As businesses embrace data and AI, leaders like Olof Granberg are driving real value! With 20 years of experience, Olof has witnessed the evolution of these technologies. From early innovations to generative AI, holding key roles at ICA, Telia, and now leading DataMentor Consulting.
In this interview, Olof shares key moments from his career, including lessons from successful and unsuccessful data trends. He offers advice on preparing data for AI. Olof also stresses the importance of creating a culture where data-driven decision-making is the norm.
With expertise in data lifecycle management, Olof shares his thoughts on the future of AI and how businesses can harness the full potential of their data. As a speaker at the upcoming Data Innovation Summit 2025, Olof will guide the attendees on steps companies can take to ensure their data strategies are effective and aligned with the future of AI.
Keep reading to discover Olof’s insights into how organizations can build a data-driven culture. Learn how to prepare for the evolving AI world!
Hyperight: Olof, you have almost 20 years of experience in data and AI. Can you share with us how your journey in data has evolved over the years?
Olof Granberg: Sure! I have had many roles over the years. I started as a developer almost 20 years ago and have had many different roles. Developer, Architect, and other types of leadership positions. Many years at ICA and some at Telia. Now I am driving DataMentor Consulting and having more fun than ever with data.
Over the years, I’ve experienced many different trends in the data and AI space. Some were highly successful, and others didn’t quite live up to expectations. Among the most successful trends I’ve seen are:
- Data Warehouse
- Data Lakes
- Self-Service Analytics
- Machine Learning & Data Science
- Gen AI
Some of the less successful trends I’ve encountered include Data Virtualization, Data Wrangling tools, Citizen Data Scientists, and AutoML. These didn’t quite deliver the expected results or struggled with real-world implementation.
Hyperight: Your presentation at the Data Innovation Summit 2025 is titled “5 Actions to Make Your Data AI Ready.” Can you give us a sneak peek into what some of those actions might look like?
Olof Granberg: I always try to be as practical as possible. The data area is a complex area and we, as data professionals, tend to make it even harder by using fancy theoretical terms and practices.
That’s why my 5 actions are practical steps, and I’ll explain the impact each one can have. I’ll cover why having clear, understandable metadata is crucial for LLMs to interpret and respond to questions accurately.
Hyperight: One of the key takeaways of your talk is how to improve structured and unstructured data. What do you believe are the most common mistakes companies make when preparing their data for AI?
Olof Granberg: I think companies often treat structured and unstructured data differently, which is understandable given their distinct nature and challenges. This is why the answer requires a two-fold approach to address both effectively.
For structured data, I think one of the most common mistakes companies make is failing to assign clear ownership. When a business owner is accountable for specific data objects and has the authority, resources, and funding to improve the data, much of the friction and inefficiency disappear. This leads to smoother processes and better data quality.
For unstructured data, I think that most companies aren’t managing it effectively. It tends to be left to individual teams or employees, with little to no structured management or oversight, leading to missed opportunities and potential inefficiencies.
Hyperight: In your experience, how do companies typically underestimate the importance of data preparation? What do they miss by not investing in it early enough?
Olof Granberg: I would say many companies do not take the whole data lifecycle into consideration, which often makes it more expensive and difficult to fix issues later on. By keeping the full lifecycle in mind, data preparation and availability become much easier,. This ultimately shortens the path to deriving value from the data. This is on the same line as the Shift Left way of thinking.
Hyperight: You’re passionate about data culture. What role does organizational culture play in AI adoption? How can companies foster a culture that trusts and effectively uses data insights?
Olof Granberg: This is a difficult question, and many companies have tried and struggled with it. I once heard someone say:
Culture is the little conversations between people when they are not in meetings.
If we want people to talk about data and insights while at the coffee table, we need to improve data literacy and provide better tools. Most importantly, emphasize the “why” behind the data.
As leaders, it’s crucial to demonstrate that we value data-driven insights by setting an example. We should show how data has influenced our decisions and explain the reasoning behind them.
Hyperight: As someone who has worked across the entire data lifecycle, where do you see the future of AI in the coming years, particularly in terms of how we manage and use data?
Olof Granberg: I envision a layer of agentic AI positioned between humans and IT systems, acting as a bridge to help us more effectively manage and utilize our data. This AI would enhance our ability to handle data and improve how we interact with technology on a daily basis.
I hope that this will lead to a better digital life, allowing us to live smarter, more efficient lives while also optimizing business management and decision-making.
If you’re looking to make your data AI-ready, don’t miss Olof’s session at the Data Innovation Summit 2025! He’ll share steps to bridge the gap between structured and unstructured data, and highlight the importance of assigning ownership for better data management. Olof will also discuss how companies can create a culture where data-driven decision-making is the norm.
For those focused on improving data preparation and AI adoption, Olof’s talk will provide strategies to help you align your data approach with the future of AI. Learn how to streamline your data processes, improve business value, and foster a culture of data-driven insights!
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