Tane Piper: Implementing Content and AI Technologies at IKEA – Episode 5

Tane Piper "Leading-edge technology" may not be the first thing that comes to mind when you walk into an IKEA store, but maybe it should be. IKEA is using AI technologies across its vast collection of businesses to deliver better content experiences to its customers. Tane Piper leads an engineering team at Inter IKEA - the business unit that owns the IKEA brand - that is building their next generation of content and artificial intelligence tooling. We talked about: his role at Inter IKEA the scope of AI activities at IKEA how their knowledge graph provides a "ground reality" for the info they share enterprise uses of AI at IKEA how narrowing the scope of models to your own enterprise improves quality and reduces costs the importance of testing implementations of AI technology how their knowledge graph helps connect content across the enterprise - and offers new content metrics and analytics benefits how their systems facilitate content discovery and reuse how he uses ChatGPT to accelerate his business research his thoughts on AI technologies can add a qualitative dimension to content metrics how AI and machine learning practices may reduce the amount of data that enterprises need to collect and store how they are developing prompt engineering skills at IKEA the importance of taking a pragmatic approach to AI adoption Tane's bio Tane Piper is a self-taught software developer with over 22 years of experience. He has worked across a diverse set of environments, from startups and creative agencies to his current role as a Software Engineering Leader at IKEA. Here, Tane focuses on projects that blend content strategy, knowledge graphs, and artificial intelligence. His approach to leadership is centered on teamwork, innovation, and nurturing growth within his team. He enjoys experimenting with a wide range of technologies. He is involved in the open-source community, releasing various libraries over the year, and writing technical articles sharing his findings. When not engaged in software development, Tane can often be found in his garden, a hobby that provides him with a peaceful counterbalance to his professional life. Alongside his wife, he is also dedicated to the ethical breeding of Polish Hunting Spaniels, reflecting their shared passion for animal welfare. Connect with Tane online LInkedIn Video Here’s the video version of our conversation: https://youtu.be/9qX8fUpWFgQ Podcast intro transcript This is the Content and AI podcast, episode number 5. When you think of the iconic furniture retailer IKEA, leading-edge technology may not be the first thing that pops into your mind. But it should. Like most enterprises now, IKEA is exploring the many ways that LLMs, machine learning, knowledge graphs, and other AI technologies can help them sell more furniture and understand their business better. Tane Piper leads an engineering team at IKEA that is building their next generation of content and artificial intelligence tooling. Interview transcript Larry: Hey, everyone. Welcome to episode number 5 of the Content + AI podcast. I'm really delighted today to welcome to the show Tane Piper. Tane is a software engineering leader at Inter IKEA. And that's the first thing I want to ask you about Tane, is IKEA is this big sprawling complex organization. Tell me about Inter IKEA and how that fits in with the overall IKEA brand. Tane: Yeah. Thanks, Larry. So Inter IKEA, as many people know, you go to IKEA, you go to a shop, but what a lot of people don't know is it is actually a franchise system. So, Inter IKEA is the owner of the IKEA concept, so it owns the furniture side, the range we call it, the supply, and also the retail concept, which is where I work. So we come up with the ideas behind IKEA, how the store works, what the concept is when you go to an IKEA store, this kind of Swedishness of it all. And when you as a customer go to the store, you're mostly dealing with franchisees, so somebody who is working with us to build the IKEA brand in a new market. Larry: That's it. And having responsibility for the retail concept of one of the most iconic brands in the world, there's absolutely no pressure in this job, I'm going to guess. Tane: Oh, no pressure. No pressure at all. No. In some way, yes and no. I mean, yes, it's a big task. We are a very big, well-known brand around the world, but in insight when we're working on things, I think we're pretty normal. We talk about pretty normal things day-to-day. I mean, at the moment why I'm here with you today, we talk about things like content and AI and how we can use these to leverage them to improve not only the lives of our customers, they're many people, but also what we do day-to-day. Larry: Great. And that's the thing about AI is it's so sprawling and especially in a big enterprise like Ikea, it's going to be everywhere. Actually, I want to start because where we met, we met a couple of years ago at The Knowledge Graph Conference in New York City and we were talking then about knowledge graphs and knowledge representation and that. And we've subsequently talked about the work that Adam and Katariina are doing up in Sweden with the knowledge graph and all that stuff, but there's so much more going on. Can you talk a little bit about the scope, like there I know that they're doing the recommendation system that's driven by the knowledge graph, but there's so much else going on. Can you give a quick overview of how AI technologies are manifesting at IKEA? Tane: Oh, absolutely. I think in many layers we're looking at it. I think when you think about what AI is, I mean AI is kind of a catchall term for a lot of things. So I mean on one end you have machine learning. So where we're really looking at existing things like lots of unstructured content for example, in terms of an organization, we have lots of things in PowerPoints and PDF files that you can be understood by using something like machine learning. And then, yeah, very much on the other side with generative AI, certainly the opportunities that are there, the future opportunities of doing things like home furnishing recommendations and doing that in such a way that the machine understands the customer context, like the size of the room or where the location where they are. Tane: And can tailor and help to give the right recommendations based on that with that knowledge graph at the bottom. I think that's the thing that when we talk about AI and machine learning, especially with a lot of the LLM stuff that is coming along is we know that's very unstructured, unatributed. So by having that kind of ground reality with knowledge graph, that's really what we are looking to build upon, at least in the area where I work, with content as well. So yeah, I mean, we have a group inside where it's an informal kind of group, but we chat across multiple areas in the business and I think we're all kind of looking at how can we bring AI to different parts of the business because there are different use cases and what use case works for our area does not necessarily work for say supply. Larry: Oh, interesting. Yeah. Well I guess the one that comes to mind immediately for a lot of people, because it's been all the fuss for the last year, is degenerative AI stuff. And the famous thing about that is its proneness to hallucinations and things like that. And when you're running a brand like IKEA, it's really important to not hallucinate, and in your communication, and you talked a minute ago about the knowledge graph as the grounding your information in reality. Can you talk a little bit about that, how you can benefit from, because I'm assuming you can benefit from technologies like generative AI but still maintain your brand and maintain the accuracy of the information you're sharing? Tane: Absolutely. I think one of the things I like that what we've done is we've not necessarily rushed into building a lot of stuff with AI and really going all in with it in many ways. And I think what that's allowing us to do is as an organization and as brand look at what is it we need to do to show going forward that there isn't anything that can harm the brand perception, or harm the brand itself. I mean out there are already things like there's somebody created a model that allows you to create IKEA style manuals for things and it's a specific model to do that. That kind of stuff is very difficult to say what effect it would have on the brand, but I think as long as people understand it's not coming from IKEA. Tane: I think that's the thing is when you put a brand out there like that, the people have a bit more of that brand themselves. So I think that's the thing we have to take away from it. But obviously, there is protection of the brand, and yes we have to look at when we bring these generative AI services in, especially where people will be having conversations with them, putting those guardrails in there that mean that if you're talking to a home furnishing bot or agent, you're only getting home furnishing information. It's not going to give you information on philosophy, or science, or anything like that. It's keeping within the bounds of what should be doing. Larry: Yeah. Well, you mentioned both a minute ago when you were talking about machine learning, the benefits of learning from what you already have, and then as you just mentioned that, that kind of understanding of the world you operate in. So tell me about the relationship between understanding your current ... Because you have not only product information that we all see on the web, but there's tons of information, I forget what you call them, but the folks working in the stores and other enterprise employees at IKEA use. Can you talk a little bit about that ecosystem and how AI and ML interact as you're both understanding and generating content? Tane: