AI in the Boadroom : Choosing the Use Case That Actually Matters
Introduction: The Pressure to Act, The Risk of Acting Blindly
Across industries, boardrooms are abuzz with the same question: What are we doing about AI?
The pressure to respond is real—from shareholders, employees, customers, and competitors. But in the race to say something intelligent about AI, many leadership teams default to superficial pilots, fragmented tools, or trendy use cases that don’t tie back to core strategy.
In the boardroom, the real AI question isn’t "What can we do?" It's: "What matters most for us?"
This article explores how boards and executive teams can focus their AI attention where it counts—not in theory, but in enterprise value.
The Illusion of Action
The biggest risk in AI isn’t inaction. It’s misdirected action.
Too many organizations confuse movement with momentum:
Running disconnected AI pilots in siloed functions
Launching initiatives driven by vendor capability, not business priority
Approving use cases because they seem "innovative"
Measuring success with vanity metrics like model accuracy or chatbot usage
These moves might satisfy a board report or PR release, but they rarely move the business.
AI needs to be aligned with business tension, not just technological potential.
Ground AI in the Strategic Agenda
Before choosing a use case, boards must clarify where the business is trying to shift.
Ask:
What are the 2-3 enterprise-level shifts we must drive over the next 18 months?
Where are we constrained—in time, cost, growth, insight, or resilience?
What outcomes would change the game for our competitiveness?
AI is not a strategy. But it can be a lever for accelerating one.
If a use case doesn’t serve a strategic shift, it’s a distraction.
Define What "Value" Looks Like First
Not all use cases deliver the same kind of value.
Boards should push executives to define the dominant value lens:
Efficiency: Where can AI reduce effort, time, or cost?
Effectiveness: Where can AI improve decision quality or consistency?
Experience: Where can AI enhance employee or customer journeys?
Exploration: Where can AI reveal patterns, options, or signals we can’t yet see?
Each lens suggests different metrics, risks, and operating models.
Choose a use case that creates visible value—not just internal interest.
Evaluate Use Cases Like a Portfolio
Treat AI use case selection like capital allocation.
The best boards evaluate use cases on dimensions like:
Strategic alignment: Does this reinforce a priority?
Feasibility: Do we have the data, talent, and process maturity to execute?
Scalability: Can this use case expand across units or functions?
Signal strength: Will this pilot generate learnings we can use elsewhere?
Use cases should be:
Few enough to focus
Bold enough to matter
Diverse enough to learn
AI maturity comes from use case discipline, not experimentation alone.
Start With a Problem Worth Solving
Rather than asking "Where can we apply AI?" ask:
What is a problem we haven’t been able to solve with existing tools?
Where do we have data but lack insight?
What decision or process is too slow, inconsistent, or manual?
The best use cases emerge from pain, not possibility.
AI should be a wedge into challenges we already know exist, not a search for novelty.
Elevate AI Literacy Without Becoming Technical
Boards don’t need to become experts in AI architecture. But they do need to ask better questions.
Focus boardroom dialogue on:
Assumptions: What data and conditions does this model depend on?
Risks: What are the ethical, reputational, or compliance implications?
Outcomes: What business value do we expect to see—and how soon?
Ownership: Who is accountable for delivery and governance?
Good questions matter more than technical fluency.
Use the First Use Case to Build a System, Not a Success Story
The first AI use case matters less for what it does, and more for what it sets in motion.
Select a use case that allows you to:
Establish governance
Build cross-functional muscle
Test new workflows and incentives
Create repeatable patterns and templates
Think of it as a systems catalyst—a way to operationalize the infrastructure, not just a proof of concept.
Track Momentum, Not Just Metrics
Don’t wait for perfect ROI. Instead, look for early signals:
Have we made a real decision or investment shift because of this use case?
Is the learning from this pilot informing others?
Are our teams asking better questions and spotting new opportunities?
Is the use case building momentum in other parts of the business?
If nothing else is moving, it wasn’t the right use case.
Conclusion: Clarity Before Capability
AI will shape the future of every business. But not every AI initiative will shape the future of yours.
Boards have a unique role to play: not in choosing tools, but in clarifying what really matters.
The right use case isn’t the most impressive. It’s the one that unlocks belief, energy, and strategic advantage.
Don’t chase AI potential. Choose AI direction.
That’s what belongs in the boardroom.
