AIHawk, a new AI-powered job application tool released in August 2024, is revolutionizing how job seekers apply for positions on LinkedIn—but not without significant risks and controversy. Created by 23-year-old Italian software engineer Federico Elia, the tool automates the application process for LinkedIn’s easy-apply jobs, allowing users to submit hundreds or even thousands of applications with minimal effort.
Elia developed AIHawk after finding his own job search “slow and boring” following graduation. The tool works by pulling information from a user’s LinkedIn profile and automatically applying to positions based on customized filters for role level, location, and job description keywords. “It was really efficient,” Elia told Business Insider. “I sent like 1,000 applications and received a lot of interview proposals.”
Since its publication on GitHub in August, AIHawk has gained massive traction, with over 20,000 users bookmarking the project and more than 6,000 members joining the AIHawk community on Telegram. The tool’s popularity reflects the challenging job market many Americans face, particularly in the tech sector, where hiring for IT roles has decreased nearly 20% since summer 2018.
However, using AIHawk comes with substantial risks. Early versions of the tool were found to add false information to résumés, including qualifications users didn’t possess. While recent updates have improved accuracy and now allow users to submit unmodified résumés, concerns remain about the tool’s compliance with LinkedIn’s terms of service, which prohibit third-party software that “scrapes or automates activity.”
LinkedIn has not directly addressed whether AIHawk violates its user agreement, though the platform did restrict Elia’s account in September. Users like Anthony Ettinger, a 49-year-old laid-off software engineer, and Tommi, a 28-year-old data engineer from Mexico City, report applying to 500-1,000 jobs respectively, with modest interview success rates.
The tool is free but requires coding knowledge and familiarity with Python, distinguishing it from paid alternatives like LazyApply ($99-$249). Following AIHawk’s success, Elia has partnered with six cofounders to launch AIHawk.co, aiming to develop a comprehensive job search platform. The GitHub page includes a disclaimer stating the tool is for “educational purposes only,” though thousands continue using it for actual job applications in an increasingly competitive labor market.
Key Quotes
It was really efficient. I sent like 1,000 applications and received a lot of interview proposals.
Federico Elia, the 23-year-old creator of AIHawk, described his experience using the tool after graduating. This quote demonstrates the tool’s effectiveness in generating interview opportunities through volume-based applications.
It’s a pretty good tool because applying to jobs is the most painstaking thing for candidates.
Anthony Ettinger, a 49-year-old laid-off software engineer who has struggled to find work since August 2023, explained why he continues using AIHawk despite its early problems with adding false information to résumés.
I can basically just leave it on autopilot applying for jobs.
Tommi, a 28-year-old data engineer from Mexico City, described how AIHawk allows him to automate his job search. He estimates the tool can apply to 250 LinkedIn positions in 3-6 hours, roughly LinkedIn’s daily limit.
It is having a positive effect in that you’re seeing a broader pool of people come to your job.
Alexander Alonso, chief data and insights officer at the Society for Human Resource Management, offered a surprisingly optimistic view of mass-application AI tools, suggesting they may benefit employers by expanding candidate diversity despite concerns about authenticity.
Our Take
AIHawk exemplifies the double-edged nature of AI automation in professional contexts. While democratizing access to job opportunities for struggling workers, it simultaneously threatens to undermine the authenticity and efficiency of hiring processes. The tool’s evolution—from generating false qualifications to offering unmodified résumé submissions—shows how AI developers are responding to user feedback, but fundamental questions remain unanswered.
LinkedIn’s ambiguous response is particularly telling. By restricting the creator’s account without explicitly banning the tool or clarifying policy, the platform reveals the difficulty of governing AI automation in established ecosystems. This regulatory vacuum creates risk for users while allowing the technology to proliferate.
Most concerning is the emerging AI arms race in recruitment: as more candidates use automation, those who don’t may become invisible, forcing universal adoption. This could fundamentally transform hiring from a quality-focused to quantity-focused process, with unknown consequences for both job seekers and employers navigating an increasingly AI-mediated labor market.
Why This Matters
AIHawk represents a significant development in the intersection of AI automation and employment, highlighting both the promise and peril of artificial intelligence in job searching. As the labor market tightens—with job openings at four-year lows and tech hiring down 20%—desperate job seekers are turning to AI tools that fundamentally change the recruitment landscape.
This story matters because it raises critical questions about fairness, authenticity, and platform governance in the AI era. When candidates can mass-apply to thousands of positions with automated tools, it potentially overwhelms HR departments while creating an arms race where using AI becomes necessary just to compete. The tool’s tendency to fabricate qualifications also underscores broader concerns about AI hallucinations and misinformation.
For businesses, AIHawk signals a shift in recruitment dynamics where traditional application processes may become obsolete. HR departments face the challenge of detecting AI-generated applications while potentially benefiting from broader candidate pools. The ambiguity around LinkedIn’s enforcement—restricting the creator’s account while not explicitly banning the tool—reflects the regulatory uncertainty surrounding AI automation across industries. This case study will likely influence how job platforms, employers, and policymakers approach AI-assisted job applications in the future.
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