It’s not about automation. It’s about reshaping how work gets done.

That was the starting point at The Intelligent Enterprise: Live in Utrecht, where leaders from ABB Robotics, GrandVision and Contentful joined us for a keynote, a panel, a fireside chat and hands-on demos.  

The central theme of the evening: The challenge is no longer in proving that AI can work. It’s in creating the enterprise conditions for AI to create value at scale. 

What we discussed in Utrecht 

Three questions sat at the heart of the evening:

• How does AI change the way customers find, choose and buy? As journeys play out as conversations across channels, owning context — that is, knowing who a customer is and what they need in the moment — is becoming the real differentiator. 
• Are data foundations ready? AI-readiness is now a boardroom conversation, not just an IT task.
• How do humans and AI work together? Scaling AI is as much a human and organizational challenge as a technical one, and judgement is becoming more valuable.

Efficiency is the starting point 

John Cunningham, Valtech's Global Chief Technology Officer, opened with what he called the pressure gap: Executive teams expect AI to deliver both acceleration and efficiency, which is how organizations end up with death by a thousand pilots.  

His answer: Transform what you already have. Even heavily customized, monolithic platforms can often be extended with generative AI, automation or machine learning without starting over.  

One real-world example is a run-and-support agent that investigates stalled orders and, once a human approves, unblocks them across systems. For the client, that meant 50% higher deployment velocity, 40% faster mean time to recovery and projected savings of $20 million over three years.  

But efficiency alone is a race to parity. Eighty percent of companies use AI primarily to cut cost. The bigger gains come where AI reshapes customer-centric workflows, journeys and decisioning — what we call orchestrating around the experience. 

Turning new capacity into growth 

John's challenge to the room: What if human and agent workflows didn't just drive efficiency, but accelerated growth and elevated the brand?  

Take one fashion and homewares retailer. New products arrive with few attributes, yet every page needs a description. Valtech developed a process to generatively enrich the copy with lifestyle attributes and optimize the copy for search and LLM discoverability. What used to be a day’s work takes just 30 minutes now, freeing the team responsible to focus on larger brand challenges. 

Brand content is harder. Out-of-the-box models get you 80% of the way, but the last 20% — your logo, your product — is where trust is won. That takes orchestrated workflows across several models, the thinking behind Cre8, Valtech's approach to AI-driven creative production, which encodes brand guidelines into every asset. In the room, visual layering turned functional images into lifestyle photography. 

Opening new doors for customers

David Toma, VP Strategy and Consulting at Valtech, hosted a panel with Lindsay Brennan of ABB Robotics and Sander van Dongen of GrandVision on how AI is changing customer expectations, and how organizations are adapting.  

His opening study insights set the scene:

• 72% of consumers would consider completing a full purchase inside an AI chat, and 94% already use AI chat regularly.
• 32% prefer to start in AI chat apps when they need help shopping or getting support. 
• 41% would use an official brand AI agent inside their chat app, and 20% would switch brands or abandon a task if a brand doesn't offer one.  
• Trust is the biggest constraint: 52% are held back by payment security concerns. 
• 45% say brand websites feel advanced but not conversational, and only 5% experience state-of-the-art AI assistants. 

The panel explored trust in depth: how AI can build customer confidence, and where human experience is still needed to explain business value and reassure customers before their next step. 

The experiences that meet customer demand today

John cautioned the audience that websites aren't going away. What changes is how people interact with brands. His Tenor framework argues that as software moves from tool to agent, the brand moves from surface to conduct.  

Valtech Concierge puts this into practice by separating the conversation, orchestration and model layers so brands can trial conversational experiences on their existing commerce platforms using content they already publish, such as SEO catalogue exports.  

For one automotive client, a vehicle launch followed a five-step loop: capture intent signals, predict the customer's need state, assemble the experience, render it, then learn from the response. The results: 41% more vehicle configuration completions, 190% more lead conversions and 274% more call-to-action clicks.