Industry: Aerospace / engineering-driven organization
Function focus: Executive leadership team

Context

Executives were enthusiastic about AI — but each function had a different interpretation of what AI should achieve.
For some, AI meant automation.
For others, decision support.
For others, innovation branding.

Discussions stayed abstract and hype-driven.
No shared view existed on risks, data readiness, or where AI should actually change decisions.

Challenge

• Misaligned leadership expectations
• No shared language for AI value
• No prioritization of decision-critical use cases
• Unclear governance responsibilities
• Low readiness to move from experimentation to execution

Approach

• Create shared leadership understanding of what AI is (and isn’t)
• Map real decision and workflow bottlenecks
• Identify 2–4 prioritized use cases tied to business outcomes
• Clarify ownership across business, data, IT, and compliance
• Define a 90-day execution roadmap linked to leadership routines

Outcome

• Leadership alignment on where AI creates real value
• Shift from abstract ambition to concrete execution priorities
• Clear ownership and governance expectations
• Momentum to move from pilots to operational integration

Leadership Insight

Alignment beats enthusiasm.
AI moves only when leaders share a concrete operating model for how decisions change.