Thank you for joining us
Whether you joined us in Utrecht or are catching up afterwards, here you can find the ideas, conversations and practical examples from Intelligent Enterprise: Live in Utrecht. It was a magical evening, enjoying the company of so many peers that are dealing with similar challenges and opportunities.
Overall the market shows that a lot of companies (85% according to McKinsey research) are focusing on efficiency, whereas only a third of them are having significant impact. Whereas organizations that are using AI to innovate, reinvent the customer experience are seeing a lot more growth.
The central message was clear: The challenge is no longer simply proving that AI can work. It is creating the enterprise conditions that allow it to create value at scale. Three questions sit at the heart of that challenge: how AI changes the experience, whether the data foundations are ready and how humans and AI work together.
On experience, as customer journeys increasingly play out as conversations across channels, owning context — knowing who a customer is and what they need in the moment — is becoming the real differentiator. Keeping humans in the loop, rather than removing them, is what separates organizations that scale AI successfully from those still stuck running pilots.
The conversation between clients Lindsay Brennan (ABB Robotics), Sander van Dongen and David (GrandVision) touched upon a lot of different things. One of them was how Valtech’s research states that trust issues related to the usage of AI are slowing down conversion. The panel discussed how can AI help build confidence and where human experience is needed to explain business value in order to give customers the reassurance to take the next step.
On data, AI-readiness is now a boardroom conversation, not just an IT task. Poor data quality surfaces faster and more visibly once AI is in the mix, which makes the case for fixing foundations easier to make, though the discipline required hasn't got any smaller.
And on people, scaling AI is turning out to be a human and organizational challenge as much as a technical one. The harder work isn't the model but the change management around it. Judgement and so-called "soft skills" are becoming more valuable, not less, as AI takes on more of the routine and repeatable work.
