Executives wonder why AI adoption is lagging - yet employees are wondering whether helping define their work will eliminate their jobs.
by Janet Ply, PhD · The Practical Leadership Newsletter · October 5, 2026
Organizations need employees to help make AI successful.
They need employees to identify repetitive work, document what they know, experiment with new tools, redesign processes, and determine where AI could improve performance.
However, many of those employees are wondering whether helping will help eliminate their jobs. Gallup found that 27% of US workers fear technology could make their jobs obsolete - a record high and roughly double the 2017 level. For workers under 45, concern reached 34%.
This is one of the problems at the center of AI adoption and how successful it will be within organizations.
Executives are asking employees to contribute the knowledge required to transform the business while often providing little clarity about how that transformation may affect them.
Then leaders wonder why employees resist, protect their responsibilities, or do minimal work to help.
What appears to be resistance may actually be a rational and expected response to the incentives executives have created.
Large ERP implementations promise integrations with other systems, efficiency, and better information. Many eventually deliver substantial benefits, but people have to redesign processes, clarify decisions, clean up inconsistent data, and change how work is performed.
When executives treat ERP implementations primarily as technology projects, organizations often automate existing confusion, work arounds, and poor processes at considerable expense.
I have been called in to help recover major initiatives where executives believed they had an execution problem. The deeper issues revolved around the leaders in charge. They had underestimated the decisions, capabilities, communication, and organizational changes required to produce results.
AI presents the same leadership challenge but at a much greater speed and scale.
Its use is spreading throughout organizations before many companies have defined the business problems they want it to solve, established meaningful quality or governance standards, or considered what employees need to participate honestly.
Every major technology and business transformation eventually becomes a leadership transformation. AI is exposing the quality of that leadership faster than most.
Employees are frequently told to “start using AI.” One of the executives in a client company said that one of their corporate goals was to implement AI throughout the company. When I asked what that meant, he said, “I’m not sure. We still have to figure that out.” “Do you have a plan for how to figure it out?” I asked. “No, not yet. We’ll need to work on that.”
That ambiguous instruction may produce more prompts, pilots, reports, summaries, and presentations. It does not necessarily produce better work. As a case in point, I was reviewing a Word document recently that reeked of AI-jargon. The person who asked me to review it didn’t even bother to change the author field from Python to their name. It’s not the first time I’ve seen this.
Leaders complain about employees turning in AI-generated slop, but the problem may have started several levels higher.
When executives announce ambitious AI goals without defining the business problem, desired outcome, or quality standard, AI slop begins at the top.
Employees respond to what leaders reward. If leaders celebrate how many people used AI, how many pilots were launched, or how many hours were supposedly saved, employees will produce evidence of activity.
Executives need to provide three conditions for responsible AI adoption: direction, standards, and psychological safety.
Direction gives employees an indication of where they’re heading - a north star of sorts. They need to know whether AI is expected to improve customer service, increase capacity, strengthen decisions, reduce costs, eliminate positions, or achieve some combination.
Standards make that participation productive. Employees need to understand what good AI-assisted work looks like, where human judgment remains essential, and who remains accountable for the final result.
Psychological safety makes participation possible without fear of retribution. Employees need to know that sharing their knowledge, raising concerns, and identifying automation opportunities will not be used against them.
Together, these conditions create the trust an organization needs to change how work gets done.
If you asked ten employees what your AI strategy means for their work, would they answer it confidently or just guess?
Here are four questions executives need to consider when asking for AI adoption from their employees:
Organizations need employees to help build a better future with AI. Executives have a responsibility to provide clear guidance and expectations.
AI adoption is exposing far more than technical readiness.
It is exposing whether executives can provide direction, establish meaningful standards, confront difficult truths, and treat people fairly while the organization changes.
It is exposing the quality of executive leadership.
Janet Ply, PhD
Author, Practical Leadership ~ Creator of the Practical Leadership Accelerator