This week we’re spotlighting Tomi Krogerus, Senior Manager of Analytics & AI at Kalmar. With a Doctor of Science in Technology from Tampere University of Technology, Tomi brings a unique blend of mechanical engineering and data science to the forefront of the cargo industry. At Kalmar, he leads a team of top talents driving innovation in industrial equipment and services, steering both the Horizon stream of the company’s Digital strategy and the AI Engineering stream of its AI strategy.
Tomi’s mission is clear: use data and AI to build smarter, greener operations. From piloting rapid proof-of-concepts to scaling a shared, cross-functional AI platform, his work ensures Kalmar leverages trustworthy technology to make material handling safer, cleaner, and more sustainable.
Hyperight.com: What’s the best way to describe your job to someone outside tech?
Tomi Krogerus: My team and I use data and artificial intelligence to shape a smarter, greener future for the cargo industry. We take complex information and apply it practically to improve real-world operations, such as predicting when a machine needs maintenance, or optimizing electrification and logistics.
Hyperight.com: What originally sparked your interest in AI/data, and what keeps you inspired today?
Tomi Krogerus: I hold a Doctor of Science in Technology, D.Sc. (Tech.) at Tampere University of Technology. My professional identity is best described as a unique combination where mechanical engineering meets data science. This intersection has given me a deep analytical mindset and a constant drive to think beyond the conventional to discover novel solutions. Today, I remain inspired by seeing what we can achieve when we process data in smart, purposeful ways. Applying cutting-edge AI to solve everyday challenges and create a meaningful, sustainable impact in the cargo industry is what keeps me highly motivated.
Hyperight.com: What is one challenge you’re trying to solve, and why does it matter?
Tomi Krogerus: A major strategic challenge we are tackling is safely scaling AI from isolated experiments to robust production. This requires moving beyond traditional MLOps to embrace comprehensive DataOps for AI-ready data, and pioneering “AgentOps” to manage autonomous Agentic AI. This matters because mastering this operational foundation enables us to solve massive real-world challenges, like optimizing heavy logistics and accelerating electrification. Ultimately, ensuring our AI ecosystems remain transparent, safe, and compliant with the EU AI Act is foundational to delivering long-term value and earning trust.
Hyperight.com: A tool you can’t live without (tech or not)?
Tomi Krogerus: Although our strategic focus is moving beyond basic LLM chatbots toward fully autonomous agentic systems, I still rely heavily on these conversational tools in my daily life. They act as a brilliant sounding board to support my thinking and significantly speed up routine tasks. By making my day-to-day work faster and more efficient, they free up my schedule so I can dedicate my time and energy to solving much more challenging and complex problems.
Hyperight.com: What trend in data or AI do you think will shape the Nordic region the most?
Tomi Krogerus: The shift toward production-ready Agentic AI will be the most transformative trend. We are entering an era of “Agentic Operations Networks” where decentralized AI agents autonomously plan, negotiate, and optimize complex workflows. I believe the defining trend will be using this agentic AI to drive massive sustainability efforts, specifically accelerating electrification, optimizing energy use, and creating self-learning, greener logistics ecosystems. Ultimately, the seamless collaboration between humans, intelligent machines, and agentic AI will redefine sustainable material handling across the Nordics and beyond.
Hyperight.com: What’s one piece of advice you’d give to others entering the data and AI field?
Tomi Krogerus: Don’t just get lost in the technology; focus on how data can be processed in smart, purposeful ways to create meaningful, real-world impact. Building AI successfully is a team effort, so foster a culture of trust and expertise.
