How Scania is accelerating work with AI across its global workforce
TL;DR
Scania is accelerating AI adoption across its global workforce by rolling out ChatGPT Enterprise, enabling team-based experimentation, and integrating AI into lean processes. This approach has led to rapid productivity gains and sustainable capability building.
Key Takeaways
- •Strong bottom-up pull from engineers and teams drove rapid AI adoption and experimentation.
- •Early governance with clear guidelines enabled innovation without restrictions.
- •Team-based onboarding ensured lasting capability and integration into workflows.
- •AI was embedded into continuous-improvement processes for natural use case discovery.
- •Leadership embraced the fast pace of uptake, designing processes to support it.
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Founded in 1891, Scania operates across Europe, the Americas, and Asia—building the trucks, buses, and transport systems that keep the world moving.
Today, the company is accelerating the shift to a sustainable transport ecosystem while shaping what AI adoption looks like inside a highly technical, engineering-led organisation evolving from vehicle maker to global transport ecosystem leader.
We sat down with Jan Oldenkamp, Chief Information Officer, and Jan Guhres, Senior Manager Business Enabling Services, to hear how Scania is rolling out ChatGPT Enterprise, enabling experimentation across teams, and building AI into the “team DNA.”
“It's going faster [than we expected]—both in time and in quality.”
Results at a glance
- Strong bottom-up pull from engineers and frontline teams
- High experimentation across functions
- Fast early gains in productivity, quality, and operational workflows
- AI now embedded into continuous-improvement and lean processes
- Teams—not individuals—trained and onboarded to build lasting capability
Inside the rollout
Scania’s decentralised culture meant teams were ready to explore AI from day one. Adoption spread quickly across engineering and operations, supported by a partnership with OpenAI that began around a year ago. Licences were made widely available so teams could experiment, share what worked, and uncover use cases organically.
From the outset, governance was built to enable—not restrict—experimentation.
“We had good cooperation with legal and security from day one,” says Guhres “By providing clear guidelines, engineers and builders felt free to experiment—and it’s worked ever since.”
To ensure capability stuck, Scania introduced team-based onboarding, not isolated individual training.
“Everyone was only allowed to join if they joined as the whole team. That’s how we build continuity… we wanted it in the team DNA,” Guhres explains.
As more teams gained confidence, momentum accelerated.
“The pace of the requests [for ChatGPT] keeps expanding.”
This blend of strong bottom-up energy and enabling guardrails is now shaping how Scania scales AI deeper into core engineering and operational workflows—turning experimentation into enduring capability across the company.
Leadership lessons from Scania
- Let the organisation pull, not wait to be pushed: Bottom-up appetite for AI was strong—Scania embraced it rather than controlling it from the centre.
- Build the guardrails early—then get out of the way: Legal and security became enablers, not blockers.
- Scale by teams, not individuals: Team-based onboarding created resilience, shared knowledge, and sustainable capability.
- Insert AI into existing improvement systems: By integrating AI into Scania’s lean and continuous-improvement processes, use cases surfaced naturally.
- Expect the speed to surprise you: Anticipate rapid uptake—and design processes that can absorb it.
What’s next
Scania is now exploring agent capabilities, deeper workflow integration, and long-term opportunities to support its ambition to build the sustainable transport ecosystem of the future.
“AI allows us to explore what our role will be in this new ecosystem—and how we can deliver on that promise.”
As adoption grows, Scania’s workforce is learning together—and moving faster together—than ever before.