For years, we’ve talked about AI as a tool, something that responds, assists, completes. But what if that framing is already outdated?
We’re entering a transformative phase in the evolution of AI agents. Today’s agents are largely reactive, acting only when prompted. But over the next 36 months, I expect a fundamental shift. AI agents won’t just follow instructions. They’ll initiate them. They’ll observe, interpret, and act. They’ll carry context across sessions. They’ll spot inconsistencies, recommend solutions, and ask for access when they need it. The result is not just a smarter tool. It’s a semi-autonomous digital co-worker.
If that sounds subtle, it isn’t.
We’ve long designed digital workflows around the idea that tools act on behalf of users. But that assumption is breaking down. In the next phase, AI agents will act on their own behalf, triggering workflows, requesting access, delegating tasks to other agents. Imagine a marketing agent proposing a full-funnel campaign, complete with copy, segmentation, and A/B test logic, without waiting for a prompt. Or an engineering agent that scours bug reports, files JIRA tickets, drafts the fix, and nudges a human engineer only when it’s time to review.
We’ve seen glimpses of this before. RPA (robotic process automation) promised end-to-end execution, but was brittle, procedural, and rarely contextual. AI agents promise the opposite: they are probabilistic, context-sensitive, and task-fluid.
But for that to happen, we’ll need to rethink infrastructure.
Most systems today are built around user identity. That’s fine when the agent is a proxy. But if the agent is autonomous or semi-autonomous, it needs its own identity. That’s not a philosophical debate. It’s an operational necessity. Agents must be able to authenticate, access resources, request permissions, and log actions independently. They must be traceable. Auditable. Accountable.
Consider the distinction:
- An agent acting on behalf of a user is constrained to what the user can access.
- An agent acting on its own behalf requires its own identity, credentials, and governance.
- An agent acting on behalf of another agent implies chains of delegation, trust, and policy.
That’s not science fiction. It’s architecture. And it calls for a radical evolution of identity standards, starting with OAuth and extending into agent-to-agent delegation, permission discovery, and task-based credentialing. The W3C and OpenID communities will need to move faster. Enterprises will need new internal permission models. And users will need ways to understand and control agent behavior, especially when those agents start taking initiative.
Which leads to the real question: What happens when your AI agent asks for permission you haven’t thought to give? Or worse, what if it doesn’t ask at all?
The optimistic view is that autonomy breeds efficiency. The skeptical view is that it also breeds unpredictability. Both are true. The next frontier isn’t just better AI models. It’s systems that allow agents to act independently while remaining visible, explainable, and aligned.
We’re not just building smarter assistants. We’re building something more akin to digital colleagues, and like any team member, they need structure, feedback loops, and boundaries.
We should stop thinking of agents as extensions of ourselves and start treating them like early-stage collaborators. That shift will unlock entirely new workflows, but only if we get the infrastructure right.
What would change if every agent in your stack had its own badge, its own keys, and its own audit trail?
And what happens when those agents start collaborating without us?
