Sprint scenario

Across banking, AI is moving from isolated experimentation into everyday operations. New tools and initiatives are emerging across customer service, marketing, risk, technology, HR and communications. But as activity accelerates, another challenge appears: more AI initiatives do not necessarily add up to an AI transformation.

A Nordic bank is running multiple AI projects across the organization. Some are already creating value, others remain experimental, and different functions describe progress in very different ways. There is plenty of activity—but no shared picture of what it means at enterprise level.

Ahead of an upcoming board discussion, the CEO asks a deceptively simple question: Where are we really in our AI transformation?

The challenge is not to catalogue every AI initiative, but to turn fragmented activity into a credible picture of enterprise maturity and direction.

Meet Clara

Clara is one of the fictional archetypes in the AI Business Council, representing a corporate communications leader navigating complex stakeholder environments. Her challenge provides the starting point for this AIBC Lab sprint.

The challenge

Turn fragmented AI initiatives into one clear direction

Find the opportunity

What does progress actually look like?

We start by bringing together what the bank already knows.

Across functions, 27 ongoing AI initiatives are identified. Some are early experiments. Others are already improving existing processes, decisions or customer interactions. Each makes sense in its own context, but together they are difficult to compare.

We combine the internal picture with AI-powered market intelligence and use an established AI maturity framework to explore the initiatives through a common lens—looking at business value, technology, data, governance, capabilities and ways of working.

A pattern begins to emerge.

The bank doesn't have an AI activity problem. It has a connection problem.

Much of the activity remains concentrated around experimentation and improving existing work. A smaller number of initiatives are beginning to change how work gets done or how value is created. But very few yet connect capabilities across the organization in a way that could be described as enterprise transformation.

That gives us the opportunity to take forward: Could the initiatives be turned into one shared picture of how AI is changing the bank?

Bring the direction to life

What would transformation actually look like?

We turn the fragmented activity into an AI Transformation Map.

Rather than ranking projects by how advanced their technology appears, the map explores what each initiative is actually changing. The 27 initiatives begin to form a progression: Experiment → Improve → Change → Transform.

Some initiatives are helping the bank learn. Others make existing work more efficient. A smaller number are beginning to change how decisions are made, how employees work or how customers experience the bank.

Common patterns begin to surface. The initiatives with greater transformational potential don't depend on technology alone. They connect business value with data, governance, capabilities, ownership and new ways of working.

The map now makes something previously difficult to see tangible:

27 AI initiatives are not the same thing as one AI transformation.

Prepare the next move

What should leadership align around now?

The AI Transformation Map gives leadership a shared view of where the bank stands today: where experimentation is producing learning, where AI is already improving existing operations and where early signs of more fundamental change are emerging.

But it also reveals what is preventing individual successes from becoming enterprise capabilities.

We identify the recurring gaps and dependencies across the strongest initiatives and explore where greater coordination, shared capabilities or clearer ownership could allow the bank to build on what is already working.

The objective isn't to create another catalogue of AI projects or a complete transformation strategy in one week. It is to give leadership a common way of seeing the transformation and a clearer basis for deciding where to focus next.

The CEO can now enter the board discussion with a much stronger answer: We have 27 AI initiatives. Here is what they are changing, where transformation is beginning to emerge—and what we need to connect if we want to start moving as one bank.

Potential sprint outcome

AI Transformation Map
A visual mapping of the initiatives, showing how activity progresses from experimentation and improvement towards organizational change and transformation.

Enterprise Opportunity
A clearer view of the initiatives showing the strongest transformational potential and the capabilities, dependencies and patterns they have in common.

New Title

Leadership Direction
A focused recommendation on what the bank should connect, strengthen or align next to turn fragmented AI activity into greater enterprise impact.

More sprint challenges