Does Fully Homomorphic Encryption (FHE) Actually Matter for AI Tokens?

Been seeing a wave of AI projects claiming to use “fully homomorphic encryption” as a selling point lately, Privasea AI ($PRAI) being one of the latest to roll it out. On paper, it sounds impressive: being able to compute directly on encrypted data without ever decrypting it. But I’m wondering how much does that really matter for an average user or even most Web3 use cases?

Are we heading into another buzzword cycle like we saw with “layer 2” or “modular blockchains,” where the tech is solid but only a handful of projects actually implement it in a meaningful way? Or is this something that’s genuinely going to reshape how AI models interact with user data in crypto?

Anyone who’s deep in the privacy or AI side of things, you think this is actually game-changing, or just another way to dress up a whitepaper?

Tech buzzword cycles only work for a while before a new & better form of the tech buzzword comes along. Technology by definition constantly replaces itself, as the goal of technology is to keep doing more with less. Most people have no idea about the significance of being able to run computations on data without decrypting it. We see this most clearly with Zero Knowledge (ZK) proofs.

Right now the meta is Internet Capital Markets, a few months ago it was Crypto X AI, in due course it'll be something else.

On the note about privacy technologies though, the market hasn't generally rewarded them well, as more people are in crypto to try to make money rather than retain their privacy (otherwise they wouldn't be using an open & distributed ledger with many of the participants being willingly doxxed). You can compare the total market cap against privacy coin market caps to understand this clearly:

Monero - $6B mcap
Zcash - $600M mcap

People who want to use privacy tech will use it, but most people value convenience over this.