Companies need to go beyond expecting employees to use AI and instead build AI-native cultures from the ground up. Nine practical shifts are outlined: tailoring AI models to company-specific knowledge, embedding AI into existing tools, removing setup friction, normalizing AI-generated work, redefining performance metrics to reward outcomes over effort, publishing AI impact data, creating internal helpdesks and champion networks, establishing clear usage governance, and tracking weekly adoption across teams. Shopify and Duolingo are cited as early examples of companies publicly committing to this transformation.
Table of contents
1. Tailor models to your company’s unique context2. Bring AI to where work happens — make it easily accessible3. Don’t make your workforce ‘set up’ AI, offer it out of the box4. Treat AI-generated work as a smart way of working5. Redefine “good work”: Reward shaping and solving, not just doing6. Publish data on how AI is improving speed, quality, and output7. Set up AI helpdesks and champion networks to drive hands-on adoption8. Create simple, public rules for how AI can be used inside the company9. Track weekly AI usage across teams, not just employee training dataRead moreSmall Slope Mentorship CareerWho's a Lead Designer? CareerDesign Quality & Business Models DesignFresh Eyes Effect ObservationsWhat I've Learned at Google as a Designer CareerSort: