Intro

I had a fascinating conversation with Dr. Biba Visnjicki, Director Global Digital Transformation, Global Supply Chain at Henkel Consumer Brands, about AI, workforce transformation and the challenges business leaders are facing.

I went into our conversation prepared to discuss how work changes: How do we define value? Which workflows should we redesign? How will roles and coordination evolve? Which capabilities become more important?

Biba was straightforward when I shared with her the four questions I believed every executive should be able to answer. She took a glance and then said, in a very candid tone, "Can I be honest?" And her response was simple:

"There's really only one question that matters, and that question is: How are we going to compete in the future?"

Her reply brought the conversation back to a much more fundamental level, and it was a refreshing one.

Since I believe all leaders should be talking about this, I decided to write down the key learnings I took from our conversation.

I was left with four takeaways that have been on my mind ever since.

1. When a lot is changing, start with strategy

"AI is an incredibly powerful technology, but it is still a technology. Leaders do not wake up worrying about AI. They wake up worrying about growth, margin, stock value, customer value, resilience and competitiveness. AI matters only to the extent that it helps address those priorities."

According to Biba, the job of strategy has not changed: deciding where to play, how to win, what customers value, where your advantage comes from and which capabilities you need to build. What AI changes is the environment in which you make those choices and, quite fundamentally, the means available to you.

We have seen a version of this before. Computers and the internet first made existing activities faster. The bigger impact came later, when they changed the businesses themselves: industries emerged and disappeared, value moved across supply chains, and advantages that had taken decades to build stopped mattering. BCG's recent research shows AI already reshaping profit pools and shifting where value is captured, sometimes before it appears in traditional performance measures.

So the strategic question has to move beyond where can we deploy AI in today's business towards what does AI change about the business itself: where value will move, what becomes commoditised, which sources of advantage get stronger and which get weaker. And when everything else is moving, knowing what will stay valuable gives you something to build around.

That is the strategic work. Not writing an AI strategy alongside the business strategy, but revisiting the business strategy because AI has changed some of the assumptions it was built on.

2. The future isn't siloed. Why should your operating model be?

The challenge is that most organisations still operate in functional silos. Each function owns its own processes, systems and metrics. Customers, meanwhile, experience the business end to end.

AI has the potential to connect those silos, but only when processes, data and decisions are orchestrated across the enterprise. A planning agent might improve demand forecasts. The real value appears when planning, manufacturing, procurement, logistics and customer service work as one connected flow. Technology creates impact when it improves the end-to-end business process, not when it optimises isolated activities.

Biba has seen this pattern from more than one seat. Before Henkel she sat at board level as the technology and digital lead of an international industrial group, and before that founded and ran the first Fraunhofer organisation in the Netherlands, working with manufacturers across Europe on how they build and operate.

"In every one of those businesses, the constraint was almost never the technology. It was whether anyone had the authority to change a process across function boundaries. That is what sets the ceiling, and the speed."

This is why operating model design is becoming a leadership priority. The question is no longer where AI can be deployed. It is how organisations should be structured to enable faster, more integrated and more adaptive business flows.

We are already seeing this reflected in leadership structures. Organisations are creating roles such as Chief Digital Officer, Chief Digital & Transformation Officer, Chief Data Officer and Chief Transformation Officer. The titles differ, but the purpose is similar: executive accountability for enterprise transformation and AI-enabled operating models.

As Biba put it:

"What these roles have in common is not the reporting line. It is that someone holds the mandate to redesign how the business runs end to end."

3. It's okay not to know. It's not okay to ignore it.

This was probably my favourite part of the conversation.

None of us knows exactly what AI will be capable of in three years, which business models will emerge, or where competitive advantage will come from. But uncertainty is not a reason to wait. If anything, it makes leadership more important.

According to Biba, navigating this level of change requires three things: creativity, competency and courage.

Creativity to imagine what the next version of the business could look like. Not just how to improve existing processes, but how to redesign them.

Competency to understand the technologies shaping the future. AI and digital literacy are becoming qualifiers for executive leadership. Leaders do not need to be engineers, but they need to understand enough to ask the right questions, challenge assumptions and make informed decisions.

Courage to act before all the answers are available. Transformation requires investment, experimentation, new capabilities and often entirely new ways of working. It challenges established practice and creates uncertainty. The organisations that come out stronger will not be the ones with the best predictions. They will be the ones willing to move first and learn fastest.

As Biba put it: "Creativity helps you imagine the future. Competency helps you understand it. Courage helps you build it."

She is careful about where that courage has to be tested:

"I ran production before I advised on it. That teaches you something no maturity model can. The design only holds if the people running the line can actually work that way on Monday morning."

4. Be a business partner above all else

This was Biba's advice to us as consultants. It is tempting to enter a conversation with an AI framework, a maturity assessment, a workforce methodology or a catalogue of use cases. But the starting point has to be the business itself.

Our job is to be a trusted partner: bring perspective, ask better questions, challenge assumptions, and help leadership make choices even when the answers aren't obvious.

Then we can talk about workflows, capabilities, governance and operating models.

Take away

I started the conversation with Biba with several questions about AI transformation. I left thinking they all come back to a more fundamental one: how are companies going to compete in the future?

Her own answer points at where the work is going:

"Digital transformation is moving beyond delivering applications, analytics and AI projects. It is becoming the discipline of designing operating models that let the business compete, adapt and create value in a world where AI is embedded in everyday work."

None of us knows exactly where this goes: leaders don't, consultants don't, technology companies don't. Which is why the conversations are worth having.