Computing in the Dark: What You Can and Cannot Do With Fully Homomorphic Encryption (FHE)
Techstrong.IT, Thursday, November 5th, 2026
Fully homomorphic encryption is becoming practical, but workloads must fit its constraints; a set of questions helps assess feasibility.
Fully homomorphic encryption (FHE) lets organizations compute on encrypted data such as medical, financial or biological records; long considered impractical, it is now becoming feasible thanks to acceleration hardware, open-source tooling and AI-assisted coding.
Applications must still be shaped to fit FHE's constraints, so the piece offers questions to decide whether a project is a good fit.
The first is whether data exposure would cause serious harm, such as regulatory exposure, breaches or IP theft, enough to justify the overhead.
Another is whether the computation can run as a fixed circuit, since FHE cannot branch on encrypted values with ordinary if/then logic and works best when the same operations run regardless of input.