The Intent Gap: Why AI Must Do More Than Just Respond

A prompt is not a strategy. Yet most AI systems today are designed to wait: wait for instructions, wait for input, wait for someone to tell them what to do next. This creates a bottleneck. Not of compute power, but of human bandwidth.

The real opportunity isn’t in faster response. It’s in eliminating the need for constant supervision.

Agentic systems close what we call the intent gap — the space between a business objective and the execution steps required to deliver it. Instead of asking a human to frame, scope, trigger, and follow through, agentic AI reads signals, interprets context, and initiates workflows toward a defined outcome.

This shift changes how we think about work. It moves AI from being a tool you operate to a system that co-operates — continuously. A campaign agent doesn’t wait for a content brief. It reads CRM activity, drafts the outreach, schedules the message, and flags any blockers. Not reactively, but proactively.

But this only works if intent is well-defined. Ambiguity kills agency. The system needs a clear goal, access to relevant data, and permission to act. Without this clarity, it either stalls or overreaches — both of which destroy trust.

To operationalise agency, you need to design around intent: What outcome are we driving? Who should be informed? Where does this action sit in the broader system?

Agentic AI is not about outsourcing judgement. It’s about removing the manual translation layer between intent and action — and freeing your best people to work on the parts machines will never own.