No, not the pandemic and work from home, nor managing people with more experience, nor elections had brought Claire to the point of tears, but the pressures and anxieties of AI had finally pushed her over the edge.
After snapping at one of her direct reports, Claire left the team meeting hurriedly. She walked directly to the bathroom and stood over the sink, red face and tears silently streaming down her face. After all of Ted's support and hard work she just bit his head off, and she even knows his questions are coming from real concern about quality and his own impact.
Ted is an eight-year veteran at the company, a role model who has navigated a lot of change with integrity. Twenty years in similar roles. He has loved the work and genuinely appreciated Claire's leadership style. But lately he is struggling — with insecurity, with a loss of autonomy, with a real fear about what he still brings to the table. He is quietly asking whether the company cares about quality anymore, or whether since the PE purchase, productivity — even at lower quality — has become the only thing that matters. He isn't being paranoid. He is reading the situation accurately.
Two weeks prior, the head of HR and the CIO sent an email:
"Starting next week, there will be mandatory AI tool training. As you know we have been investing in AI tools for everyone at the company. We are not seeing the usage or productivity gains. To better ensure this investment works we are providing this training and then will begin to monitor AI logins and usage."
It was not really the move but the message. They weren't indifferent to the people who had built this company — they were caught between a board expecting measurable progress and a workforce that needed something they hadn't been given yet. Like all companies, there were times the executive team managed change better than others. This was not one of the good examples. The initial rollout of the tools felt transactional — and now this email made the subtext plain. The company needed to increase production or decrease costs to justify the AI investment. It further heightened fears that had already been building quietly for months.
It also caught every front-line manager off guard. They received the message at the same time as the workforce. They were sent a few FAQs. They didn't feel prepared. They had the same questions. The same fears. And no better answers.
Leadership, in their haste to see ROI, did what many companies are doing — they tossed the tools over the wall. AI got a bad reputation it didn't entirely earn, and team members felt unheard while managers felt unprepared.
It didn't have to go this way. If the team had been involved, Claire walks down the hall with Ted, brainstorming how he could prototype a new process with the AI tool. Same manager. Same employee. Same tools. Entirely different story.
Why did we go so fast when these are the people we have trusted for so long?