Just Do It With Data: Nike's $500M AI Gamble
Why buying four AI startups worked, why going digital-only didn't, and the frameworks you can steal
Hey Adopter,
Between 2019 and 2024, Nike’s direct sales jumped from $11.8 billion to roughly $23 billion. AI powered the entire shift. The company bought four startups, integrated them fast, and went to market.
Then an aggressive digital-only push backfired. Nike lost shelf space to competitors. The company saw its first digital sales decline since 2015. A poorly managed restructuring drove out experienced talent.
This case study matters if you’re running a company and you can’t afford Nike’s $70 billion learning curve. But you can use their playbook.
The full analysis reveals what worked, what failed, and why both matter for mid-sized companies building AI capabilities today. No theory. Just the exact frameworks you can apply Monday morning.
Who benefits most from this report:
Small to medium-sized businesses trying to figure out how to compete with enterprise budgets. You need big company insights with small company constraints. You want to learn from the expensive mistakes without making them yourself.
Inside the full case study, you’ll get:
The exact four-acquisition sequence Nike used to build AI capability in 36 months instead of five years (and how to apply the same logic with partnerships, not purchases)
How Nike’s first-party data ecosystem generates 4x higher customer lifetime value, and the simple loyalty program framework that starts your own flywheel
Why Nike’s supply chain AI tripled digital fulfillment capacity while reducing costs, and the single high-ROI process where you should deploy AI first
The organizational restructuring mistake that caused a $70 billion market cap loss (and the change management rule that prevents it)
Three implementation frameworks designed specifically for mid-market companies, with budget ranges, timelines, and success metrics
Download the full report
The 55-page case study includes financial analysis, technology stack breakdowns, implementation roadmaps, and templates you can use immediately.