Nil

From Marketplace to Operating System: Applied AI and the NIL Back Office

The first wave of NIL software solved discovery — match an athlete to a brand. The revenue-sharing era turned NIL into an ongoing operation someone has to run. Marketplaces don't run operations. Operating systems do, and that's where applied AI earns its keep.

Discovery in the NIL economy is solved. The unsolved, expensive part is the back office — deals, disclosures, compliance, payments — at scale. Here's where applied AI fits, and where judgment still has to win.

Applied AI in Sports Media: When Every Athlete Is a Distribution Channel

Teams and leagues are expected to produce thousands of personalized clips a week for athletes who each out-reach the old broadcast networks. The supply of moments hasn't changed; the demand for content cut from them has exploded. That gap is where applied AI earns its keep — or gets built badly.

The athlete became the distribution channel, and almost no one can feed that channel by hand. Here's where AI actually fits in sports media — and where judgment still has to win.

The Future of AI in College Athletics: What NIL Taught Us About Building for Chaos

NIL turned college sports into a fast-moving, lightly-governed market overnight. That's exactly the kind of mess AI is good at — and exactly the kind of mess that punishes software built without judgment. Here's where we think AI actually fits.