In this exclusive interview, Juho Korpela, Head of AI Value Acceleration at Neste, discusses his career journey and what led him to his current role. In addition, he discusses challenges and opportunities with different facets of AI such as implementation and scaling, literacy, regulations, and sustainability. He also shares insights from his experience with the Aurora Live Executive Business Network, highlighting its value for networking with peers, meeting diverse solution providers, and gaining new ideas.

Hi Juho! What led you to the role of Head of AI Value Acceleration at Neste?

I joined Neste 8 years ago to manage a major investment project. One thing led to another, and I’ve been involved in many digital-related programs since then. In my previous role, I was responsible for the acceleration of our digital and data portfolio growth and its business impact.

With AI, we see so many areas where we can build more advanced capabilities on top of the existing dataset or wisely utilize information. That’s why AI was picked and now I’m pushing that forward and making sure we get the value out of it by having the right tools and capabilities in place, in terms of technology, people, and know-how.

I’ve held several development positions at Neste, so the Head of AI Value Acceleration role was a good next step. I’ve been working with AI, data, and digitalization throughout my career. As AI is evolving rapidly, it’s interesting to be part of that in a big company. I see many opportunities at Neste as well within this space.

How do you demonstrate AI’s business value to the board?

We are far beyond AI hype. AI overall is valuable at Neste, whether it’s machine learning, generative AI, or intelligent automation. We have a solid way to track the actual value. If we think of AI in a nutshell, it’s a tool that helps us utilize our existing data in a smart way in decision-making, forecasting, and predictions.

The actual value comes from how we can improve processes and the way people work. When we measure that, it’s easy to model the monetary value and compare that to financial results as well. We have a program called Neste Excellence that enables this value measurement. We use the same tools and models to track AI value as we do for digitalization or process development.

What challenges do you face with AI implementation and scaling?

Topics we want to work with include data quality, AI expertise, and the integration of AI into our operations. While we have a large amount of data, its quality varies. We need to prioritize core data elements, as high-quality data is crucial for effective machine learning. Data presents both challenges and opportunities for our organization.

Next, we need the right AI talent and ensure widespread AI literacy across the organization. It’s not just about having a few development experts but empowering our entire workforce with AI knowledge. We need to boost overall AI maturity and understanding when working with data. Finally, integration is a key focus. Our processes and infrastructure are complex, and seamlessly integrating new AI tools and capabilities is a priority.

What initiatives has Neste rolled out to improve AI literacy and awareness organization-wide?

We are just about to launch the Neste Data and AI Academy as a more comprehensive approach to foster AI literacy and maturity across the organization. We also conduct different trainings and pilots with our people. Currently, it’s about sharing information and making sure that people can opt into pilots and training. The overall response is forward-looking and positive. People are interested in what can be done with AI. There are many use cases and ideas on how to utilize AI in daily operations.

How does AI align with Neste’s commitment to sustainability?

As Neste is operating in an energy-intensive industry, we are aiming to be as efficient as possible within our operations.

For example, we use machine learning in the optimization of our logistics plans. This has saved fuel, reduced emissions, and improved our vessel logistics. Machine learning with AI capabilities can support us in the GHG emissions reduction and optimization of energy usage and processes, and thereby impact our sustainability goals.

Another example is generative AI. It will be a great tool for our R&D to come up with new sustainable solutions for our customers. It can have an impact on our products that help our customers reduce their GHG emissions. How we can impact our footprint in terms of facilities and operations, and then our handprint, and how we can strengthen R&D activities in fulfilling our customers’ needs.

How has the EU AI Act impacted AI developments at Neste?

The EU AI Act’s emphasis on transparency, accountability, risk mitigation, and cybersecurity aligns with our existing focus. It encourages us to strengthen our internal processes in these areas. Personally, I think the EU AI Act is a good thing as it emphasizes the right things we should focus on and will not impact Neste negatively.

What AI trends or technologies are on your radar?

There are many new developments in AI such as multimodal AI. But at Neste, our approach is more straightforward. We divide the AI technical landscape into four categories:

• AI for everyone tools like Gemini or Copilot that every employee can use safely without compromising confidential information.
• Predictions and forecasting leveraging machine learning to go beyond traditional reporting and achieve advanced analysis and forecasting. Our focus is on automating these processes and becoming truly data-driven.
• Information Assistance using LLMs to consolidate our vast amounts of R&D, contract, technology, and market information.
• Intelligent automation to help get rid of manual tasks.

At the same time, we want to run the technical POCs and understand how the whole technology space is evolving. It’s not something we should forget and just look past, but it shouldn’t be the only focus area because the value comes from being able to change our processes. The POCs help us prepare for the future. The actual value comes when we can act differently and improve our processes based on data, AI, and new capabilities.

What made you join the Aurora Live Network? Which elements of the Network provide the most value?

I joined early on when the Network was just setting up. It sounded interesting to have this peer network of people, especially as I worked with digital transformation at the time. I was able to join different events and smaller peer group meetings. It was a good platform to meet colleagues, and now it has expanded to a wide network of people. There is lots of good content and good events.

I joined the Network because it was a good way to meet people, get new ideas, and gain new perspectives around IT, digital, and data spaces.

Also, the 1-to-1 meetings are a good way to scan vendors that may be viable or valuable for Neste and identify any synergies. We take a long time to select new vendors for our pool. However, the meetings are a good way to go through different available vendors. It’s efficient for me, as I can meet four or five partners in 2 hours, instead of arranging meetings here and there.

How important are vendor partnerships at Neste? What criteria do you use to select the right AI vendors?

It’s extremely important, because now, for example, within AI, finding the right developers is difficult as there is a huge demand. At Neste, we rely on our partner network heavily.

We try to get enough good partners to work with us and ensure we have different capabilities available. We try to have a balanced portfolio of partners and provide enough interesting things for our colleagues working in different companies.

*The interview answers have been edited for length and clarity.