Something quiet but profound is happening inside companies right now. It doesn’t show up cleanly in headlines. It’s not fully captured in layoff numbers or hiring trends. But if you talk to operators, product leaders and engineers across Utah, the pattern is clear: The workforce isn’t being replaced. It’s being rewritten. And the people who are moving first are pulling away — fast.
The signal beneath the noise
When Catherine Wong, COO of Entrata, talks about AI, she’s not talking about tools. She’s talking about restructuring how product teams work entirely.
Product management, design and engineering — once clearly defined roles — are compressing. AI is accelerating the work so dramatically that the boundaries between roles are blurring. This isn’t a future scenario. It’s happening now.
Across Utah, similar patterns are emerging:
- Program managers are running internal workforce programs delivering weekly AI capability building, not annual training cycles.
- Demand generation teams, many led by women, are using AI to outperform traditional sales models with smaller teams.
- Master’s students are building full-stack applications in a week, compressing what used to take months.
- Senior engineers are being quietly displaced because they aren’t adopting fast enough.
And when Block, the parent company of Square and Cash App, laid off roughly 40% of its workforce, it sent a ripple through the tech world and a clear signal: AI isn’t just changing efficiency. It’s changing who is needed.
This is not a job story — it’s a participation story
The biggest misunderstanding about AI is that it’s a job replacement problem. It’s not. It’s a participation problem.
AI is unbundling work into tasks by automating the repetitive, accelerating the analytical, and elevating the strategic. In this reality, the advantage no longer belongs only to those with the most experience. It belongs to those who can apply AI to increase their output, decision-making, and impact.
That’s why a 24-year-old using AI fluently can outperform someone with 15 years of experience who isn’t. That’s why entire functions are compressing. And that’s why the real divide in the workforce is no longer degree versus no degree, or technical versus non-technical; it’s AI adoption versus non-adoption.
Utah’s inflection point
Utah’s economy is expanding rapidly. Deep tech industries are accelerating across the state with no sign of slowing down.
At the same time, our workforce is facing a paradox. Our population is growing to nearly 4 million by 2033, and jobs are expanding to 2.8 million, but thousands of experienced workers have stepped out of the workforce in the past five years. This means Utah does not have enough people to meet its own growth, unless it expands who participates.
“AI isn’t removing the need for people; it’s raising the bar for participation. The question for leaders is no longer, ‘How do we adopt AI?’ It’s ‘Who are we enabling to succeed in an AI-driven economy, and who are we leaving behind?’”
— Cydni Tetro
The missing piece
Women make up nearly 45% of Utah’s workforce. Yet in many of the fastest-growing, highest-paying, and most AI-influenced roles, participation remains uneven.
At the same time, thousands of professionals, many of whom are women, have stepped out of the workforce temporarily, built careers in adjacent or nontechnical roles, and even developed leadership, operational and customer expertise. They are needed and potentially valuable additions to our growing workforce needs. But they now face the new great barrier of entrance: AI fluency. They do not lack capability. But the system hasn’t been redesigned to bring them forward.
AI changes who gets to build
AI is the first major technology shift where you don’t need to be an engineer to create value, you don’t need to code to build and you don’t need years of technical training to contribute to innovation.
AI expands the surface area of who can build products, analyze markets, create systems and influence decisions. That means the next wave of economic growth will not be driven by a small group of technical specialists. It will be driven by how broadly capability is distributed across the workforce.
If AI adoption remains uneven, Utah doesn’t just face a skills gap; it creates a participation gap that becomes a productivity gap, a wage gap, an advancement gap, and ultimately, a growth constraint. Because when only part of the workforce is enabled, the entire economy slows.
The companies pulling ahead
With this outlook, the organizations gaining an advantage right now are not the ones experimenting with AI tools — they’re redesigning work at the task level. They’re expecting AI fluency across roles, not just in engineering. They’re training managers to lead in AI-enabled environments, and measuring adoption like they measure revenue.
In these companies, a marketer can generate and test campaigns in hours, an operations leader can model scenarios instantly, a product team can move from concept to prototype in days. When companies build AI into their workforce, more people are capable of contributing at a higher level.
The bottom line
The story of AI is not just about what technology can do. It’s about who gets to do the work that matters next. If Utah gets this right, it fills our workforce gaps, accelerates economic growth, expands opportunity across industries and strengthens household income and long-term stability.
If we don’t, our growth will slow, our talent shortage will deepen and opportunities will concentrate instead of expanding.
AI isn’t removing the need for people; it’s raising the bar for participation. The question for leaders is no longer, “How do we adopt AI?” It’s “Who are we enabling to succeed in an AI-driven economy, and who are we leaving behind?”
In this next phase of growth, the companies — and the regions — that win will not be the ones that automate the fastest. They will be the ones that expand who can contribute to building the future.