AI as an accelerator of premium experiences beyond the pixels

There is a lot of discussion today about what artificial intelligence will do to design. Will it generate interfaces? Replace production work? Make design faster, cheaper and more automated?

These are valid questions, but they only describe part of the opportunity. The more important question is not whether AI can help us produce more. It is whether AI can help us spend more time designing better experiences.

Great product experiences are shaped by user needs, product understanding, brand expression, technical realities, business goals and design judgement. AI can help us connect these inputs into something coherent and meaningful for the customers we serve.

Designers spend a considerable amount of time on production work: creating concept material, adjusting details, documenting decisions, preparing presentations and checking consistency across touchpoints.

This work matters. But it can take time away from the questions where design creates the most value: what the user is trying to achieve, where the journey breaks down, what the experience should feel like, and which decision creates the most value.

AI can help reduce time spent on repetitive tasks. But the goal should not only be faster delivery. The goal should be better focus.

When AI supports production, synthesis or documentation, designers can spend more time understanding context, framing problems, evaluating trade-offs and making quality visible.

In my experience working in large organisations, a lot of design knowledge already exists. Quality standards, brand guidance, design principles, product information, accessibility requirements, research insights and previous decisions are often available somewhere.

The challenge is that this knowledge is spread across systems, documents, teams and formats. It can be difficult to find, interpret and apply consistently. This creates friction and inconsistency.

AI gives us an opportunity to make this knowledge easier to access and apply. Not by replacing the guidance itself, but by helping people navigate it, ask better questions and understand what the guidance means in their context.

At Scania, we are exploring this in different ways, from content migration to advisory guidance around digital experience. Some initiatives take the form of agents that help teams understand what good looks like and how a concept aligns with our design and brand expectations.

The results are not perfect. Precision, context and input quality still matter. But the direction is promising: AI can make design knowledge more available and invite more people into informed discussions about quality.

AI can support this by making it easier to explore, compare and critique ideas earlier. A team can generate alternative directions faster, pressure-test a concept against principles, user needs or brand attributes, and turn abstract guidance into concrete questions.

This does not remove the need for designers. In many ways, it raises the importance of design judgement. When AI helps create more possibilities, the critical question becomes: which of these possibilities are actually good?

That is where designers need to be even more present: helping teams understand trade-offs, connect signals, challenge assumptions and keep the user perspective alive.

This is especially important at Scania. Our digital experiences are connected to operational needs, technical ecosystems, vehicle platforms, services, data, business models and customer expectations. The experience does not live only on the screen. It lives in the relationship between the customer, the product, the service and the brand over time.

Digital design is often associated with screens: layouts, flows, components, prototypes and visual details. These are important. They are the visible layer of the experience.

But the quality of an experience is often decided before the interface is produced. It is decided in how we frame the problem, understand the user, prioritise needs, align stakeholders, interpret technical constraints, translate brand into behaviour, measure impact and decide what not to build.

AI can help designers move more confidently into these spaces. It can support research synthesis, scenario exploration, journey analysis, content clarity, service logic, design critique and decision framing.

It is tempting to think that if AI can generate options quickly, quality will automatically improve. I do not think that is true.

AI can accelerate the process, but it cannot define what premium means for Scania. It cannot fully understand our customers, strategy, brand, constraints or ambitions without human direction.

For Scania, premium is not only about how something looks. It is about reliability, clarity, confidence and value across the full customer experience. Premium experience requires judgement, empathy, restraint and the ability to make decisions in ambiguity.

AI can reveal patterns, suggest alternatives, challenge our first ideas, make knowledge easier to access and reduce repetitive work. But the responsibility for quality remains with us.

From our journey at Scania, I see artificial intelligence less as a tool for automation and more as a new layer in design practice.

A layer that can strengthen critical thinking. A layer that can make knowledge easier to access. A layer that can support more consistent ways of working. A layer that can bring more people into meaningful conversations about experience quality.

We are still early in this journey. There are open questions around accuracy, governance, trust, integration and responsible use in real product development. But the direction is clear.

If we use artificial intelligence only to generate more interface variations, we will miss the bigger opportunity. The bigger opportunity is to expand the influence of design: to connect user needs, technical inputs, brand expectations and business goals into more coherent solutions.

Artificial intelligence will not create premium experiences by itself. Used well, it can help design teams raise the quality of their thinking, their decisions and their collaboration. And that is where its real potential begins.