AI-Powered Tools May Make it Even Harder to Find a Job – Time

Entering 2025, underlying the calm surface of the U.S. labor market were currents of anxiety, dissatisfaction, and stagnation. Companies were taking longer to fill open roles, and a growing numbers of employees were disengaged but staying in their roles out of concern it would be difficult to find something better.

Now, President Donald Trump, Elon Musk, and their Department of Government Efficiency have laid off thousands of federal employees. These workers are now re-entering the job market. Plus, companies and employees alike are trying to anticipate the impact of rollicking financial markets thanks to constant changes in tariffs. This economic tumult is bringing the stormy currents of the labor market to the surface.

In the face of these challenges, many job seekers are turning to new AI-powered apps meant to help them find jobs. But ironically, these tools are likely to exacerbate the present challenges and make it harder, not easier, to find jobs.

To understand why AI tools designed to help individuals apply to jobs will make the job market more challenging to navigate, it helps to understand the history of those tools and how companies actually hire people today.

AI isn’t a new phenomenon in the job-application process. Its mainstream use began on the employer side when companies deployed AI-powered tools in the 2010s to filter through the hundreds of job applications they were receiving for open online job postings.

The AI tools baked into these applicant tracking systems—software that companies use to manage the hiring process—looked for matches between the words on incoming resumes and those in job descriptions. If there was enough of a match, then a job seeker’s resume likely made it through the filter.

On its face, this seemed to offer an advantage to companies over job seekers. In reality, although companies did use these tools to winnow their hiring funnels, most actual hires weren’t made from the pool of people applying online without a connection to the hiring manager. 

Instead, despite the democratization of job postings online, estimates suggest that well over half of jobs—and perhaps as high as 85%—are still found through personal connections. This is due in no small part to a lack of trust that job seekers and companies have in each other when interacting online.

Online job descriptions today have become a long list of skills, qualifications, and platitudes about work style and culture cribbed from past job descriptions, competitors’ postings, and requirements for pay and title grading at the desired level of the role. They have become so vague and meaningless that roles can be impossible to fill as described. Think of the myriad entry-level postings that call for “two years of experience,” for example. Or all the job descriptions that require college degrees—even when current employees in the same roles lack them. Indeed, if you peruse enough job postings, you sometimes get the feeling that employers are seeking employees who do not exist.

Simultaneously, as AI-powered applicant tracking systems sort out individuals that don’t match the desired skills, experiences, and characteristics listed in these job descriptions, prospective employees have learned to embellish their resume and make themselves look like superheroes. In order to get past AI-powered gatekeepers, it has become common for applicants to exaggerate their experiences.

This cycle has generated mistrust in the resumes and cover letters coming in from the internet. As a result, managers often prefer to source candidates through a referral they can trust from someone they know. Sure, that might mean it takes longer to fill open roles. But the delay can be worth it from a company’s perspective if it results in a better match.

The consequence of this dynamic is that as job seekers begin using AI tools to apply to jobs online, it’s unlikely to help them. It’s actually likely to send the job market into an AI-driven hiring doom loop—the result of which will be employers relying on their personal networks for hiring even more.

According to a recent survey by Canva, 45% of global job seekers use AI to create and fine-tune their resumes and cover letters. And a growing number of job seekers are doing something more radical: They are using AI-powered tools like LazyApply and JobCopilot to apply directly to open jobs on their behalf. But unfortunately, positive experiences with these AI-powered apps tend to be the exception, not the rule.

As more job seekers leverage these automated application tools, it may become even more difficult for job seekers to find a job online because they will flood hiring managers with more applications than they could ever consider. Employers that were receiving hundreds of applications for open roles already tell us that they now receive thousands. With even less trust in the AI-tailored resumes pouring in, companies are likely to rely on personal connections even more to help them find employees.

Hiring processes that overly rely on personal connections creates problems—both for companies and job seekers. Companies seeking to boost the diversity of their funnel by gathering large numbers of applicants will likely continue to end up with new hires in similar social circles as their existing employees.

Network-based hiring has downsides for job seekers as well. If getting a job is all about who you know, those with limited networks are often left out. As Harvard University’s Raj Chetty’s Opportunity Insights research has shown, networks are strongly based in class—particularly at the top. This means that individuals from low socio-economic backgrounds often have significantly fewer high-income connections. And given the number of jobs filled by who you know, that means that low-income Americans are less connected to higher paying opportunities in the workforce.

If these personal connections become even more important when looking for a job, individuals must beef up their networks—not just on social media or with AI bots, but in real life.

To be sure, networking can “feel dirty,” but as AI makes the job search process more difficult, it will be increasingly critical. So what to do? Rather than connecting with a potential member of your network with the explicit goal of asking for a job, make a habit of being curious about the work other professionals do. Talk with people who hold roles that interest you to learn about what they do on a day-to-day and week-to-week basis.

The focus, in other words, should be about learning and growth. Over time, you will expand your network and learn about the roles that are good fits for you, your unique skills and experience, and the types of work that energize you.

The goal should be to become a self-aware individual who understands what opportunities are out there, recognizes what they bring to the table, and demonstrates real interest in others. That will, in turn, set you apart as someone worth recommending by those that others trust—which is something AI can’t do.