AI Is Picking Who Gets Hired—Research from Drexel University Reveals How to Get Picked

Artificial intelligence isn’t just changing the way we work; it’s changing who gets to work in the first place.

Today, algorithms decide whether your resume even reaches human eyes. Studies show that more than 90% of employers now rely on automated tools — from applicant tracking systems (ATS) to AI-driven platforms like HireVue or LinkedIn Recruiter — to filter and rank job applications.

And it doesn’t stop at hiring, as it extends towards workforce management, too. Tech leaders like Accenture, IBM, and Amazon have already restructured teams to make room for AI capabilities, proving that AI is redefining not only who gets the job but also who gets to keep it.

Overall, this tremendous shift isn’t about robot taking jobs; it’s about algorithms redefining which jobs will evolve and which new ones will emerge to meet ever-changing industry needs.

To stand out, you can’t just tailor your resume for recruiters. You have to optimize it for algorithms. That means learning how AI evaluates candidates and more importantly, building the skills that make the algorithm want to pick you.

The AI-driven job market no longer rewards degrees and static credentials alone. Instead, it prioritizes people who can learn fast, adapt faster, and use AI to solve problems.

In his analysis for Silicon Republic, Murugan Anandarajan, researcher professor at Drexel University’s LeBow College of Business, identifies several key skill clusters defining employability in the age of automation. These insights are drawn from the Data Integrity & AI Readiness Survey and College Hiring Outlook Survey.

The first is AI and digital literacy — the ability to understand and apply AI tools in real-world workflows. Whether it’s automating repetitive tasks, prompting AI systems effectively, or simply knowing how these tools operate, literacy in AI is now as basic as computer literacy was 20 years ago.

Next comes data and analytical thinking. As algorithms filter more business decisions, employers are looking for people who can interpret patterns, measure results, and make data-backed choices. Demonstrating this is as simple as quantifying outcomes on your resume, such as saying you boosted a key metric by Y% using X data, instead of simply listing Excel or SQL proficiency.

Anandarajan also introduces the concept of human–AI fluency, referring the ability to “work with smart systems, question their results and keep learning as things change.” This particular fluency is inextricably linked to adaptability and learning agility, as it showcases how workers learn new skills and tools to adapt to a new role and future-proof their careers.

Overall, simply listing a degree or certificate may no longer suffice. It is imperative to describe what you can do with new technologies like AI to fully harness their potential in the workplace.

Even as AI takes a larger role in screening and hiring, human skills remain a differentiator.

More than just hiring people who are adept with AI, employers want people who can think with and beyond it. Thus, creativity, critical judgment, and emotional intelligence have become essential complements to technical fluency — the same skills that allow you to blend machine intelligence with human insight.

Anandarajan thus points to the rise of hybrid roles, such as AI translators, who bridge the gap between data scientists and business leaders, and digital coaches, who help teams adopt intelligent systems effectively. These jobs exist because people still need to interpret and apply what AI can’t fully understand: human context.

To reflect that balance, focus your resume and portfolio on impact storytelling: describe what you built, how you built it, and what changed because of it instead of simply stating the job description. That’s what both the algorithm and the hiring manager will notice.

The landscape of work is evolving faster than ever, and the skills in demand today might not be the same ones AI values next year.

To stay visible in an algorithm-driven world:

• Pick one of the core skill clusters — AI literacy, data fluency, adaptability, or human–AI collaboration — and deepen it with a micro-course, side project, or certification.
• Refresh your resume or LinkedIn profile every 3–6 months to reflect what you’ve learned and achieved.
• Stay curious. Experiment with AI tools that can streamline your daily work — even simple ones like ChatGPT, Notion AI, or Perplexity.

Ultimately, getting picked by AI isn’t about outsmarting the system. It’s about aligning with it. Showing that you can think, adapt, and grow alongside the very technology shaping the future of work matters now more than ever.

Because in the age of intelligent hiring, the smartest move you can make is learning how to work with the machine — not against it.