Roundup: AI 'Arms Race' Grows Between Workers and Employers

The same companies who use AI to manage application volume are scrambling to detect its use by candidates.

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AI has spurred an arms race of sorts between candidates and employers, as each side looks for ways to both leverage the technology and identify when it’s being used to circumvent the generally accepted rules of talent acquisition. Among the issues employers confront is volume: Ars Technica reports LinkedIn today processes 45% more job applications per minute than it did a year ago. “Both sides [are] deploying increasingly sophisticated AI tools in a bot-versus-bot standoff that is quickly spiraling out of control,” the website said.

The same employers who use AI to manage application volume are now scrambling to detect its use when candidates craft resumes or cover letters, or even identify job opportunities and tweak their applications.

Although candidates have long used technology to refine their resumes, AI has disrupted hiring by allowing candidates to easily create hundreds of job applications, Ars Technica said, “turning what was once a time-intensive process of demonstrating interest into a numbers game that overwhelms businesses trying to find genuinely qualified applicants.” In turn, employers have deployed AI to uncover machine-generated application materials. In the end, the conversation becomes one of AI talking to AI, rather than candidates talking with employers.

At the same time, AI has enabled notable growth in the number of dicey applications. Employers are receiving more applications involving a false identity, while helping candidates “to game screening systems using prompt injections in ways human reviewers can't detect.”

All of this could lead employers to evolve their hiring process to focus less on resumes and more on approaches that make the use of AI difficult, things like live problem-solving sessions, portfolio reviews or trial work periods.

AI Evens the Playing Field for Employees

The rise of AI-powered copilots is evening the playing field for candidates and employees by providing them with much of the same market intelligence employers use routinely. In his Future of Work Weekly, Kevin Wheeler writes that by compiling labor market data, skills patterns and salary benchmarks, “these AI copilots [are able] to compare an employee’s skills and experience against a broader external market, rather than solely through the lens of one employer’s job structure and opportunities.”

That means employees can make more informed judgements of a company’s offer of either internal or external opportunities. “Such a shift dramatically reduces information asymmetry, giving employees greater confidence and more solid evidence when making career decisions or negotiating compensation,” Wheeler says.

Using such agents, workers can evaluate offers based on information besides what’s provided by the employer. Arguably, they can do that now, but compiling data on industry trends in hiring, compensation and future opportunities is a daunting task, even before one considers the sheer volume of data that’s out there. Companies like Rora, Career Copilot and Skyhive are developing “an expanding group of tools that help both candidates and current employees,” Wheeler said.

Wheeler said such products will pressure employers to be more transparent. At the same time, he notes copilots aren’t coaches, and users could still need humans to tackle subjects that don’t drop neatly into a data set. “The best models will blend human and AI guidance,” he said, “allowing each to complement the other rather than substituting one for the other.”

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News & Notes

Chief technology officers expressed less faith in their strategies for AI transformation. A report from Adecco’s engineering firm Akkodis found that executives’ confidence in AI strategy dropped from 69% in 2024 to 58% this year. CTOs’ confidence declined 20 points while that of CEOs fell by 33 points. That shows increasing concerns about scalability, implementation delays and a tangible ROI, the company said.

Only 55% of CTOs believe their leadership fully understand the risks and opportunities of AI, while 46% see an “AI trust gap” with employees. And while companies are investing more in employee learning around AI, Akkodis said training is often siloed and “disconnected” from business goals or role-specific needs. [Akkodis]

Payroll vendors are looking for ways to take advantage of the latest technology, particularly AI, to improve payroll processing outcomes. While some applications are still in the nascent stages for payroll, other use cases – such as conversational chatbots and enhanced employee self-service – are gaining traction, according to research by the Hackett Group. Payroll teams face a 7% increase in workload but a 2% decrease in budget. In particular, they’re turning to software solutions that provide enhanced automation and generative AI capabilities to alleviate operational pressure and ensure uninterrupted payroll delivery, the Hackett Group said.

Payroll organizations that engage with advanced software providers are realizing significant value, the report said. End users say an average 67% of their payroll process is fully automated, dramatically reducing workloads for payroll administrators. Additionally, 60% of end users report cost reductions for payroll processing. [BW]

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