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GoMore

AI decisions for GoMore's leadership

GoMore/Getaround's leaders needed a grounded view of what AI could change over the next three years and which decisions would follow.

Client
GoMore
Challenge
GoMore/Getaround's leaders needed a grounded view of what AI could change over the next three years and which decisions would follow.
Results
  • A 90-minute session and discussion for approximately 25 leaders
  • Built on interviews, company research and documented development curves
  • Work cards for choosing workflows, ownership and bounded 90-day experiments

The question in the room

GoMore and Getaround had become one combined company. Around 25 leaders from both sides were looking three years ahead: what happens to a company when AI can solve longer tasks, becomes cheaper and moves into daily operations?

This was not meant to be a tour of new tools. The session needed to help the leadership team see which assumptions might be expiring and what they should therefore examine again.

The preparation

I started outside the company. I researched the development of AI, mobility and digital marketplaces. I then moved closer to GoMore/Getaround’s own work through research and conversations with the organization.

That produced one movement through the session:

  1. What has changed in the world?
  2. What does that mean for concrete workflows?
  3. Which choices must leadership make about accountability, mandate and learning?

Uncertainty was part of the material. Projections were used to stress-test current plans, not as confident predictions about 2029.

From inspiration to work

The leadership team worked with old assumptions about AI, handoffs between people and systems, and possible digital roles. Freja took part as a digital colleague, briefly moving the room from listening to working with its own examples.

After the session, the group could continue with work cards about concrete workflows, human accountability, stop rules and small experiments designed to produce useful evidence within 90 days.

This is how I prefer to advise on AI: close enough to the work for the questions to become real, without pretending that one session can predict the future or deliver a finished strategy.

Brokk & Sindre

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