Your board's AI problem (And it's not what you think)

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Dear Reader, 👋

What if the biggest threat to your company's future isn't your competitors' AI strategy but your board's lack of one?

Flipped.ai's weekly newsletter reaches over 75,000 professionals, innovators, and decision-makers worldwide. This week, we're tackling something that doesn't get enough attention: board-level AI governance.

While 88% of companies are already deploying AI across their operations, a staggering 66% of board directors admit they have "limited to no knowledge" of AI. Even more concerning? Nearly one in three boards don't even discuss AI in their meetings.

This isn't about understanding algorithms or coding it's about understanding how AI fundamentally reshapes competitive dynamics, creates trillion-dollar opportunities, and poses existential risks to unprepared companies.

The gap between AI adoption and AI governance is widening fast. And it's costing companies real money.

Let's dive in! 👇

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Why are 66% of directors dangerously underprepared?

The $trillion wake-up call

Here's the reality: AI isn't just another technology upgrade. It's a general-purpose capability that touches nearly every sector, function, and role. We're talking about fundamental shifts in how companies compete, operate, and grow.

But here's what caught our attention from recent research:

• 88% of organizations are using AI in at least one business function

• Only 39% of Fortune 100 companies have any form of board oversight of AI

• 66% of directors report their boards have limited to no AI knowledge or experience

• Nearly 1 in 3 boards don't even have AI on their agendas

And yet, despite massive AI investments, most companies aren't seeing significant returns. The culprit? A lack of strategic coherence and unclear value dynamics are exactly the issues boards are positioned to solve.

The performance gap

Companies with AI-savvy boards outperform their peers by 10.9 percentage points in return on equity. Those without? They're falling 3.8% below their industry average.

That's not a small difference. That's the difference between leading your market and losing it.

The four AI postures: Which one are you?

Here's something most boards miss: not every company should approach AI the same way.

The key is defining your AI posture how AI fits into your strategic ambition. This clarity gives boards and management a foundation for making critical decisions about strategy, governance, and investment.

Your posture depends on two dimensions:

• Source of value: Will AI expand you into new markets or optimize existing operations?

• Degree of adoption: Will AI be embedded enterprise-wide or applied selectively?

1. The business pioneer

Who they are: AI sits at the center of strategy, driving new offerings and redefining competition.

Real example: A medical device company evolving from selling equipment to delivering AI systems that interpret scans and suggest treatments transforming from manufacturer to healthcare solutions provider.

Board's role: Ensure leadership understands AI's value potential. Scrutinize sustainability, required skills, implications on traditional business, data privacy, cybersecurity, IP protection, and regulatory compliance.

Key questions:

• Which competitive advantages does AI enhance or threaten?

• Does our AI business case target a large enough value pool to reshape our market?

• Do we have the resources, talent, and capital to deliver?

2. The internal transformer

Who they are: AI becomes the backbone of operations, reshaping how the enterprise runs at scale.

Real example: A mining company deploying AI to guide exploration, automate extraction, and optimize refining transforming from labor-intensive to data-driven. Or a media studio embedding AI across production to produce faster, cheaper content.

Board's role: Direct and oversee the rewiring of the operating model across multiple functions. Challenge management to certify that operational gains are structural, not temporary, and that systems are resilient, trackable, and explainable.

Key questions:

• Is AI truly rewiring how we operate or just automating isolated tasks?

• What evidence proves operational changes are structural and sustainable?

• How confident is management in tracking AI-driven cross-functional processes?

3. The functional reinventor

Who they are: AI enhances specific workflows with proven ROI. This is disciplined, targeted investment not wholesale reinvention.

Real example: A healthcare system adopting AI scheduling, transcription, and workforce tools. Or a logistics provider using route optimization and predictive maintenance to cut costs.

Board's role: Focus on scaling for value, securing coherence across initiatives, and mitigating vendor risks. Use real-time dashboards to track outcomes and progress.

Key questions:

• Which high-value workflows benefit most from AI?

• What are the advantages and risks of buying versus building?

• What's our mechanism for scaling promising pilots and defunding weak ones?

4. The pragmatic adopter

Who they are: Fast followers who adopt AI for targeted applications after others prove market traction.

Real example: A consumer goods company waiting for proven e-commerce recommendation tools before adopting them. Or a fashion retailer leveraging AI for clothing rentals and personalized styling only after competitors validate effectiveness.

Board's role: Concentrate on strategic readiness and the risk of inaction. Review market intelligence, competitor moves, and AI evolutions regularly. Establish clear metrics to track competitor AI maturity.

Key questions:

• How are we tracking AI developments among competitors and in adjacent industries?

• Do we have a credible plan to follow fast on proven AI capabilities?

• What are the risks of not pivoting in time?

The 6 actions every board must take

Regardless of your AI posture, here are six critical actions your board should implement:

1. Align on AI posture and review annually (minimum).

This is step one. Without clarity on your posture, nothing else matters. Revisit it regularly as competitive, regulatory, and technological environments evolve.

2. Clarify ownership of AI oversight

Define explicitly:

• Which topics deserve full board discussion (e.g., material enterprise-wide AI investments)

• Which belong in committees (e.g., risk frameworks, vendor reviews)

• Which don't require significant board discussion (regular operational decisions)

Without specificity, accountability breaks down or you waste precious agenda time.

3. Codify a framework for AI governance policy

Most companies draft principles, but fewer than 25% have board-approved, structured AI policies. Your framework should specify:

• Scaling rules: When pilots earn capital for enterprise-wide deployment

• Risk thresholds: Where human sign-off is necessary and what guardrails exist

• Vendor/data guardrails: IP protections, third-party audit rights, security standards

• Escalation triggers: What incidents reach the board and how fast

4. Engage more broadly (and frequently) with doers.

Don't only talk to CEOs and CFOs. Regularly interact with chief data officers, analytics leaders, and business unit heads who are actually embedding AI into operations. Get a real understanding of progress and competitive impact.

5. Tie AI investment to business value

Only 15% of boards currently receive AI-related metrics. You need visibility into:

• ROI by business unit

• Percentage of AI-enabled processes

• Resilience indicators (override rates, backup drill results)

• Workforce reskilling progress

• Regulatory alignment

This reframes AI oversight the same way you approach capital allocation and risk reviews.

6. Build AI fluency

Directors don't need to be data scientists, but you need sufficient understanding of how AI creates opportunities and risks for your business. Build this through:

• Ongoing education and regular briefings

• External trainings and advisory panels

• Personal use of AI tools (for meeting prep, document analysis, etc.)

• Input from external experts on emerging technologies and regulations

The real cost of inaction

Here's what keeps us up at night: AI adoption hasn't yet led to significantly improved performance for most businesses. Companies report only modest savings and new revenue.

But here's the twist: many of these disappointing outcomes stem from issues boards are perfectly positioned to solve:

• Lack of strategic coherence

• Unclear value dynamics

• Misalignment between ambition and execution

• Insufficient risk frameworks

• Poor resource allocation

The rules, risks, and expectations around AI are evolving rapidly. Boards can't assume today's practices are sufficient for tomorrow's challenges.

AI is closer to a reckoning than a trend. With trillions of dollars potentially at play and implications that could be existential to companies, this is unequivocally a board-level priority.

The competitive dynamics are shifting now. The winners will be companies whose boards can:

• Provide strategic direction aligned with AI's transformative potential

• Ask the right questions at the right time

• Help leadership navigate both massive opportunities and material risks

• Build governance models that match their AI ambitions

The question isn't whether AI will transform your industry.

The question is whether your board will lead through it or be left behind.

Want to explore more? Read the full article here.

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Team Flipped.ai