How fully homomorphic encryption is reshaping secure AI

https://www.siliconrepublic.com/enterprise/zama-ai-encryption-fhe-privacy-data-opinion

Publish Date: 2026-03-09 12:12:00

Zama’s Jeremy Bradley discusses why the AI surge is forcing businesses to take privacy more seriously and how new technologies are responding.

Published last month, 2026’s International AI Safety Report made two things clear: while AI deployments were still pilots or limited-scope tools just one to two years back, AI capability has advanced at lighting speed, and adoption – even faster. In fact, more than 700m people now use leading AI systems every week, which is a rate of uptake that far outpaces earlier technologies like the personal computer.

For companies witnessing this shift – in both the tech’s capabilities and demand for it – the lure to capitalise on AI is strong. Delivered largely through cloud-based data processing, AI opens the door to everything from automating decisions and extracting value from data at scale to moving far faster than competitors if embraced early doors. These pros have seen many already embed it into core workflows – including pricing, decisioning, R&D, legal, healthcare and finance.

The transparency paradox

However, as soon as AI touches core IP and regulated data, businesses hit a roadblock. Dealing with systems that are open by design, they struggle to support real-world use cases involving any kind of confidential data (payroll, identity, enterprise finance etc).

This hasn’t necessarily slowed AI adoption, but it has made it uneven. Specifically, we’ve seen rapid experimentation at the edges, where AI is low-risk, but caution when it comes to AI systems training on or interacting with sensitive, regulated or proprietary data. This has seen many limit production use to narrowly scoped tasks; rely on thinner, sanitised, or synthetic datasets; or keep high-value workloads out of shared cloud environments entirely.

This all of course stems from the risk of data exposure, whether that’s via third-party infrastructure, data being reused in ways that are hard to audit, or…

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