You’re Doing Agents All Wrong – Why You Should Focus on Human Attention

Why It Matters

By redirecting AI from incremental efficiency gains to scaling human attention, firms can unlock economic value in previously unaddressable problem spaces. This reframes AI ROI and reshapes enterprise operating models.

Key Takeaways

• Agents shift focus from automation to human attention
• Economic value emerges by covering organizational whitespace
• Scalable agents surface risk drift for timely expert review
• Human judgment remains critical; agents act as sense‑makers
• Attention‑as‑a‑service model redefines AI ROI

Pulse Analysis

Enterprises have long equated AI agents with the next wave of workflow automation, extending existing process‑centric tools to squeeze incremental efficiency. Anderson challenges that narrative, proposing instead that agents serve as attention‑amplifiers, surfacing the gaps where human judgment is too costly to apply at scale. This attention‑economics lens moves the conversation from technical architecture to economic impact, urging leaders to look beyond standardization and consider how AI can illuminate organizational whitespace that has resisted optimization.

A concrete illustration comes from a major insurance firm struggling with divergent risk‑control policies across business units. Traditional audits were infrequent and expensive, leaving the central risk team blind to drift. By deploying an agent that ingests, compares, and flags policy deviations, the insurer reduced weeks of manual review to minutes, allowing experts to focus on high‑impact decisions. The agent does not replace judgment; it merely performs the grunt work of data synthesis, turning previously invisible risk exposure into actionable insight and delivering measurable cost savings.

The broader implication is a shift toward an "attention‑as‑a‑service" model, where AI’s primary value lies in filtering and prioritizing information for human experts. This reframes AI ROI from pure labor substitution to leverage amplification, prompting organizations to redesign operating models around continuous, AI‑driven monitoring rather than periodic automation projects. While autonomy remains a secondary concern, the strategic advantage of directing scarce human focus to the right problems promises a new frontier for enterprise AI adoption.