Each AI agent acting on a user's behalf creates a new "non-human identity" with its own keys and API access. This proliferation of autonomous agents dramatically increases the number of potential exploit points, a problem traditional security models weren't designed to handle.

The future of work involves potentially millions of AI agents operating within a company. This requires a new governance layer, including agent inventories, inspectable reasoning traces, identity management, and sandboxed execution environments to maintain security and control.

Managing human identities is already complex, but the rise of AI agents communicating with systems will multiply this challenge exponentially. Organizations must prepare for managing thousands of "machine identities" with granular permissions, making robust identity management a critical prerequisite for the AI era.

The ease of creating specialized AI agents is setting the stage for "agent proliferation." Soon, companies will suffer from deploying multiple, uncoordinated agents that, while useful independently, will create a chaotic and fragmented experience for customers, leading to brand damage and operational messes.

As AI generates more content and powers sophisticated bots, the fabric of online trust is eroding. This forces platforms and services, from social media to LLM APIs, to require identity verification to differentiate humans from agents, creating a massive demand tailwind.

Teleport's decision to build a single identity layer for humans, machines, and workloads prepared them for the AI wave. This architecture became critical for containing non-deterministic AI agents, as enforcing security policies requires reasoning about all identity types simultaneously.

The rise of autonomous software agents like Cognition's "Devin" introduces a new, critical security layer: agent identity. Organizations must decide if agents have their own unique identities or inherit them from the deploying user. This is fundamental for creating auditable logs and securing their actions.

The current market of specialized AI agents for narrow tasks, like specific sales versus support conversations, will not last. The industry is moving towards singular agents or orchestration layers that manage the entire customer lifecycle, threatening the viability of siloed, single-purpose startups.

For AI agents to move beyond human oversight, they'll need their own identities, budgets, and authorization to consume services. This creates a new enterprise tooling category focused on agent governance, ensuring they don't "run wild" with resources or access sensitive data.