Part 1 — Building AI Trust at Scale: The Missing Growth Lever
Introduces the idea of a “trust ceiling” in AI adoption. Argues that the real bottleneck isn’t model performance but the lack of a verifiable identity layer that makes it clear who an AI system is working for, what it’s allowed to do, and whether its outputs can be trusted.
Part 2 — Building AI Trust at Scale: Translating Promise into Value
Dives into three core functions where decentralized identity unlocks AI’s value: agentic delegation, hyper-personalization, and decision-making in a world of synthetic content. Shows how verifiable credentials and runtime authorization provide the trust rails for AI agents and data flows.
Part 3 — Building AI Trust at Scale: Why your content needs an ingredient list
Examines content provenance and creator rights in an AI-saturated media ecosystem. Explores how C2PA Content Credentials and DIF’s Creator Assertions Working Group can make media supply chains transparent while preserving creator control and privacy.
Part 4 — Building AI Trust at Scale: Authorising Autonomous Agents at Scale
Examines why current identity and access-control systems — especially OAuth — break down in multi-agent environments, and why autonomous agents require fine-grained, time-bound delegation, attribution, and cross-boundary trust. Introduces how DIF’s Trusted AI Agents Working Group is tackling these challenges using decentralized identifiers, verifiable credentials, and capability-based models to establish verifiable delegation chains at scale.
Part 5 — Coming soon
