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The new rules for getting hired in an AI-driven job market
The rise of AI is reshaping the job market, leaving many workers, particularly early-career professionals, at a disadvantage. Layoffs that companies have attributed to AI accounted for 25% of all US job cuts in March 2026 and have contributed to a steady erosion of entry-level and mid-level openings.
Beneath the surface, a more nuanced shift is occurring. In Q1 2026, demand for experienced technology and professional services personnel increased by 10.5% quarter over quarter and 6.4% year over year, according to a new report from professional services firm Toptal.
The result is a labor market increasingly split between work that can be automated and work that requires high-level judgment and technical expertise to collaborate effectively with AI. But in this article, Toptal outlines concrete steps that junior-level and mid-career workers can take to adapt and stay competitive.
The Evolving Entry-level Career Path
Career paths have generally followed a simple progression: Enter the workforce in a junior role, build expertise over time, and gradually move into more senior, strategic positions. AI is narrowing that pathway, and the effects are measurable. According to the Burning Glass Institute, young college graduates now face an unemployment rate that is rising faster than any other group.
Because generative AI tools can perform many basic tasks, including drafting content, summarizing information, writing code, analyzing data, and managing workflows, companies are reassessing how many entry-level workers are actually needed. Between December 2025 and February 2026, entry-level hiring fell 6% compared to the same period the year before, and hiring for mid-level managers fell 10%. Employers are placing greater emphasis on hiring experienced professionals who can apply AI to business problems rather than execute repetitive tasks.
Toptal
Joint research from Harvard Business School and The Burning Glass Institute suggests that AI-driven automation could eliminate nearly 18 million entry-level positions, roughly 12% of the total workforce.
New Opportunities for Adaptable Workers
The news isn’t all bad: The Harvard and Burning Glass research also points to the emergence of a whole segment of positions that are likely to open up to entry-level workers and job changers, because of AI. For these so-called “mastery roles,” AI lowers technical skill barriers by enabling less-experienced people to do more complex work sooner, using natural language to prompt AI tools that can help accomplish tasks that once required years of specialized training.
The researchers estimate that roughly 29 million of these mastery roles exist across the US economy, including network administrators, data warehousing specialists, loan interviewers, construction managers, electrical drafters, and systems engineers.
Toptal
The result of this AI enhancement is that certain well-paid, high-demand careers could become more accessible to workers at any level who can effectively use AI systems to augment their capabilities. This doesn’t mean anyone can instantly become an expert, but it does mean more people can participate in high-value technical work by using AI to augment what they already do well.
What Workers Need to Do Now
A growing number of companies are expecting new hires to arrive with stronger AI-related and technical skills, according to the Toptal report. “Companies increasingly want proof that candidates are actively using AI in practical ways, not just saying they’re familiar with it,” says Erik Stettler, Toptal’s chief economist. For developers, that might mean GitHub contributions or open-source projects. For other professionals, it could mean building workflows, publishing projects, documenting experiments, or showing how they’ve used AI to improve outcomes in their work.
The people who stand out in the hiring process now are the ones who are already experimenting, adapting, and learning how to apply these tools in real-world environments, says Stettler. His advice is simple: Pick one or two AI platforms and start using them in practical ways applicable to your field or a growing field that you are interested in pursuing. Stettler recommends the following five steps to improve your odds of being hired in the current AI-driven job market:
- Build at least one public AI-related project. That could mean publishing on GitHub, creating short demo videos, or documenting a 30-day experiment using AI tools on LinkedIn with regular posts tracking what worked and what didn’t. Even using AI to build a simple personal website from scratch and writing about the process is worth sharing.
- Learn an automation workflow relevant to your target industry, using ChatGPT, Claude, Zapier, Make, Airtable, Notion AI, Microsoft Copilot, or Google Gemini. For example, a construction manager might use Airtable with AI to track schedules, flag delays, and send deadline reminders, while an accountant or auditor might use Notion AI or other tools to organize documentation and help surface anomalies for review.
- Add measurable AI-related outcomes to portfolios and resumes. Recruiters want to see specifics like, “Used AI-assisted targeting and analytics tools to increase campaign conversion rates by 18%.” Even entry-level workers can document AI-assisted outcomes, such as tracking time saved on a task or using AI to identify patterns in a dataset that informed a real decision.
- Develop AI literacy alongside communication skills. Learn how generative AI tools work, their risks and limitations, how to evaluate outputs, and where human judgment is still needed. Free courses from Google and Coursera, as well as the University of Helsinki’s Elements of AI program, are all good starting points.
- Gain hands-on experience through freelance and contract work, or by volunteering. Organizations like Catchafire and Idealist connect people with nonprofits looking for specific skills, and that work makes for legitimate additions to your resume.
Stettler cautions that many workers risk paralysis by trying to figure out the “right” AI model, workflow, or platform before they begin. The better approach is to start now, experimenting and documenting processes along the way.
AI is disrupting many traditional career paths. It’s also reshaping which skills create value and how quickly workers can acquire them. For professionals navigating this transition, the challenge is learning how to evolve alongside systems that are changing the nature of work itself.
This story was produced by Toptal and reviewed and distributed by Stacker.
