From the Engine Room to the Value Machine: How Leaders Can Unlock AI’s True Potential

By John Kårikstad, Group CEO, Forte Digital

AI is no longer a side project

Artificial intelligence is moving fast, much faster than most leadership teams anticipated. New models are released monthly, and breakthroughs happen almost daily. What was once a futuristic discussion in innovation labs is now a boardroom agenda item.

According to Forte Pulse 2025 (in Norwegian), eight out of ten companies in Northern Europe have integrated digital transformation into their core business strategy. Yet, 93% have not successfully integrated AI into their operations, and in more than a third of organizations, ownership of AI still sits within IT.

This gap between ambition and impact is widening. The companies that win with AI are not necessarily the ones with the most data or the latest tools. They are the ones that treat AI as a strategic growth driver, not a technical experiment.

Why leadership ownership matters

When AI is owned by IT, it’s seen as a cost center, something to automate processes or reduce manual work. When AI is owned by the CEO and the board, it becomes a value creator.

Leadership ownership changes three things:

1. The questions being asked Instead of “Which tools should we use?”, leaders start asking, “Which customer experiences can we redesign?” or “How can we use AI to grow revenue?”
   

2. The metrics that matter KPIs shift from model accuracy or infrastructure uptime to tangible business outcomes: growth, customer satisfaction, and innovation speed.
   

3. The willingness to scale Leadership involvement breaks the pilot trap. Successful ideas are funded, integrated, and scaled, not left as isolated proofs of concept.

From hype to structure

Many leaders still feel that AI is overwhelming, complex, fast-moving, and filled with buzzwords. The pragmatic answer is not to chase every new model or trend. It’s to build structure around experimentation.

At Forte, we often say that AI doesn’t fail because of technology; it fails because of structure. Without clear ownership, defined goals, and a business-aligned roadmap, even the most promising initiatives lose momentum.

A practical starting point is to establish an AI governance framework anchored in leadership:

• Create an AI committee within the board or leadership team that tracks progress and business impact, not just technical deployment.

• Appoint a C-level AI owner, such as a Chief AI Officer or a senior leader with a cross-functional mandate.

• Align KPIs with strategy, linking AI metrics to growth, retention, and efficiency, not model performance alone.

• Run annual AI strategy sessions at board level to review how technology developments impact the company’s strategic direction.

These are small, structural decisions that send a strong signal: AI is part of how we lead, not just how we operate.

Culture beats code

No matter how sophisticated your models are, AI will fail in a rigid organization. Companies that succeed with AI have one thing in common: they treat it as a cultural transformation, not a technical one.

A culture that enables AI success is built on three elements:

• Cross-functional collaboration: Business, technology, and design teams work side by side, not in silos.

• Psychological safety to experiment: Teams are encouraged to test, fail, and learn quickly.

• Clear accountability: Every AI initiative has a defined owner, objective, and timeline.

When leadership creates this environment, AI becomes part of everyday problem-solving, not a distant innovation project. It’s the difference between a company that experiments with AI and one that runs on it.

From efficiency to innovation

Most companies begin their AI journey with efficiency goals, automating processes, reducing costs, improving productivity. That’s a natural start, but it’s not where the true potential lies.

The real value of AI emerges when it becomes a platform for innovation, enabling new services, experiences, and business models.

Three questions every leader should ask

As AI moves from the engine room to the core of the business, leaders should ask themselves three simple, strategic questions:

1. Is AI owned by the leadership team or buried in IT? Ownership defines impact.
   

2. Are our AI goals linked to business outcomes, not technology outputs? Strategy without metrics is just ambition.
   

3. Do we see AI as a tool for growth — or just for savings? Efficiency is the beginning, not the end.

The Scandinavian approach: Pragmatism over hype

In the Nordics, we value simplicity, structure, and substance over show. That mindset applies perfectly to AI. Success doesn’t come from adopting the flashiest models or hiring armies of data scientists. It comes from clarity of purpose, trust in collaboration, and the discipline to turn strategy into action.

AI is no longer an experimental technology; it’s a strategic capability. The question is no longer if your business will use it, but how fast you’ll make it part of your value machine.

About the author John Kårikstad is Group CEO of Forte. He advises executives across Europe on digital transformation and AI strategy, helping organizations move from experimentation to scalable value creation.