value proposition — not just their processes.

WHAT THIS PANEL COVERS

• The AI transformation flywheel starts with vision, not efficiency — companies must ask 'what more can I be doing?' rather than 'how do I cut costs?'
• Reuters uses AI to write first-draft financial news for speed, then reinvests savings into hiring more original news reporters worldwide — a model of competitive differentiation through AI
• A two-clinic veterinary startup (Dr. Treat) used AI to prompt vets during patient conversations and cross-reference an insurance database, earning acquisition by a 700-location PE firm
• Data is becoming the primary competitive moat — when all companies access the same AI platforms, what differentiates you is the proprietary data and know-how you bring
• McKinsey estimates $7 trillion in AI infrastructure investment by 2030; Mark Zuckerberg says he would 'rather overspend by $200 billion than be on the wrong side of that bet'

PANELISTS

• Stephan Balzer — Keynote Speaker, Host & Moderator; Managing Director, red onion (Moderator)
• Prof. Vijay Gurbaxani — Taco Bell Endowed Professor of Business & Computer Science; Founding Director, Center for Digital Transformation, UC Irvine

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Tags: digital transformation, AI flywheel, AI strategy, competitive advantage, Reuters, AI first company, AI intensive, value proposition, data moat, AI investment, UC Irvine, Davos 2026, unDavos, REWIRE, business model innovation