A Fortune 500 CEO recently told me, “We don’t have an AI strategy. We have 47 of them.”
The CTO is rolling out copilots. The CHRO is scaling a skills academy. The CMO is testing generative content. Every function is sprinting. But not together.
There are strategy decks. There are AI councils. There are task forces. But when I asked, “What are we solving for?” the room went quiet.
No one had a clear answer. And that’s the point.
This is what AI transformation looks like when intent outpaces integration: high activity and low alignment, all wrapped in a false sense of progress.
Jim Collins calls this the “undisciplined pursuit of more.” More pilots and tools, but less clarity and cohesion, and ultimately, less value.
Effective leadership teams move together with purpose, ownership and a shared agenda.
Yet, that's where so many teams stall because everyone is waiting for someone else to define the mandate.
The silent killer of AI ROI is misalignment. And it's exactly what we're unpacking in this edition.
SUMMARY
Trends: Impact of misalignment in AI transformation
Tips: How to shift from isolated to shared mandates
Tools: AI tools and brief for leadership teams
TRENDS
Only 28% of executives say their leadership team is aligned on AI strategy (McKinsey, 2024). That misalignment is showing up in three costly ways:
- Redundant spend: Multiple AI tools solving the same problem
- Competing agendas: Functions optimizing for local gains, not enterprise value
- Slow scale: Pilots succeed but never integrate
AI is moving faster than leadership teams. Each functional leader has good intent. But without a shared transformation mandate, good intent fragments execution.
What’s at stake?
ROI, trust, and competitive advantage.
TIPS
1) Misalignment is not a people problem
The old model was letting each function lead their own technology initiative. The new model is establishing an enterprise AI mandate with aligned success metrics. Apply the right model and the people will be aligned.
Use a single-page “Enterprise Value from AI” scorecard and tie every AI initiative to one of three business outcomes:
- Productivity gain
- Speed-to-value
- Net-new revenue
2) Define shared success before deploying new tools
Before greenlighting another pilot, ask:
- How does this reduce cost, increase revenue, or save time
- What will “good” look like in 30, 60, and 90 days?
- Can we scale this learning or is it a dead-end experiment?
3) Appoint a single AI integration owner
AI integration must be owned by a single leader to ensure execution discipline, ideally the COO. Reinvention scales through coherence and accountability, not consensus.
TOOLS
Pressure-test executive alignment with this brief:
- What is our enterprise-wide outcome from AI?
- How will each function contribute to that outcome?
- What capabilities are we building and what are the gaps?
- What does success look like in 6, 12, and 24 months?
- What risks are we willing to take and which are non-negotiable?
- How are we resourcing this (budget, talent, tools)?
- Who’s the integrator?
AI Tool: Try WorkBoard AI to cascade shared objectives across transformation leaders and track results in real time.
What will move your team from inertia to aligned action?
Until next time...stay curious!
Cheers,
Nikki
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