Teach Your AI How You Make Decisions

2026-06-25 · Source: Feeds - HBR.org · Field: Business & Management — Corporate Strategy & Leadership, Operations & Process Management, Human Resources & Workforce Development · Depth: Intermediate, long

Summary

Published on June 25, 2026, by Jen Stave, Ryan Kurt, and John Winsor, this article argues that the main bottleneck in scaling AI agents is an organization's capacity to explicitly define its decision-making processes, not technology access. It proposes building "judgment infrastructure" through three shifts: collaborative governance by business units, HR, and IT; managers becoming "judgment architects" who codify expertise (e.g., Debbie Riazzi at AWP Safety, Nathan Mapp with Claude and Claude Code); and fostering "thought-doers" who operationalize thinking via agents (e.g., Ramp, which equips 30,000 companies with ChatGPT Enterprise, Notion, and Perplexity). The authors suggest codifying judgment by convening expert panels to discuss scenarios, capturing nuanced reasoning in transcripts. This makes institutional knowledge portable, yielding faster decisions and consistent quality, as shown by ITA Group.

Key takeaway

For Directors of AI/ML or VPs of Engineering aiming to scale AI agent deployments, your focus must shift from technology access to explicitly codifying organizational judgment. You should establish cross-functional governance involving business units, HR, and IT, treating agents as operational contributors. Empower your managers to become "judgment architects" by translating tacit expertise into structured guidance. This approach will make institutional knowledge portable, accelerating decisions and enhancing quality across your organization.

Key insights

The bottleneck in scaling AI agents is codifying tacit organizational judgment into explicit guidance.

Principles

• Explicitly codify tacit organizational judgment.
• Govern digital labor collaboratively across functions.
• Managers must operationalize expertise for AI.

Method

Convene a small panel of experienced practitioners in the same role with a skilled moderator to discuss realistic scenarios and edge cases. The transcript of this conversation becomes the first draft of codified judgment.

In practice

• Convene expert panels to externalize decision logic.
• Empower employees to build and refine AI agents.
• Establish cross-functional AI governance.

Topics

• Generative AI
• AI Agents
• Organizational Decision Making
• Tacit Knowledge Codification
• Judgment Infrastructure
• Workforce Strategy

Best for: CTO, Executive, AI Product Manager, Director of AI/ML, VP of Engineering/Data, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by Feeds - HBR.org.