IKEA Retail (Ingka Group), the largest IKEA franchise, is operating most IKEA stores worldwide while also investing in areas such as digital innovation, sustainability, renewable energy, and customer services to support the IKEA vision of creating a better everyday life for the many people.
You joined IKEA after leadership roles at Adidas and GE. What attracted you to IKEA as an opportunity?
I've always enjoyed working across different industries, technologies, and functions throughout my career. After 15 years at Adidas, where I spent several years helping rethink sales across wholesale, retail, and online channels, I was considering what might come next when IKEA approached me.
What stood out was the company's purpose, values, and focus on improving everyday life for the many. I also saw a unique opportunity to help shape IKEA's next chapter. The company was transitioning from a traditional brick-and-mortar retailer to an omnichannel business, expanding into smaller urban formats, and exploring new areas such as secondhand products, sustainability services, and financial solutions. The combination of purpose and transformation made it an incredibly compelling opportunity.
Many organizations rushed into AI, while IKEA appears to have spent considerable time building data foundations first. Was that a deliberate strategy?
Absolutely.
Strong foundations are essential if you want AI to scale. It's relatively easy to create a proof of concept or launch a pilot, but scaling AI across more than 400 stores and over 30 countries requires the right data foundations, governance structures, and change management processes.
As part of our broader digital transformation, we committed early on to putting data at the center of everything we do. We focused on building foundational capabilities such as customer data, product data, and core business processes before layering applications and AI on top. We're still on that journey, but having those foundations in place has allowed us to move further and faster as AI adoption accelerates.
Can you share examples where AI has delivered measurable ROI for IKEA?
One important distinction is that AI is broader than generative AI. Some of our strongest returns are still coming from traditional AI initiatives that we launched years ago. In customer-facing areas, personalization and recommendation engines have generated significant value by helping customers discover relevant products and improving cross-sell and upsell opportunities.
On the generative AI side, we've developed what we call our Home Imagination platform. Customers can scan a room and receive multiple furnishing suggestions based on their preferences and budget. The solution is now available across nearly 30 countries, and we're seeing strong increases in engagement, dwell time, and conversion rates. In supply chain operations, AI-driven order allocation has also delivered substantial ROI by optimizing fulfillment speed while balancing logistics costs.
How has the home imagination platform evolved since its launch?
We originally launched the platform in 2021 and 2022 in the United States, before generative AI became widely available. At that stage, customers could scan a room and visualize IKEA products through 3D technology.
Today, the platform is significantly more advanced. Customers can explore multiple furnishing concepts for their spaces, while internally we've created versions for our coworkers as well. A room-planning task that previously took a coworker eight or nine hours can now be completed in approximately 30 minutes. That dramatically lowers the cost of providing the service and allows us to help many more customers with the same resources.
You're training tens of thousands of coworkers in AI literacy. What are your objectives, and what does that look like in practice?
The first step is ensuring everyone understands what AI actually is. We want to remove the hype and anxiety while helping coworkers understand the possibilities, limitations, and responsibilities that come with the technology. With approximately 160,000 employees, broad adoption is critical if we want to capture AI's full value.
So far, around 40,000 coworkers have completed AI literacy training. Beyond education, we involve coworkers directly in the development process. We bring AI specialists together with frontline employees, home furnishing experts, and planners to ensure we're solving real-world problems. That's where practical experience and technology come together most effectively.
How are you encouraging bottom-up AI innovation across the organization?
In addition to top-down initiatives, we actively encourage coworkers to identify opportunities where AI can improve daily work. Through pilot programs in several countries, we give employees access to AI tools and invite them to develop solutions for routine tasks, automation opportunities, and workflow improvements.
A great example came from a store visit in Germany. Two coworkers demonstrated applications they had built using large language models to improve areas such as replacement parts management and billing processes. What began as local solutions are now being expanded more broadly. Those ideas emerged directly from the frontline, and they illustrate why successful AI adoption requires both strategic direction from leadership and creativity from employees closest to the work.
You mentioned that even with strong foundations, some course corrections were necessary. What lessons have you learned?
One of the biggest lessons is the importance of maintaining a single source of truth. As product teams were given greater autonomy, some created their own data environments and duplicate datasets to move faster. While that accelerated short-term delivery, it also created technical debt and inconsistencies.
Today, we're correcting those issues by reinforcing common data foundations and standardized processes. That work takes time, but it's essential if AI is going to scale effectively. Without shared data and governance structures, organizations can build isolated AI solutions, but they will struggle to create lasting enterprise-wide impact.
