TL;DR

Swedish transport manufacturer Scania has successfully rolled out ChatGPT Enterprise across its global engineering and operations teams, achieving faster-than-expected productivity gains through team-based onboarding and bottom-up experimentation. The company’s approach of building enabling guardrails rather than restrictive controls has created sustainable AI capability embedded into continuous improvement processes.

Transforming Industrial Teams Through AI

Founded in 1891, Scania builds the trucks, buses, and transport systems that keep the world moving across Europe, the Americas, and Asia. Today, the engineering-led organisation is evolving from vehicle maker to global transport ecosystem leader whilst accelerating the shift to sustainable transport.

The company’s partnership with OpenAI, which began approximately one year ago, has transformed how industrial teams learn, build, and innovate together. Chief Information Officer Jan Oldenkamp notes that adoption is proceeding “faster than we expected—both in time and in quality.”

Bottom-Up Adoption with Enabling Governance

Scania’s decentralised culture enabled teams to explore AI from day one. Rather than controlling adoption from the centre, leadership embraced strong bottom-up appetite by making licences widely available for experimentation. This approach allowed teams to share what worked and uncover use cases organically.

Critically, governance was designed to enable rather than restrict. “We had good cooperation with legal and security from day one,” explains Jan Guhres, Senior Manager Business Enabling Services. “By providing clear guidelines, engineers and builders felt free to experiment—and it’s worked ever since.”

The company introduced team-based onboarding to ensure capability stuck. “Everyone was only allowed to join if they joined as the whole team,” Guhres notes. “That’s how we build continuity… we wanted it in the team DNA.”

This combination of strong bottom-up energy and enabling guardrails has generated measurable results: high experimentation across functions, fast early gains in productivity and quality, and AI now embedded into continuous-improvement and lean processes.

Results and Strategic Implications

The rollout has achieved several key outcomes:

  • Strong pull from engineers and frontline teams driving organic adoption
  • High experimentation rates across diverse functions
  • Fast productivity and quality improvements in operational workflows
  • AI integration into existing continuous-improvement systems
  • Sustainable capability through team-based training rather than individual learning

Senior Manager Guhres observes that “the pace of the requests for ChatGPT keeps expanding,” indicating sustained momentum beyond initial enthusiasm.

Looking Forward

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,” says Oldenkamp.

The company’s experience offers several lessons for organisations pursuing AI adoption: let the organisation pull rather than wait to be pushed, build guardrails early then get out of the way, scale by teams not individuals, insert AI into existing improvement systems, and expect uptake speed to surprise you.

As adoption grows, Scania’s workforce is learning together—and moving faster together—than ever before.

Source: OpenAI

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