Autonomous AI models introduce supply chain and intellectual property risks, and synthetic content becomes harder to distinguish from genuine material. Organisations are increasingly unable to verify what their systems are doing – or producing.

“AI has created a new trust challenge,” Amit Sinha (pictured), CEO of DigiCert, said in a statement.

“Organisations are relying on agents, models, and content they can’t always verify. With our AI Trust solution, we help organisations confirm what’s real, secure, and approved so AI can be used with confidence.”

At the core of the architecture is an expansion of the DigiCert ONE platform, embedding cryptographic identity, integrity, and provenance controls across the AI life cycle. The approach applies established public key infrastructure principles to emerging AI use cases, enabling enterprises to enforce identity-based governance for autonomous systems, validate model integrity from development through deployment, and verify the origin and authenticity of digital content.

Industry analysts say the move reflects a broader shift towards embedding trust directly into AI infrastructure.

“Bringing cryptographic assurance to AI systems gives enterprises the ability to independently verify identity, integrity, and provenance of content,” said Jennifer Glenn, research director for security and trust at IDC.

DigiCert argues that establishing verifiable trust will become a defining requirement as AI adoption scales, particularly as regulatory scrutiny intensifies and organisations seek to reduce reputational risk.