Foundational Ideas for Operational Leaders in the Age of AI
At the center of this series is a hopeful idea: AI can give people time back, expand what one person can build, and make new forms of contribution possible. The challenge is to realize that promise without losing the judgment, relationships, context, and learning through which people and organizations become more capable.
I wrote these pieces to help leaders navigate that tension. Each one stands on its own, but together they explore a series of questions leaders are likely to encounter as AI changes work. Start with the question closest to the decision in front of you, or read them in order to follow the progression from the economics of AI-enabled work to modes of use, organizational change, judgment and fit, and human learning.
Choose your starting point.
When AI makes work easier to produce
Keeping Humans Centered in How We Build and Decide
AI can return time and expand what one person can build, but it can also bypass the alignment, context, and learning the work still needs.
Read this if you are asking: “How can leaders keep AI-enabled work human-centered?”
Start with the economics of AI-enabled work.What role is AI playing in the work?
A Better Question Than “Are We Using AI?”
Before deciding how much review or responsibility the work needs, distinguish whether AI is helping people know, do, or figure out what comes next.
Read this if you are asking: “What role is AI playing in this work?”
Understand the three modes of AI-supported work.What kind of organizational change are we pursuing?
Improve. Redesign. Reimagine.
“Use AI” is not a strategy. This framework helps leaders distinguish improving familiar work, redesigning a workflow, and making a new kind or scale of impact possible.
Read this if you are asking: “How do I align AI initiatives with my organization’s priorities?”
Map the change you intend to create.Does the answer actually fit our organization?
The Most Likely Answer Is Not Always the Right One
A polished AI response can be common or broadly recommended without being appropriate for your audience, relationships, constraints, and intended outcome.
Read this if you are asking: “How do I ensure AI outputs fit my organization’s context and needs?”
Test a plausible answer against context and fit.Who develops when AI does more of the work?
Who Learns When AI Does the Work?Coming soon
Work produces an artifact while developing knowledge, judgment, confidence, and readiness. This next piece asks what people and organizations may lose when AI produces the visible output.
The question it will explore: “How can AI increase capacity without weakening the learning that makes people and organizations more capable?”
These connected ideas do not form a maturity model. An organization may work across all five at once.
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