Right now, there’s a gold rush for AI use cases. Some offer companies a sharp competitive edge. Others? They have the potential to lift entire industries.
So what if, instead of everyone hoarding their data, we started building smarter models together? More data means better AI. Shared resources mean stronger implementation. In some cases, collaboration isn’t just smart, it might be the only way forward.
Yes, data is sacred. It’s the new gold and often the core of a company’s value. Handing over raw data to competitors? Not happening. But contributing to a shared industry model while retaining control of your own data? That might just be worth thinking about.
A few examples come to mind:
- Industry-wide fraud detection in finance (fraudsters already collaborate, might be time we caught up)
- Smarter diagnostic imaging in healthcare (less guesswork, more precision)
- Safer cars through pooled safety data (because building crash test dummies from scratch is not a competitive advantage)
- Improved demand forecasting in retail (less waste, more revenue)
- Predictive maintenance in aviation and manufacturing (fewer surprises mid-air or mid-shift)
- More effective educational support tools (because every student deserves a fighting chance)
