In advance of his appearance at CDAO Nordics, we interviewed Murat Acar, Data and Machine Learning Leader at IKEA. Murat brings a systems-focused perspective to data and AI, driven by his background in engineering and software development.
In this exclusive interview, Murat explores key trends in responsible AI, regional readiness, and the transformative role of data in today’s business landscape. He discusses the ongoing convergence of digital, data, and AI, and emphasizes the importance of a robust data foundation for sustainable growth in analytics and AI initiatives.
Join us at CDAO Nordics, to hear from Murat and other industry leaders about the top trends and challenges they believe will define AI and analytics in 2024 and 2025.
C: What do you see as the biggest challenges in bridging the gap between research and practical application in data analytics and AI?
Murat Acar: One of the key issues I see is the gap between research and practical application in data analytics and AI. Back in, say, 2010, we were focused on data mining, predictive analytics, and prescriptive analytics, with little mention of AI in the industry. Then a paradigm shift occurred, and AI became the main topic.
For me, it's important to be realistic, not overly hyped, especially in analytics and AI. Grounding discussions in reality, with a strong data foundation, is essential. I prioritize a pragmatic and research-oriented approach in my work.
C: At CDAO Nordics you'll be speaking on a panel about the convergence of digital, data, and AI. What do you find most interesting about this convergence?
Murat Acar: If we look at it chronologically, we went from digitization to digitalization, and then to digital transformation—each of these stages has unique characteristics. Starting around the 2000s, we had ERP, business intelligence, and data warehousing. By 2010, digital transformation was gaining momentum, and we saw digital, data, and AI movements beginning to interlink.
Initially, data analytics, data mining, and data warehousing became popular across industries. Then, as tech giants started making these technologies accessible, AI began to follow a similar path. The increased computing power has pushed AI toward becoming a commodity, much like data. I see digital, data, and AI as interconnected systems that build on each other in meaningful ways.
C: How do you think the Nordic region stacks up in terms of readiness for the next steps in digital and AI? Are there any regional factors that stand out?
Murat Acar: There’s one factor that stands out to me: the digital maturity of organizations and individuals in the Nordic countries. Everything, even digital transformation, starts with people. The long-standing digital capability and maturity in the Nordics serve as a strong catalyst, positioning the region as a pioneer or first mover in analytics and AI topics.
This solid foundation makes the Nordics especially well-prepared and adaptable, and similar levels of digital maturity can be seen in parts of Europe as well. In short, the digital readiness of individuals and organizations will play a critical role in the region's progress in these areas.
C: Given that you primarily work in retail, what do you see as the opportunities arising from the convergence and increasing maturity of AI for retail organizations?
Murat Acar: In retail, if we look back to the era of data warehousing, we had retail-specific data warehouse models that became a baseline for major retail players worldwide. These models established foundational data practices for many retail organizations. Now, as AI maturity increases across countries and organizations, there's an opportunity to standardize AI models and approaches specifically for retail.
For example, AI maturity can lead to more defined guidelines around data privacy and security tailored to retail, as well as to other sectors like telecom. I believe we’re moving toward a point where we’ll see distinct, industry-specific AI practices emerge, especially around responsible and ethical AI. Many companies are already developing frameworks in this area to ensure AI is deployed in ways that align with sector-specific standards.
C: What do you consider to be the essential pillars of a strong data foundation, and how do they contribute to successful analytics and AI initiatives?
On a personal level, I always emphasize that a solid data foundation is the cornerstone for everything we do in analytics and AI. For any initiative to succeed, establishing this foundation is the first priority.
With a strong data base, we can then build toward our goals and objectives effectively. For me, ensuring this foundational layer is always a top priority.
One major pillar of any foundation is a strong framework for data security and privacy, which impacts many organizations. This is crucial for establishing a reliable data foundation.
For analytics and AI, responsible AI practices are also essential. In Europe, for instance, we have the European AI Act, which companies are actively aligning with. These frameworks create different priorities for organizations, helping them build a responsible and effective foundation for data and AI initiatives.
C: On a professional level, what excites you most about working in data and analytics? What’s the most interesting aspect for you?
Murat Acar: I remember reading the phrase “data is the new oil” about a decade ago—it was a powerful statement. Since then, what motivates me most is the progressive and incremental potential of data. It has shifted from a support function to a strategic asset at the core of organizations that aim to lead in their fields.
Data, analytics, and AI now impact every critical function—from product and engineering to HR, operations, and finance. The ability to drive a holistic, horizontal impact across an organization is what truly excites me.
You can find senior members of our expert community discussing these topics, as well as many others, at CDAO Nordics, click here to register now