AI in recruiting: Why 10,000 jobs were cut this year and what you can do next

A new report from Challenger, Gray & Christmas attributes more than 10,000 job cuts so far in 2025 to generative artificial intelligence. CBS News unpacked the data, spoke with experts, and explored what this means for workers — especially recent college graduates — and for the future of hiring. In this article I’ll break down the numbers, explain which roles are most at risk, and offer practical steps for jobseekers, hiring managers and recruiters navigating AI in recruiting and the broader labor shift.

What the numbers say: 10,000 jobs and the rise of generative AI

The headline is stark: more than 10,000 jobs cut this year and specifically attributed to AI by an outplacement firm. Challenger, Gray & Christmas tracked layoffs and announced that employers have cited AI as the primary reason for a substantial portion of workforce reductions during the first seven months of 2025. Those numbers are not theoretical projections — they represent real people losing positions as companies integrate generative AI tools into workflows.

Here are the core data points that stood out in the reporting:

• Over 10,000 jobs cut in 2025 linked by companies to AI adoption.
• Many of those cuts concentrate in the tech sector, where AI accelerates coding, debugging, and other software tasks.
• Entry-level and repetitive roles are especially vulnerable, making it harder for recent graduates to find their first jobs out of school.

Who’s getting hit hardest?

Not every industry or role is affected equally. In the interviews and reporting I conducted, three groups emerged as particularly at risk:

1. Tech workers focused on routine coding and automation tasks. Generative AI can write, refactor and even debug code, which reduces demand for certain junior engineering tasks.
2. Entry-level roles with repetitive responsibilities. Jobs that historically served as first steps into the workforce — data entry, basic content production, some customer service functions — are increasingly automated.
3. Recent college graduates seeking their first role. According to career platform data I discussed, job postings aimed at new grads are down about 15% while applications to those jobs have surged about 30%, creating intense competition.

That dynamic has led to what I described in the segment as “concentration remorse” — young professionals regretting a majors or career path that once reliably led to opportunities. The harsh reality is that fields long advertised as gateways to secure careers now face disruption, and that is reshaping early-career expectations.

Context matters: AI isn’t the only factor

It’s important to avoid an oversimplified narrative that AI is the sole cause of every layoff. As I emphasized during the conversation, companies cite multiple pressures: tariffs, changing policy, rising costs, and economic uncertainty. Those factors cause firms to pause investments and hiring decisions. When businesses look to cut costs, labor is often the most immediate lever they pull.

So while the report explicitly attributes many cuts to AI, the truth is often a mix of structural and cyclical forces. For example, importers in the retail industry face higher projected costs due to tariffs and supply chain shifts; that can shrink margins and force hiring freezes or layoffs even without direct AI substitution.

What leaders are saying: a cautious optimism

"AI gives you a place to go that we've never been able to go before… Now you're able to maybe use a machine to enhance an activity. So we believe that people harness AI for their benefit are gonna be very successful." — Bank of America CEO

That line captures a common executive perspective: AI can create new possibilities, but those possibilities often require different skills. Many leaders argue that the best path forward is “human + AI” — upskilling workers to use AI tools to amplify productivity rather than simply replacing them.

That’s not a universal outcome. The pace of adoption and the specific tasks automated will determine whether workers are augmented or displaced. For many organizations, early wins from AI have come from automating coding tasks, generating first drafts of content, or handling routine customer interactions — work that often sits at lower experience levels.

What jobseekers can do now

If you’re starting your career or reevaluating your path, here are practical steps you can take to remain resilient in the era of AI in recruiting and broader workforce change:

• Develop AI literacy. Learn the basics of generative AI tools relevant to your field — whether that’s code-generation assistants for developers, writing tools for marketers, or automated screening and sourcing platforms for HR professionals.
• Emphasize uniquely human skills. Communication, critical thinking, leadership, judgment, ethics, and relationship-building remain hard to automate. Your ability to collaborate, manage complexity, and provide contextual decision-making is valuable.
• Build a portfolio that shows impact, not just tasks. Employers want evidence that you can drive results. Case studies, measurable outcomes and demonstrable project value trump resume bullet points that could be generated by an AI.
• Upskill strategically. Prioritize areas that complement AI — data analysis, prompt engineering (crafting useful prompts to get accurate AI outputs), model oversight, and domain-specific expertise.
• Consider apprenticeship and hybrid roles. Organizations are experimenting with roles that mix human oversight and AI work; these can be gateways to longer-term opportunities.

All of these actions help jobseekers in two ways: they make candidates more attractive to employers using AI in recruiting, and they reduce the risk that a role you pursue is easily automated away.

How AI is changing hiring: practical implications for recruiters

For hiring teams and recruiters, AI in recruiting is already reshaping candidate sourcing, screening, and outreach. Tools that parse resumes, generate outreach messages, and rank candidates based on algorithmic profiles are in widespread use. That introduces both efficiencies and new responsibilities:

• Efficiency gains: Recruiters can surface candidates faster, personalize outreach at scale, and automate administrative workflows.
• Bias and auditability: Systems trained on historical data can perpetuate bias. Recruiting teams must audit algorithms, maintain transparency, and include human oversight.
• Candidate experience: Automation can speed processes, but impersonal AI-driven interactions can harm employer brand. Balance speed with human touchpoints.
• Skill definition: With AI handling basic tasks, role descriptions should emphasize higher-order problem-solving, domain knowledge and collaborative skills.

Recruiters who understand AI in recruiting — how tools work, their limits, and their compliance risks — will be best positioned to attract top talent and to craft roles that are resilient to automation.

Policy and employer responsibilities

Beyond individual strategies, there are systemic responses that can help mitigate disruption. In the reporting I did, employers and policymakers need to consider:

• Retraining and upskilling programs. Employers that invest in internal training are more likely to retain staff and redeploy talent into higher-value roles.
• Safe transitions. Severance, placement support and partnerships with community colleges or bootcamps smooth labor-market shifts.
• Regulatory guardrails. Transparency requirements for AI use in hiring and sectoral support for displaced workers can reduce harm.

Designing these policies requires coordination between businesses, educators and government. Left to market forces alone, transitions can be abrupt and inequitable.

Final thoughts: adapt, advocate and stay informed

Generative AI is reshaping hiring and the workplace in real time. The 10,000-plus jobs tied to AI this year are a wake-up call, especially for early-career workers and routine-heavy roles. But disruption also creates opportunity. Workers who learn to use AI tools to amplify their impact, who double down on human skills, and who can translate domain expertise into measurable results will be in demand.

For recruiters and hiring managers, the imperative is twofold: use AI responsibly to make hiring better and more inclusive, and design roles that cannot be easily offshored to a machine. That is where sustainable value lies.

If you’re navigating the job market, keep these three priorities front and center: learn to work with AI, document your impact, and connect with mentors and programs that help you upskill. For employers, invest in your people or risk losing institutional knowledge and trust.

Resources and next steps

If you want to keep following this topic, I encourage you to subscribe to trusted reporting and to explore practical training options: online courses in data literacy or prompt design, apprenticeships, and community college certificates. Watch for transparency reports from recruiters and employers about how they use AI in hiring, and ask questions during interviews about how teams use AI and what training they provide.

AI in recruiting will continue to evolve. My goal in reporting on this story is to give you context, concrete steps and a realistic sense of what’s changing — and how to respond. Stay curious, stay proactive, and keep learning.