DigiCert has announced the introduction of its AI Trust architecture, a new solution aimed at securing AI systems and their outputs for organizations. This innovation includes advancements for protecting autonomous agents and AI models, along with features for verifying the authenticity of digital content in the evolving AI landscape.
The progressive emergence of artificial intelligence is changing traditional trust paradigms, as autonomous agents and AI models present new challenges in supply chain risks and intellectual property security, while digital content faces scrutiny over its authenticity. At the heart of these issues is an absence of cryptographically verifiable management over AI systems.
Embedding Cryptographic Verification
“AI has created a new trust challenge,” stated Amit Sinha, CEO of DigiCert. “Organizations are relying on agents, models, and content they can’t always verify. At DigiCert, our purpose is to give people confidence in the security, privacy, and authenticity of their digital interactions. With our AI Trust solution, we help organizations confirm what’s real, secure, and approved so AI can be used with confidence.”
Addressing these concerns, DigiCert has developed a unified trust layer that integrates verification across AI agents, models, and content. This comprehensive framework supports identity-based governance, model integrity validation, and content provenance through new enhancements in DigiCert ONE.
Ensuring Verifiable Origin
This measure not only authenticates and proves the origin of content but also prevents alterations
The Content Trust Manager allows organizations to cryptographically sign and verify digital content using the C2PA standard, accepted by major companies like Adobe, Microsoft, and Google.
This measure not only authenticates and proves the origin of content but also prevents alterations, thereby combatting misinformation, brand impersonation, and AI-induced fraud. Furthering this capability, DigiCert’s Device Trust Manager lets manufacturers embed C2PA certificates directly into imaging devices, securing real-time content authenticity through cryptographic signing and timestamping from capture.
Audit Autonomous Systems
The AI Agent Trust feature offers functionalities like discovery, identity, governance, and lifecycle management tailored for AI agents.
It enables authentication and authorization, allowing enterprises to audit and oversee autonomous systems, granting every action an attributable and controlled status compliant with security protocols. The AI Model Trust provides cryptographic protections for AI models, focusing on secure packaging, signing, and runtime validation, ensuring integrity across the model’s lifecycle from development to deployment.
Automated Trust Architecture
The AI Model Trust provides cryptographic protections for AI models
Together, these features empower organizations to shift from manual processes to an automated trust framework that guarantees identity verification, integrity assurance, and continuous validation of AI systems.
Jennifer Glenn, a Research Director at IDC Security and Trust Group, emphasized the importance of cryptographic assurance in AI, stating, “AI is forcing organizations to rethink trust from the ground up. Bringing cryptographic assurance to AI systems gives enterprises the ability to independently verify identity, integrity, and provenance of content, enabling these organizations to build trustworthy AI at scale.”
Proven PKI Principles
With DigiCert's unified AI Trust structure, companies can mitigate both reputational and regulatory risks while facilitating responsible AI adoption.
They gain the capacity to verify content provenance, maintain model integrity, and manage AI agents reliably, thus transforming security and compliance from reactive to measurable and audit-ready operations. As AI usage increases, the establishment and verification of trust will be crucial for enterprise success, as DigiCert delineates the essential infrastructure, informed by established PKI principles, to support AI agents, models, and content.
DigiCert, a pioneer in intelligent trust, introduces a new AI Trust architecture designed to help organizations secure AI systems and their outputs. The company is also unveiling new capabilities to help secure autonomous agents and AI models, along with separate capabilities to provide verifiable content authenticity in the age of AI.
Artificial intelligence is accelerating innovation at an unprecedented pace while simultaneously breaking traditional models of trust. Autonomous agents act across enterprise systems at machine speed; AI models introduce new supply chain and IP risks; and digital content can no longer be trusted at face value. At the core of this challenge is a lack of cryptographically verifiable control over AI systems. Specifically, what they are, what they are authorized to do, and what they produce.
Embedding cryptographic verification
“AI has created a new trust challenge,” said Amit Sinha, CEO of DigiCert. “Organizations are relying on agents, models, and content they can’t always verify. At DigiCert, our purpose is to give people confidence in the security, privacy, and authenticity of their digital interactions. With our AI Trust solution, we help organizations confirm what’s real, secure, and approved so AI can be used with confidence.”
To address this challenge, DigiCert is introducing a unified trust layer that spans AI agents, models, and content. By embedding cryptographic verification across the AI lifecycle, organizations can enforce identity-based governance for autonomous systems, validate model integrity, and establish content provenance all within a single, cohesive framework. This unified approach is realised through new DigiCert ONE enhancements:
Ensuring verifiable origin
Content Trust Manager enables organizations to cryptographically sign and verify digital content, providing tamper-evident provenance and transparency using the C2PA standard, which is adopted by Adobe, Microsoft, Google and more. This allows organizations to prove where content originated, how it was created, and whether it has been altered, helping combat misinformation, brand impersonation, and AI-generated fraud while strengthening confidence in digital media.
Taking content authenticity even further, organizations can establish trust at the moment of capture through cryptographic signing and timestamping enabled by embedded C2PA certificates on trusted devices. Delivered through DigiCert Device Trust Manager, this capability allows imaging device manufacturers to embed trust directly into devices such as cameras, microscopes, and scanners. Content can be signed and timestamped at the source, ensuring verifiable origin and authenticity from the start and preserving trust throughout the content lifecycle.
Audit autonomous systems
AI Agent Trust - Provides discovery, identity, governance, and lifecycle management for AI agents, enabling organizations to authenticate, authorize, and audit autonomous systems. By issuing cryptographic identities and enforcing policy-based controls, DigiCert enables enterprises to govern AI agents like a new digital workforce, ensuring every action is attributable, controlled, and aligned with security and compliance requirements.
AI Model Trust - Delivers cryptographic protection and verification for AI models, including secure packaging, signing, and runtime validation. By establishing a verifiable chain of custody for models, from development through deployment, organizations can create models that have not been tampered with, are running in trusted environments, and are handling sensitive data securely, even in distributed or third-party infrastructure.
Automated trust architecture
Together, these innovations help organizations move from fragmented, manual approaches with an automated trust architecture that delivers verifiable identity, tamper-evident integrity, and continuous validation across AI systems.
“AI is forcing organizations to rethink trust from the ground up,” said Jennifer Glenn, Research Director for IDC Security and Trust Group. “Bringing cryptographic assurance to AI systems gives enterprises the ability to independently verify identity, integrity, and provenance of content, enabling these organizations to build trustworthy AI at scale.”
Proven PKI principles
With a unified AI Trust foundation, organizations can reduce reputational and regulatory risk while accelerating responsible AI adoption. They gain the ability to verify content provenance, ensure model integrity, and govern AI agents with accountability, transforming security and compliance from reactive processes into measurable, audit-ready capabilities.
As AI adoption accelerates, the ability to establish and verify trust will become a defining requirement for enterprise success. DigiCert is defining the trust infrastructure required for AI, extending proven PKI principles to agents, models, and content.
