It's Already Starting
In September 2025, Accenture made the quiet part loud.
The global consulting firm cut over 22,000 positions as part of an $865 million restructuring program, with CEO Julie Sweet explicitly stating they are "exiting on a compressed timeline people where reskilling is not a viable path" for AI capabilities. Sweet warned that employees need to "retrain and retool" at scale, and those who cannot will be let go.
This wasn't about trimming underperformers. Reports from inside the company suggest people who've been with Accenture for 20-30 years with above-average performance were laid off. The message was clear: experience and tenure don't protect you if you can't demonstrate AI fluency.
Accenture had already trained 550,000 employees in the fundamentals of generative AI. It wasn't enough. The company decided that some couldn't be reskilled quickly enough for the skills they need now.
This is exactly what Boomband CEO Jeff Taylor has been warning about. And it's not theoretical anymore—it's happening right now.
There's a lot of anxiety right now about AI swallowing up entry-level jobs. But Taylor thinks we're looking in the wrong direction.
"My worry right now is in the fat middle," Taylor says, referring to mid-career professionals and middle management layers. While much of the discourse focuses on entry-level workers, Taylor believes this demographic faces the most disruptive period ahead as organizations move from strategic AI planning in 2025 to heavy implementation in 2026.
The Naturalization Gap
Taylor's perspective comes partly from watching his own kids navigate technology. His younger children, ages 11 and 14, don't think about "googling it" the way older generations do—as reaching for a tool. For them, it simply exists. There was no before. "They just go get what they need," he explains.
This echoes what researcher Marc Prensky identified in his 2001 essay "Digital Natives, Digital Immigrants"—but AI is accelerating this divide within a single generation of workers. Entry-level employees who've already integrated AI into their college work, side projects, or daily problem-solving have naturalized it. They don't think about "using AI"—they just solve problems.
The fat middle? That's where the translation gap becomes dangerous.
Two Paths Are Emerging
Taylor sees two groups forming in mid-career roles: "AI shapers" who have AI curiosity and move fluidly with the technology, and those who don't. This mirrors what economist David Autor describes as "skill-biased technological change"—where new technology doesn't replace jobs uniformly but rather creates winners and losers based on adaptation.
The Accenture cuts prove this divide is real. Some employees adapted. Others didn't, or couldn't fast enough.
As AI-driven efficiency creates more "free time" on paper in 2025, organizations will face a reckoning in middle management layers. Some will use that capacity to drive strategy, innovation, and higher-value work. Others will appear... less necessary.
"I know this is unpopular—and perceived to be dramatic—but I think job eliminations will follow," Taylor says.
He's not being dramatic. He's being accurate.
We're in the Quiet Period—Use It
Here's the helpful part: if you're reading this, you're likely not too late. The current moment, Taylor argues, is like engagement before a wedding, or garden leave before starting a new job. "We're in the quiet period," he says. "We all need to work out."
The thinking that we should test applicants and employees for AI capability will soon feel as outdated as testing for internet skills in 2010. AI is already embedded in tools you're probably already using. The question isn't whether you can pass an AI test—it's whether you have AI fluency.
What AI Fluency Actually Looks Like
This isn't about prompt engineering tricks or taking a ChatGPT course. Real AI fluency means:
Knowing when AI helps and when it doesn't - Recognizing which parts of your work AI can accelerate vs. where human judgment is irreplaceable
Building AI into your workflow naturally - Not as a separate "AI task" but as an integrated part of how you research, draft, analyze, and problem-solve
Staying curious about new capabilities - As AI tools evolve monthly, AI shapers experiment and adapt rather than waiting for formal training
Understanding AI's limitations - Knowing when to verify, when to push back, and when outputs need significant human refinement
Clayton Christensen's The Innovator's Dilemma (1997) showed us that incumbents struggle with disruptive technology not because they're incapable, but because their success with old methods makes them resistant to new ones. Mid-career professionals have something powerful: institutional knowledge, relationship capital, and strategic thinking. The challenge is integrating AI as an amplifier of these strengths, not viewing it as a threat.
Accenture trained over half a million employees in GenAI fundamentals. But training isn't the same as fluency. Fluency is using it every day, naturally, until it becomes invisible infrastructure in how you work.
The Class of 2026 Will Show Us the Future
AI's impact on the entry-level hiring class of 2026 will be fascinating precisely because some have already naturalized to working with AI, while others haven't. Companies will quickly see the difference between candidates who integrated AI into their capstone projects, internships, and job searches versus those who treated it as a novelty.
For Gen Alpha—the generation born after 2010, as named by futurist Mark McCrindle—entering the workforce in the 2030s? They won't have these challenges at all. AI will be like electricity—invisible infrastructure.
Your Move
If you're in the fat middle, this quiet period is your advantage. You have:
Time - Though the Accenture news shows the window is closing faster than many expected
Context - You understand your organization and industry deeply
Agency - You can choose to become an AI shaper starting today
Start small. Pick one repetitive task this week and figure out how AI could handle it. Not as a replacement for your judgment, but as a tool that gives you more time for the work that actually requires your expertise.
The Accenture layoffs aren't an isolated incident. They're the beginning of the pattern Taylor predicted. The question isn't whether this is coming to your industry or your company—it's whether you'll be ready when it does.
By Jeff Taylor and Dee Dellovo, with editorial help from ChatGPT and Claude
