When it comes to home furnishing, few names are as instantly recognizable as IKEA. The Swedish giant has shaped how millions of people around the world think about design, affordability, and flat-pack furniture. But in an era where digital and AI are reshaping industries at breakneck speed, even a brand with IKEA’s reach and legacy has had to rethink its playbook.

Parag Parekh, Global Chief Digital Officer at Ingka Group (holding company that operates IKEA stores), admits the company was slower than some peers to embrace digital transformation. Yet, as he explains in this conversation with CDO Magazine, IKEA is now moving decisively—building data foundations, experimenting with AI, and reimagining what the shopping experience of the future could look like.

Parekh oversees everything digital, from in-store connectivity and customer-facing platforms to logistics, back-office systems, and co-worker tools. Over the past four years, he has helped build strong data foundations, unify analytics across markets, and drive AI-led innovation, positioning IKEA as a truly omnichannel brand.

With initiatives like the IKEA Creative 3D design, predictive supply chain analytics, and experiments in generative AI (GenAI), Parekh is steering the company toward a future where technology and human creativity work hand in hand.

Edited Excerpts

Q: In your four years at IKEA, what are some examples of data-led digital transformation initiatives you’ve overseen?

It started with building the foundation. IKEA was relatively late in fully embracing digital transformation, so the first step was laying strong data foundations. Our main objective was to evolve from a brick-and-mortar retailer into a true omnichannel brand, meeting customers wherever they choose to engage with us.

We began by identifying core data assets we needed to consolidate from across the organization, ensuring they were governed properly and enriched over time. Once the foundation was in place, we moved to develop analytics and insights capabilities.

A significant transformation came in consolidating analytics and insights, which had been scattered across different parts of the organization. By bringing them together under the digital umbrella and working closely with both global and local markets, we were able to deliver actionable insights that directly benefit the business.

On top of these foundations sit our AI capabilities — both traditional and GenAI. We have dedicated teams working with the business to prototype, pilot, and deploy AI-led use cases. I often describe our journey in three layers:

Let me share a couple of examples. The first is inventory availability, which is fundamental to retail. Several years ago, visibility into our inventory was limited. So, our first step was to create a single source of truth for inventory, and then integrate it into our digital channels — whether on the website, app, or in-store kiosks. This enabled basic e-commerce functionality.

But once we combined inventory data with sales transactions, we could apply intelligence to build recommendation engines. For example, in 2021, certain bed components (lattices) were unavailable in some regions due to supply chain challenges. Our recommendation engine automatically suggested alternatives, preventing lost sales. Similarly, we now cross-sell and upsell by recommending accessories, complementary furniture, or related items both online and in stores. This has significantly improved personalization and customer experience.

Another transformation has been in logistics. Our large-format stores (50,000–60,000 sqm) now also function as distribution centers. With the right data on inventory, customer location, and demand, we can optimize delivery routes, reduce costs, and improve delivery speed. Order orchestration driven by data has made us more efficient, sustainable, and customer-centric.

These are just two examples, but across customer service, back-office operations, and even reimagining customer experience in home furnishing, data has been pivotal.

Q: IKEA operates globally, with a complex supply chain. How is data, analytics, or even AI helping you shift from reacting to disruptions to anticipating and adapting to them?

The starting point is visibility — having transparency into where products are, where bottlenecks exist, and what’s happening across the entire supply chain, from suppliers to customers, including reverse logistics for returns and recycling.

Once we have visibility, predictive analytics sits on top as a superpower. For example, it helps us decide the best locations to ship products from factories to meet demand efficiently and cost-effectively. When customers place orders, predictive models also optimize delivery times and routing, often balancing between parcel and truck deliveries.

AI adds another dimension. For instance, trucks sometimes leave our distribution centers only partially filled. With AI, we optimize load planning so we aren’t “delivering air.” AI models recommend the best way to load furniture into trucks to maximize capacity while keeping costs and environmental impact low. 

Q: What do you see as the biggest challenges data and digital leaders are facing today, and how have these shown up in your own journey at IKEA?

There are essentially two types of companies today — digital natives and established organizations with decades of history. IKEA belongs to the latter, with over 80 years of growth and global expansion, often driven by entrepreneurial local leadership.

While this brought great success, it also resulted in fragmented data landscapes, with silos across different markets. Our challenge, therefore, has been to move from fragmentation to creating foundational data assets that bring collective visibility and consistency.

Moreover, we have a long and successful history as a brick-and-mortar retailer. But as we’ve shifted toward becoming a true omnichannel business, we’ve had to rethink not just our processes, but also our mindset. For decades, our ways of working were tuned to physical retail. Now, we need to understand how customers engage with us both online and offline, bring that information together, and use it to generate insights that lead to meaningful action.

This transformation isn’t only about building strong data foundations — it’s also about culture. It requires co-workers to embrace data in their day-to-day decisions and to see its value in shaping customer experience. Bridging that gap between foundations and culture has been one of the most important parts of our digital journey.

I’d add one more challenge: Ensuring we focus on the “why” before the “what.” It’s easy to get carried away by technology. But the real question is: what customer or co-worker problem are we solving? Without that focus, even the most advanced tech risks becoming a gimmick. Data and AI are enablers, but the “why” must always lead the way.

Q: GenAI is rapidly reshaping industries worldwide. From your vantage point, what opportunities does it present for IKEA, and what progress have you made in testing or scaling GenAI solutions?

What excites me most is how GenAI democratizes capabilities that were once too expensive or technically out of reach. Let me give you a concrete example. Historically, shopping for home furnishing meant browsing a website or visiting a store, selecting a sofa, bed, or desk, and then discovering later that it didn’t quite fit your home’s style or dimensions. That experience was often frustrating and costly.

Now, with GenAI, we can change this journey entirely. With our IKEA Creative tool, customers can build a 3D version of their room. In the past, we explored AR to let customers place individual pieces of furniture into their rooms. With GenAI, we’re taking this much further.

Using our “Life at Home” insights, we can identify hotspots in a room — where dining, socializing, or working usually takes place — and generate complete layouts around those activities. The system can then create several versions of a fully furnished IKEA home, each in different styles and budget ranges.

What GenAI enables is an interactive, conversational design process. You can take a suggested layout, tweak a few elements, and immediately see how the changes affect the overall feel of the space.

It’s not just about helping you buy a sofa — it’s about inspiring you with a complete living environment. Maybe the sofa works best with a certain carpet, or the lighting changes the entire ambience, or the placement of chairs creates a more welcoming flow.

By building these possibilities into our GenAI capabilities, we’re able to offer customers a very different kind of experience — one that goes beyond transactions and focuses on inspiration and co-creation. At its core, it’s about rethinking what the shopping journey should feel like. And while this shift is happening across industries, it’s especially powerful in home furnishing, where the experience is as important as the product itself.

Moreover, IKEA’s Ingka Group is scaling AI adoption across its 170,000 co-workers through initiatives like Hej Copilot, which already has 26,000 monthly and 2,100 daily active users, supported by training resources and templates. 

Q: How do you measure the success of these initiatives? In other words, what does ROI look like for GenAI at IKEA?

We look at this in two ways. First, GenAI has significantly boosted efficiency for our co-workers. For instance, if you visited our store in Bangalore, India, with a floor plan of your home, it used to take a co-worker 8–16 hours and multiple interactions to design a customized furnishing plan.

With GenAI, that same task can now be completed in 30–60 minutes. This has been rolled out across all 30 countries in our Global Product Catalog tool, and the feedback from co-workers has been overwhelmingly positive.

To deepen usage of AI within the organization, Ingka introduced My AI Portal, a secure hub for GenAI use cases and team-based assistants. Early pilots showed 67% monthly active users, 17% daily active users, and a 30% productivity boost, with expectations of 50% efficiency gains as deployment expands to all markets by FY26.

Second, from a customer perspective, we are piloting these capabilities in front-end tools like IKEA Creative, which is already available on our website and app. While today it doesn’t yet include full auto-placement features, we’re testing that functionality. The impact is already clear: customers engaging with IKEA Creative show conversion rates almost double compared to regular web or app visitors. That’s a very tangible ROI.

Q: Another area where many companies are experimenting with GenAI is code generation. Is IKEA using GenAI tools to accelerate software development or even modernize legacy systems?

Yes, we’ve started exploring this in Group Digital. We are using AI for code generation, user experience design, and even brainstorming-to-design scenarios. But it’s not just about the tools — it’s about shifting the mindset. Engineers, product owners, and designers need to embrace AI in their daily work, whether through GitHub Copilot or other code-generation platforms.

We’ve launched several lighthouse experiments and POCs in this space. Early results show productivity improvements of around 5–10% with AI-assisted coding. While this is far from the 50–60% boost sometimes claimed in the media, it’s a meaningful start. I believe that as adoption grows and cultural shifts take root, the impact will scale significantly across our digital teams.

Q: As you look to scale its use across the organization, what do you see as the most significant risks or challenges?

While GenAI is already delivering value, the real challenge is doing this responsibly and at scale. The technology is moving faster than most organizations’ ability to adapt, so risks include:

• Building and maintaining digital trust: Ensuring our co-workers and customers feel confident that AI is used ethically, transparently, and for their benefit. Data quality and governance – AI is only as good as the data it learns from. We need to ensure that our data is trustworthy, inclusive, and well-governed. 
• Change management at scale: Bringing nearly 160,000 co-workers along this journey means continuous upskilling, reskilling, and ensuring AI augments and supports the workforce needs.
• Sustainability of AI operations: AI’s environmental footprint can be significant, so we must adopt energy-efficient training and responsible data practices to align with our climate-positive goals.

Q: What’s one lesson from your IKEA experience that you think more data and digital leaders need to hear right now?

Don’t treat AI as a purely technical deployment; treat it as a human transformation. At IKEA, our most impactful AI projects succeed because they start with people — understanding their needs, addressing their concerns, and giving them the tools to thrive in an AI-powered workplace.

We separate jobs from tasks, automating the repetitive steps, freeing up humans for creativity, problem-solving, and customer connection. It’s about human capability amplified by technology, not the other way around.

Q: And on the flip side, what’s one thing you’re curious to learn from your peers in other industries as you continue evolving IKEA’s digital journey?

I’d like to learn how others are measuring long-term value from GenAI, not just in efficiency gains, but in customer trust, employee engagement, and environmental impact. We’re experimenting with new AI-powered customer channels, like the IKEA GPT shopping assistant, but I’m keen to hear how others are translating early experiments into sustainable, scalable business value, while still staying true to their brand voice and values.