AI's rise has made job interviews more grueling, due to a rise in technical tests, essays, and assignments, as recruiters struggle to find the right candidates
Efforts to push back against unsuitable mass applications are turning a dispiriting situation into a miserable one
Context & Ripple Effects
Automated screening had already pushed applicants toward increasingly tailored, time-consuming submissions, as reflected in earlier coverage of application-specific résumés. This report shows the burden moving further into the interview stage as recruiters seek better signals from large applicant pools.
The dynamic is a precursor to the later AI arms race between employers and jobseekers: tools that make applying easier can also make proving suitability more labor-intensive.
First-order effects
- Applicants face longer, more demanding hiring processes, including technical tests, essays and assignments.
- Recruiters shift more of the screening burden into work-sample-style assessments in an effort to distinguish suitable candidates from mass applicants.
Second-order effects
- Candidates must spend more unpaid time per application, which can discourage broad job searches and reward those able to absorb the added effort.
- Employers may face a trade-off: tougher assessments can improve filtering but also add review work and risk losing qualified candidates to faster processes.
Third-order effects
- If application-generation tools continue to increase application volume, recruiting is likely to become an escalating verification contest rather than a simpler matching market.
- The durable advantage may shift toward hiring systems that can assess genuine capability without imposing excessive work on candidates; whether that improves fairness depends on how assessments are designed and used.
The trend: Generative AI is turning recruitment into a reciprocal automation-and-verification cycle, with more effort pushed from submitting an application to demonstrating authenticity and skill.