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The most interesting thing about AI this week has not really been AI

From this week's reflections — the difference between sending a message and creating a recipient, and why digital transformation is decided in the translation from strategy to everyday work.

The most interesting thing about AI this week has not really been AI

I have been at several professional events and had good conversations with people working closely on digitalisation and transformation.

Across organisations, industries and maturity levels, one challenge keeps coming up:

There is a big difference between sending a message and creating a recipient.

Leadership may have understood why the organisation must change. The strategy may be sound. The tools may be available. The data may be ready.

But if the people who are supposed to use them do not understand why, see the relevance in their own everyday work or get the opportunity to practise new ways of working, little happens.

Perhaps that is where much digital transformation is decided. Not in the technology, but in the translation.

🔸 From strategy to everyday work.
🔸 From data to decision.
🔸 From training to skill.
🔸 From AI tools to a work process that is better than the old one.

I know this well from commercial leadership. It helps little that the CRM shows where the opportunities lie if customer prioritisation does not change. And it helps little that sales see one picture and operations another if no one builds the bridge between them.

AI makes this even clearer.

We can get better decision support, faster insight and entirely new ways to train, simulate and solve tasks. But the value only comes when we also dare to redesign how the work is performed.

McKinsey & Company points out that change leadership and silos are greater barriers to scaling AI than technological infrastructure.

Boston Consulting Group (BCG) shows at the same time that only 28 per cent of frontline employees experience a strong connection between what leadership says about AI and what the organisation actually does.

It is a leadership problem before it is a technology problem.

Sources

McKinsey & Company, How to close the agentic adoption gap, 7 August 2026. McKinsey shows among other things that change leadership and silos are seen as greater obstacles to scaling AI than technological infrastructure.

Boston Consulting Group, AI at Work: Why Strategy Matters More Than Tools, 3 June 2026. BCG's global survey among nearly 12,000 leaders, middle managers and employees shows among other things that only 28% of frontline employees see a strong connection between what leadership communicates about AI and what the organisation does in practice.

👉 What do you think we need to change in the way we lead, collaborate and work for technology to create value?

#DigitalTransformation #Leadership #AI #ChangeLeadership #Execution

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