By Murugan Anandarajan*
The consulting company Accenture while . This is a stark reminder that the same technology that drives efficiency is also redefining what it takes to hold down a job.
And Accenture is not alone. IBM has already replaced hundreds of roles with AI systems, while creating new jobs in sales and marketing. Amazon has cut staff even as it expands teams that create and manage AI tools. In every industry, from to to , workers and managers are trying to understand which roles will disappear, which will evolve, and which new ones will emerge.
I’m at Drexel University, studying how technology changes work and decision-making. My students often ask how they can stay employable in the age of AI. Executives ask me how to build trust in a technology that seems to advance faster than people can adapt to it. Ultimately, both groups are really asking the same thing: What skills are most important in an economy where machines can learn?
To answer this question, I analyzed data from two surveys my colleagues and I conducted this summer. In the 1st, we asked 550 companies across the US how they use and invest in AI.
For #2, we looked at how 470 employers viewed entry-level hiring, workforce development, and AI skills in candidates. These studies show both sides of the equation: those who are developing AI and those who are learning to work with it.
AI is everywhere, but are people ready?
More than half of organizations told us that AI now drives daily decision-making, but only 38% believe their employees are fully prepared to use it. This gap is reshaping today’s job market. AI is not just replacing workers; she is revealing who is prepared to work with her.
Our data also shows a contradiction. Although many companies now rely on AI internally, only 27% of recruiters say they are comfortable with candidates using AI tools for tasks like writing resumes or researching salary ranges.
In other words, the same tools that companies rely on to make business decisions still raise questions when job seekers use them to advance their careers. Until this view changes, even skilled workers will continue to receive mixed messages about what “” actually means.
In the Data Integrity and AI Readiness Survey, this readiness gap was most evident in operational and customer service jobs like marketing and sales. These are the same areas where automation is advancing rapidly and layoffs tend to occur when technology evolves faster than people can adapt.
At the same time, we found that many employers have not updated their degree or credential requirements. They are still hiring based on yesterday’s resumes, while tomorrow’s jobs require fluency in AI. The problem is not that people are being replaced by AI, but that technology is evolving faster than most workers can adapt.
Fluency and confidence: the true foundations of adaptability
Our research suggests that the skills most closely linked to adaptability share a theme, which I call “human AI fluency.” This means being able to work with intelligent systems, question their results, and keep learning as things change.
Across businesses, the biggest challenges lie in scaling AI, ensuring compliance with ethical and regulatory standards, and connecting AI to real business objectives. These obstacles are not about coding, they are about common sense.
In my classes, I emphasize that the future will favor people who can transform machine output into useful human insights. I call this digital bilingualism: the ability to fluently navigate both human judgment and machine logic.
What management experts call “reskilling” – or major changes to an old role – works best when people feel safe to learn. In our study, organizations with strong governance and a high level of trust were almost twice as likely to report gains in performance and innovation.
Data suggests that when people trust their leaders and systems, they are more willing to experiment and learn from mistakes. In this way, trust transforms technology from something to be feared into something to learn from, giving employees the confidence to adapt.
According to , about 86% of employers now offer in-house or boot camps online, but only 36% say AI-related skills are important for entry-level roles. Most training still focuses on traditional skills rather than those needed for new AI jobs.
The most successful companies make learning part of the job itself. They create learning opportunities on real projects and encourage employees to experiment. I often remind leaders that the goal is not just to train people to use AI, but to help them think along with it. This is how trust becomes the foundation for growth and how reskilling helps retain employees.
New hiring rules
In my opinion, leading AI companies are not just cutting jobs; they are redefining them. To be successful, I believe companies will need to hire people who can connect technology with common sense, question what AI produces, explain it clearly, and turn it into business value.
In companies that are putting AI into practice more effectively, hiring is no longer just about resumes. What matters is how people apply traits like curiosity and common sense to smart 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 how to work with intelligent systems. Each of these roles connects human common sense with artificial intelligence, showing how the jobs of the future will combine technical skills with human insights.
This combination of insight and adaptability is the new competitive advantage. The future will not only reward the most technical workers, but those who can transform intelligence – human or artificial – into real value.
