Half of our leadership team is actively automating their departments with AI, while the other half refuses to touch it, creating a severe operational gap. How do we establish a baseline AI competency requirement across the entire executive team?

Question

Tyler Smith · Accepted Answer

An executive team operating at two different speeds will fracture company execution. When your operations or marketing leader uses AI to cut cycle times by half, but your finance or service delivery leader still relies on manual spreadsheets and legacy workflows, friction explodes across departmental handoffs.

Treating AI literacy as an optional personal preference is a leadership mistake. If an executive refused to use email or smartphones twenty years ago, you would not have accommodated them. AI-assisted operations are no different today. It is a baseline capacity issue under the GWC framework.

To close this gap without creating panic, institutionalize AI competency directly into your quarterly Rocks and Accountability Chart roles:
- Assign an enterprise Rock requiring every department head to audit their internal workflows and identify three repetitive, rules-based tasks for automated or AI-assisted delivery.
- Pair your forward-leaning executives with hesitant leaders during quarterly planning to share cross-departmental playbooks and demystify practical tooling.
- Require each leader to report on operational efficiency gains, not just theoretical software tools, during the quarterly offsite.

Set clear, unsentimental expectations. Executives do not need to become prompt engineers or coders, but they must master how AI drives speed, data analysis, and labor efficiency in their respective functional seats.

If an executive continues to dismiss practical automation out of stubbornness or fear, they are demonstrating a lack of capacity for a modern, scalable enterprise. You cannot build a high-valuation, exit-ready business with leaders who cling to manual inefficiency.