Me, Myself & AI - Part I: The Thinking Window.
Exploring how the rise of AI challenges the balance between speed and reflection, and why reclaiming human judgment may be our most valuable competitive edge.
Easy title. Complex topic.
Artificial Intelligence is undoubtedly redefining relationships—across business, society, and beyond. For any normal human being, it is impossible to keep up with the current pace of change in the AI space. (Please contact me if you can—I have questions.)
Every day brings a flurry of innovation. Every day pushes the boundaries of how AI shapes our lives. But missing from these announcements is a key insight: will these changes elevate us—humans—as part of business, community, and society?
Between market buzz and customer adoption sits a rare, precious gap—a window for reflection. However, history shows that this window is usually short-lived…if it ever exists. Adoption often follows hype, not reflection.
AI is no exception: ChatGPT is a vividly recent example reminding us that fundamental questions are being asked later rather than sooner.
“Move fast and break things,” as you have probably heard. Are we moving fast? Definitely, but what are we breaking? The jury is still out.
Let me zoom in on this thinking window.
At an individual level, AI adoption seems simple: while it can take time for new technologies to permeate our daily lives, network effects are powerful accelerators. Your friends use it. You try it. You love it. You pass it on. By and large, adoption depends on individual choices, influenced or initiated. Its implications stay under control.
At a company level, ramifications appear. The AI adoption question touches an overly sensitive human dimension. Similarly to previous technologies, a wider adoption of AI in a corporate environment comes with the promise of greater speed and accuracy. This is a logical business aspiration. More worrying is that this aspiration also begins shifting ownership and relevance from humans to machines. Collective work-related interactions become abstracted. Sometimes, automated. Ultimately, individualised: you do not need a team meeting to discuss a decision if the system provides you with an indisputable output. You only need someone data literate enough to read it. Saving time, gaining clarity, removing ambiguity to extents unheard of until now: these are some of today’s most prominent pillars of AI in the corporate world.
In Part II, I will explore what happens when this logic extends further:
Could AI become the ultimate business equaliser?
Can we challenge AI’s output with human nuance?
Can we go beyond "human-in-the-loop"? (spoiler alert: yes.)
Part II drops soon. Stay tuned.