Massive layoffs announced at Amazon.com Inc. recently serve as a reminder that artificial intelligence technology driving efficiency is also redefining what it takes to keep a job.
Across industries, workers and managers alike are trying to understand which roles will disappear, which will evolve and which new ones will emerge.
I research and teach at Drexel University’s LeBow College of Business, studying how technology changes work and decision-making. Students often ask how they can stay employable in the age of AI. Executives ask how to build trust in technology that seems to move faster than people can adapt to it. In the end, both groups are really asking the same thing: Which skills matter most in an economy where machines can learn?
I analyzed data from two surveys my colleagues and I conducted over the summer. For the first, the Data Integrity & AI Readiness Survey, we asked 550 companies how they use and invest in AI. For the second, the College Hiring Outlook Survey, we looked at how 470 employers viewed entry-level hiring, workforce development and AI skills in candidates.
More than half of organizations told us that AI now drives daily decision-making, yet only 38% believe their employees are fully prepared to use it. This gap is reshaping today’s job market. AI isn’t just replacing workers; it’s revealing who’s ready to work alongside it.
This readiness gap showed up most clearly in customer-facing and operational jobs such as marketing and sales. These are the same areas where automation is advancing quickly, and layoffs tend to occur when technology evolves faster than people can adapt.
At the same time, we found that many employers haven’t updated their degree or credential requirements. They’re still hiring for yesterday’s resumes while tomorrow’s work demands fluency in AI. The problem isn’t that people are being replaced by AI; it’s that technology is evolving faster than most workers can adapt.
Our research suggests that the skills most closely linked with adaptability share one theme, what I call “human-AI fluency.” This means being able to work with smart systems, question their results and keep learning as things change.
Across companies, the biggest challenges lie in expanding AI, ensuring compliance with ethical and regulatory standards and connecting AI to real business goals.
In my classes, I emphasize that the future will favor people who can turn machine output into useful human insight. I call this digital bilingualism: the ability to fluently navigate both human judgment and machine logic.
What management experts call “reskilling” works best when people feel safe to learn. Organizations with strong governance and high trust were nearly twice as likely to report gains in performance and innovation. The data suggests that when people trust their leaders and systems, they’re more willing to experiment and learn from mistakes.
The most successful companies make learning part of the job itself. They build opportunities to learn into real projects and encourage employees to experiment. I often remind leaders that the goal isn’t just to train people to use AI but to help them think alongside it.
The companies leading in AI aren’t just cutting jobs; they’re redefining them. To succeed, companies will need to hire people who can connect technology with good judgment, question what AI produces, explain it clearly and turn it into business value.
In companies that are putting AI to work most effectively, hiring isn’t just about resumes anymore. What matters is how people apply traits such as curiosity and judgment to intelligent tools. I believe these trends are leading to new hybrid roles such as AI translators, who help decision-makers understand what AI insights mean and how to act on them, and digital coaches, who teach teams to work alongside intelligent systems.
That blend of judgment and adaptability is the new competitive advantage.
Murugan Anandarajan is a professor of decision sciences and management information systems at Drexel University. Distributed by The Conversation and The Associated Press.
