AI is becoming cheaper, faster, and easier to access. But the more I think about it, the less I believe the real value will come from the model alone.
What keeps standing out to me is the invisible human effort behind every intelligent system. A single correction, feedback loop, curated dataset, or model adjustment can completely change an output. Yet most AI platforms absorb those contributions quietly, without leaving any visible trail behind.
That is where blockchain starts making sense for AI.
Not as hype, but as infrastructure for attribution. A way to track who contributed what, how it influenced the system, and whether that history can still be verified later.
This is why @OpenLedger feels interesting to me. Instead of treating AI like a black box, it focuses on provenance, ownership, and traceability across AI workflows.
And I think that distinction matters more than people realize.
Cheap intelligence is easy to scale. Trusted intelligence is harder.
As AI systems become more layered, reused, and interconnected, verification may become the premium layer of the market. In that world, the biggest value may not come from who used the model, but from who can prove where the intelligence came from.