We’ve Been Here Before: Why AI Adoption Feels Familiar (and How to Get It Right)
I remember the early days when "we need a website" was the rallying cry in every boardroom. Years later, it was "we need a social strategy" or "marketing automation."
Today, the cry is "we need AI agents."
While the technology changes, the underlying challenge for leadership remains the same. I recall a project earlier in my career involving a large scale initiative to launch a proprietary industry forum. The vision was massive. However, when we dug into the "Why"—why our audience would care and what specific gap we were filling—the answers were thin.
We eventually found success by starting small with a focused, partner led pilot in one region. That version flourished for years because it was built on a foundation of credibility rather than just the desire to "do something big."
AI feels different because of its speed, but the implementation traps are identical to those I have navigated over the last 20 years:
The Authenticity Gap: AI is not a mind reader. Whether you are an independent consultant or a marketing lead in a larger organization, your brand is built on a specific perspective. Without feeding the software your specific "scar tissue" and unique insights, the output is just generic "slop."
The Implementation Gap: I have seen many leaders get excited by "great ideas" that never move past the prompt box. High level strategy only works when it is translated into executable actions and playbooks.
The Resource Gap: No matter the size of the company, resources are never unlimited. Whether you are managing a startup budget or a departmental one, the goal is to use those resources wisely. You do not always need complex ROI calculations to see what is working. You need to ensure that every automated activity is actually moving the needle on your specific goals.
As a brand strategist and founder, I have learned that the most "innovative" thing you can do is not adopting the tool first. It is asking the right questions before you turn it on.
Instead of asking "What can AI do?", perhaps we should be asking: "What problem are we actually trying to solve, and is our brand's voice still recognizable in the solution?"
