These days, there is a scene we often see in corporate settings.
The CEO and executives say, “We need to adopt AI too.” A company‑wide message goes out, training circulates, and tools are deployed.
However, in practice, employees who actually integrate AI into their work and deliver results are often a tiny minority within the organization. In such cases, the company typically has only one or two people per team—at most a handful—who are proficient, and the workload piles onto these few.
The next issue is...
The company must deliver short‑term results every year. Employees who use AI well will produce outcomes faster and more abundantly than others. The problem comes next.
But the way the organization works remains unchanged—reporting structures, collaboration methods, evaluation criteria. What will happen then?
In the eyes of most colleagues who can’t use AI, that person appears to be "someone working at a different pace than everyone else". And, as recent reports have shown, in such cases they often trust AI more than their peers. When you try to collaborate with colleagues, work actually gets delayed, whereas AI instantly provides the output for the tasks assigned from above. However, if this repeats, those who work in traditional ways start to view the person as lacking "soft skills" because collaboration is difficult. In the worst case, if that high performer also has weak interpersonal relationships, they may be sidelined by office politics and fail to receive good evaluations despite delivering results. What happens then? The high performer can still succeed elsewhere, either by moving to another company or by going freelance. Ultimately, the organization ends up losing its talented employees while only the less capable remain.
We call this 'AI adoption paradox'. The more AI is adopted, the more the organization loses the talent it needs most.
The cause is clear. AI has accelerated the pace of work, but the organization hasn’t built a structure to absorb that speed.
Therefore, I often tell executives in my consulting work that AI adoption is not just about using the right tools; the organization’s ways of working and its culture must change first.
In the AI era, AI should handle the mundane tasks while we redefine what humans should do and redesign workflows—responsibility that rests with executives or, at minimum, team leaders. Consequently, for AI adoption to truly boost productivity, executives and team leaders must first become experts who understand and effectively leverage AI.
Seeing so many unfortunate cases around me has been on my mind, so I’m writing this in the early hours.
If you’re grappling with similar concerns, feel free to leave a comment or send me a DM.