AI vs. AI: The Hiring Arms Race
How is the 'AI doom loop' — where companies' AI systems clash with candidates' own algorithms — affecting recruitment?
Mei Sullivan
A silent but massive race is currently underway in the world of hiring. On one side stand the AI systems companies use to screen thousands of applications in seconds; on the other, candidates deploying their own algorithms to beat those systems. This situation is referred to in the literature as the "AI doom loop," and it is transforming the hiring process from a human interaction into a technology war where two pieces of software battle each other. If your company fails to manage this loop correctly, you may be losing not just the most talented candidates, but also the reputation of your employer brand.
How are candidates "fighting back"?
Today's candidates know that getting past AI filters is now the first rule of finding a job. According to Nicole Jurado's (2025) study titled "The effects of artificial intelligence on shaping employer brand perception," a large proportion of candidates in the US actively use AI in their job search processes. Candidates are no longer just sending a simple resume; they are developing strategies to "hack" the AI-Powered Applicant Tracking Systems (ATS) companies use.
Some of the methods candidates employ include:
- Keyword optimization: They stuff their resumes with words that the company's AI "likes."
- AI-assisted preparation: According to data shared by Crist (2025), candidates use AI to practice interviews and create work samples.
- Automated applications: Data from the same research shows that candidates use tools that fully automate applications.
The AI loop: Erosion of trust
The greatest danger created by this situation is the disappearance of the "human" element on both sides of the process. The "AI doom loop" described by Crist (2025) warns that when both employers and candidates over-rely on automation, trust and quality in the hiring process decline. Companies receive thousands of AI-generated resumes, while candidates complain that the system on the other side sees them not as a human but merely as a data point.
According to interview results in Nicole Jurado's (2025) research, candidates interpret companies' over-reliance on AI as "laziness" and "avoiding investing in people." As one candidate put it: "If the company won't spend time on me, why should I spend time on them?" This causes the highest-quality candidates to quickly distance themselves from your brand.
Strategic responses and interview "theater"
Candidates are developing defenses against AI not just at the resume stage, but during interviews as well. The study titled "Behavioral Measures Improve AI Hiring" conducted by Marie-Pierre Dargnies and colleagues (2025) proves that candidates predict the company's "ideal employee" profile and "strategically" modify their answers accordingly. On topics like patience or risk management, candidates present not their true personalities but the personalities they believe the AI will score highly.
Things have even gone a step further. Research conducted by Md Nazmus Sakib and team (2018/2024) reveals that some candidates resort to "AI talking to AI." In this scenario, the candidate feeds the interview question to an AI, then feeds the response back to the interview system through a text-to-speech bot. This kind of "performance obligation" emotionally drains candidates and turns the process into a theater stage.
How do we break out of this loop?
The way to rescue hiring from this chaos is to design AI as a "bridge" rather than a "wall." As emphasized in the TestGorilla (2025) report, without human oversight (human in the loop), the AI loop quickly deteriorates. Allowing AI to make decisions on its own creates both ethical risks and reduces talent quality.
The winning strategy of the future may include these steps:
- Mandatory transparency: Candidates should be clearly told where and how AI is used.
- Hybrid models: AI should only handle certain screening and administrative tasks; humans should be involved in the evaluation phase.
- Quality analysis: As noted in Brian Jabarian and Luca Henkel's (2026) research, when AI interviews are balanced with human-led processes, new hire retention rates increase.
Conclusion: Technology that centers humans
Candidates view the balance a company strikes between AI and human interaction as a mirror of that company's values. Companies that focus solely on cutting costs and remove humans from the equation appear destined for criticism in this loop.
The right AI interview tool for your company should not be a "cold filter" that incentivizes candidates to game the system, but rather an "intelligent assistant" that reveals their true talents and offers deeper insights to HR professionals. The most successful teams of the future are built not by software, but by visionary leaders who use technology in the most human way possible.
References
- Crist, C. (2025). 1 in 3 companies say AI will run their hiring process by 2026. HR Dive.
- Dargnies, M. P., Hakimov, R., & Kübler, D. (2025). Behavioral Measures Improve AI Hiring: A Field Experiment. Working Paper No. 532, Collaborative Research Center Transregio 190.
- Jabarian, B., & Henkel, L. (2026). Voice AI in Firms: A Natural Field Experiment on Automated Job Interviews. Booth School of Business, University of Chicago.
- Jurado, N. (2025). The effects of artificial intelligence on shaping employer brand perception: insights from entry-level hiring practices. Master Thesis, Universidad Carlos III de Madrid.
- Sakib, M. N., Rayasam, N. M., & Dey, S. (2018/2024). Experience and Adaptation in AI-mediated Hiring Systems: A Combined Analysis of Online Discourse and Interface Design. University of Maryland.
- TestGorilla. (2025). Why 78% of candidates choose AI job interviews (and what it means for hiring). TestGorilla Insights.