AI’s job shakeup hits faster than workers can adapt

AI’s job – A leadership veteran working across Verizon and HCLTech says AI is changing employment with “remarkable” speed—cutting roles in some areas while creating new ones in others. In a conversation centered on real career moves, Shelly Ashwill points to layoffs, job

The first quarter of 2026 has barely ended, yet already the message for many workers is landing with unusual force: the ground rules are shifting—fast.

Shelly Ashwill. a leadership veteran with more than three decades across Verizon and HCLTech. says the speed and scale of change is what makes the moment so unsettling for today’s workforce. She describes AI’s impact as immediate. not theoretical. and points to figures showing how quickly companies are rethinking roles and responsibilities.

In the first quarter of 2026 alone, the tech industry reportedly laid off 80,000 workers globally, with about half of those layoffs linked to AI or automation. Goldman Sachs economists estimate AI is reducing U.S. payroll growth by around 16,000 jobs monthly in AI-exposed industries.

Those numbers catch attention, Ashwill said—but she also argues that they don’t fully explain what comes next. The broader picture, she says, is that job churn is set to be enormous.

The World Economic Forum estimates AI will affect 92 million jobs globally by 2030. At the same time, it projects 170 million new roles could be created, which would translate to 80 million net new jobs over the next several years.

For Ashwill, the heart of the issue isn’t whether work will disappear. It is how work will change.

As she puts it. several forces are pushing the shift beyond AI itself: populations are growing. people live longer and many will remain in the workforce later in life. and technological progress is creating new types of roles. Inside AI adoption, she says, entirely new job categories are already emerging—positions that train, manage, and govern these systems. AI trainers, governance and compliance specialists, and prompt engineers are becoming important as organizations move to adopt AI responsibly.

“The key takeaway?” Ashwill says. “AI is transforming work, not simply eliminating it.”

For employees in technology, that framing translates into a straightforward pressure point: adapt now. Ashwill’s advice starts with a self-assessment—skills and experience, but also how clearly someone can show that they understand and use AI tools.

She urges workers to ask whether they can demonstrate how they use AI tools in their work. whether they feel comfortable discussing AI experience in interviews. and whether they’ve taken courses or earned certifications to strengthen their understanding. In her view. employers increasingly want professionals who combine technical awareness with human strengths—critical thinking. data literacy. emotional intelligence. and clear communication.

The practical message is blunt: workers will need to keep their skills relevant as the job market evolves. The professionals most likely to succeed, she says, are those who invest in learning and can articulate the value they bring to their organizations.

Ashwill also emphasizes that AI education doesn’t have to be a major life overhaul. Her recommendation is to dedicate a small portion of time weekly to learning AI. She highlights short. focused learning programs and the appeal of micro-learning formats such as 30-day courses or bite-sized modules that fit into busy schedules.

She points to platforms like Coursera, Udemy, and IBM for AI course options. For ongoing updates, she mentions newsletters such as The Rundown AI and TLDR AI. Certifications, she adds, can be added to LinkedIn to signal continued learning.

When turning learning into work-ready skills. she says professionals should focus on practical steps: identify routine tasks like drafting emails. conducting research. or preparing reports where AI can assist; learn to write effective prompts by providing clear instructions and thoughtful context; treat AI as a thought partner to brainstorm. refine drafts. and explore new perspectives; and build workflows that connect tasks together to boost productivity when creating reports. analysis. or insights. Experimenting with different tools matters. too. she argues. because each platform has unique strengths and learning how they fit a personal workflow is part of the process.

Once those habits become routine, she says, productivity gains can increase significantly.

That need for adaptation extends beyond individual workers to how teams are managed. Ashwill says leaders have a critical role in helping employees navigate rapid technological change. She points to a “practical limit” on how much information people can absorb. stressing that employees cannot be expected to master every new tool that emerges.

What they need instead, she says, are leaders who guide change, model curiosity, and create an environment that supports continuous learning.

One strategy she recommends is learning together as a team: employees can explore specific use cases. then share what they discover across the broader group. Ashwill says this reduces uncertainty, builds confidence, and strengthens teamwork. She also argues that technology adoption rarely succeeds as a solo effort—when teams combine knowledge and perspectives. they’re more capable of developing innovative solutions.

AI, she adds, will reshape roles. But it also creates room for people who remain curious, adaptable, and committed to learning.

Larraine Segil, founder, chair, and CEO of the Exceptional Women Alliance, introduced the conversation as part of the nonprofit’s peer-to-peer mentoring community for high-level women focused on personal and professional success through sisterhood.

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