LocalWork News

Category: ATS & Recruiting Tech

News and analysis on applicant tracking systems and recruiting technology platforms

  • AI Video Interview Tools Face New Bias Audits as Regulators Take Notice

    Vendors of AI-driven video interview and resume-screening tools are facing increased pressure to prove their systems don’t discriminate against protected groups. Several jurisdictions now require independent bias audits before automated hiring tools can be used on candidates, and more are considering similar rules.

    In response, a number of ATS and screening vendors have begun publishing audit summaries and adding “explainability” features that show recruiters which factors influenced a candidate’s score. Some vendors are also giving candidates the option to request a human review of an automated decision.

    HR and compliance teams say the extra transparency is a welcome step, but note that keeping up with a patchwork of state and local disclosure rules is becoming a real administrative burden for multi-state employers.

  • New Research: Candidates Who Apply Through Mobile Devices Have 34% Lower Offer Acceptance Rates

    A new study examining 4.2 million job applications across 280 employer career sites has uncovered a troubling data point for talent acquisition teams: candidates who complete applications on mobile devices accept job offers at significantly lower rates than those who apply on desktop. The gap — 34% lower acceptance rates for mobile applicants — persists even after controlling for job type, compensation level, and geographic market.

    The research, conducted by a workforce analytics firm in partnership with three large enterprise ATS vendors, suggests that friction in the mobile application experience creates a negative first impression that colors candidates’ perception of the employer throughout the hiring process.

    The Candidate Experience Problem

    Despite years of conversation about mobile-first recruiting, the study found that 68% of employer career sites still require candidates to upload a resume file — a task that is significantly harder on mobile — and 54% include form fields that do not render correctly on smartphone screens. Average mobile application completion time was 22 minutes, compared to 14 minutes on desktop.

    ATS vendors are responding. Several platforms announced updates this quarter that enable one-tap applications using LinkedIn or Indeed profiles, reducing friction for mobile candidates. Employers who deployed these integrations saw mobile offer acceptance rates improve by an average of 19 percentage points.

  • AI-Powered ATS Platforms Are Reshaping How Recruiters Screen Candidates in 2026

    The applicant tracking system market is undergoing a significant transformation as artificial intelligence moves from a buzzword to a core feature of enterprise recruiting software. Major ATS vendors are racing to integrate large language model capabilities that can parse resumes, score candidates, and even predict cultural fit — all before a human recruiter reviews a single application.

    Industry analysts estimate that AI-enhanced ATS platforms now account for more than 40% of new enterprise software sales in the HR tech segment, up from just 18% two years ago. The acceleration has been driven by talent acquisition teams under pressure to reduce time-to-fill metrics while simultaneously improving quality of hire.

    Key Developments

    Several platform updates have made headlines this quarter. Greenhouse announced expanded AI screening capabilities that allow hiring managers to define custom evaluation criteria in plain language. Workday added real-time bias detection to its candidate scoring algorithm following pressure from enterprise customers focused on DEI compliance. Lever, now part of Employ Inc., launched a predictive analytics dashboard that forecasts pipeline conversion rates at each hiring stage.

    Not everyone is cheering. A growing coalition of labor advocates has raised concerns about algorithmic discrimination, citing studies showing that AI screening models can perpetuate biases embedded in historical hiring data. The EEOC is currently reviewing its guidance on AI use in employment decisions, with a final rule expected later this year.