Most people assume stronger attribution automatically strengthens AI markets. I think the opposite risk is more important. @OpenLedger $OPEN #OpenLedger The deeper provenance systems become, the harder it gets for markets to treat AI assets as fluid capital. Financial markets scale

through abstraction because assets must move fast enough to be bundled, repriced, and redistributed continuously across the network. Attribution systems do the reverse. Every added layer proving who contributed data, models, inference, or agent behavior increases informational weight around the asset itself. That

improves trust, but it also introduces friction into pricing because markets now have to process expanding histories of dependency and ownership before capital can move efficiently. The hidden danger is that attribution may scale faster than abstraction. If that happens, AI assets become increasingly verifiable while

progressively less tradable. Markets stop optimizing for circulation and start optimizing for validation. The implication is simple: the winning AI ownership layer will not be the one that records the most provenance, but the one that prevents provenance from slowing liquidity.