When I read about how AI is currently being rolled out in workplaces, it often feels a lot like a senior manager with a megaphone shouting down a very long hallway. The usual script goes like this: “We want to boost efficiency. We want faster production cycles. So start using AI tools. NOW” The higher-ups throw the AI ball over the fence and expect everyone on the lower rungs to catch it and run with it. This approach is like a top-down waterfall trying to fill a pool but forgetting the pool has holes in it. You get some splashes, but a lot of wasted effort and frustration. A recent internal memo at a large tech company is a perfect illustration of this top-down dynamic. In the memo, leadership made it mandatory for all employees to become “AI native,” making daily use of AI tools a core job requirement. Employee evaluations now consider AI adoption, and staff must demonstrate that tasks cannot be handled by AI before requesting additional resources or hires. This sweeping directive, issued from the top, exemplifies how leadership-driven mandates can rapidly reshape workplace expectations, often without much room for gradual adjustment or grassroots input.
I have been noodling on this and feel strongly that this kind of AI adoption is backwards. It’s like trying to get a plant to grow faster by spraying fertilizer on the leaves instead of enriching the soil first. What if, instead, we flipped the whole process around and made it bottom-up? The core driver wouldn’t be “let’s squeeze every last bit of efficiency,” but rather “let’s help everyone learn what AI can really do and how to use it.” This means investing time and resources into AI education for employees, especially those on the front lines who use the tools day-to-day.
The way I see it, AI adoption is less about a blunt tool wielded by management and more like a garden where every worker is a gardener who needs to understand the soil, the sun, and the water. When frontline employees become sufficiently AI-literate, they don’t just follow instructions blindly; they start improvising, experimenting, and coming up with creative hacks that management probably never imagined. This bottom-up approach sparks innovation and invites people to shape AI’s role within their own workflows, rather than having it dumped on them as a mandate.
From my experience poking around different companies and talking with people using AI tools, I have noticed something: the real roadblock isn’t fancy tech or stubborn software, it is knowledge and trust. Many employees either don’t fully understand AI’s strengths and limits or worry it might replace their jobs quickly. So instead of seeing AI as a helpful teammate or at least a very useful tool, they treat it like some mysterious black box they are forced to use. That is why I keep coming back to intentional AI education as a true unlock. I first stumbled onto this idea during a conversation with Thorsten Johanntoberens, sparked by a note he had posted here. Imagine a workplace where AI is demystified employees get hands-on training, share their success stories, and troubleshoot issues together, like the Bertelsmann AI Summer Camp. It cuts through the fear and builds a culture of collaboration between humans and machines.
Twist is, for this to work, it also means management has to get comfortable with relinquishing a bit of control and listening more carefully to subject matter experts. These are the people who understand the nuances of the work better than anyone and can spot where AI really adds value or where it might screw things up. Instead of top brass telling them “Use AI this way,” a better question is: “How do you think AI could fit into your workflow?” This kind of dialogue doesn’t just improve AI adoption; it improves the AI itself because feedback loops get faster and richer.
I like to think about this shift like a jazz band versus an orchestra. The top-down approach is an orchestra playing from a strict score, conducted by management, everyone must follow the sheet music exactly or risk chaos. The bottom-up approach is jazz, where each musician listens, responds, creating something unique and dynamic. AI is the new instrument, and only by letting the individual players experiment can real magic happen.
Of course, this is easier said than done (and I have never managed a large team/org.) But I believe rethinking incentives, training programs, and communication channels is worth it. Organizations need to move beyond the checklist of “deploy AI tools” and instead build ecosystems that foster ongoing learning and sharing. I have seen examples where even small, informal AI “hack days” or peer learning groups have sparked leaps in creative problem-solving. It is like lighting little fires that spread warmth and light rather than pushing AI as a cold efficiency machine.
To me, the ultimate win here isn’t just cutting time or resources, it is unlocking human creativity powered by AI’s strengths. Efficiency is a natural byproduct when people are excited and empowered to use AI in ways that truly make their work better, not just faster. That’s the win-win scenario that currently feels elusive in many workplaces stuck in old-school top-down mindsets. The experiment I would encourage is to start with education that isn’t just a one-off training but an ongoing conversation. Give employees space to design how they actually want to use AI. Watch for those moments when they surprise with unexpected use cases or workflows that hadn’t considered. And don’t be surprised if efficiency gains show up as a happy side effect rather than the main headline.
AI in the workplace isn’t some magic bullet sprayed from above; it’s more like a garden that needs tending from the roots up. As long as we keep trying to force it from the top down, it’ll feel like pushing water uphill. But when we invest in learning, listening, and adapting, AI becomes not just a tool for efficiency but a partner in innovation and growth. In this sense, the future of AI at work is less about handing down decrees and more about starting a conversation that everyone can join. It’s an invitation to get your hands dirty, explore, and find new ways to thrive together. And honestly, that’s a much more exciting place to be.