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Very quietly, an Italian developer has launched an application that automates the application process for job seekers. Auto_Jobs_Applier_AIHawk can apply for hundreds of jobs in a day, completely automatically unless the user wants to tweak content as they go. It’s the flip side of high-volume recruiting.
Similar products are being developed by other parties, some of which smooth over the technical nuts and bolts AIHawk imposes. A company called JobMagic, for example, eliminates the need to know Python, which AIHawk requires.
The appearance of such products was inevitable. After all, job seekers are just as human as talent acquisition professionals struggling to identify candidates in today’s labor market. They also loathe a process which, in many if not most cases, is clunky, frustrating and anxiety-producing.
Career experts urge candidates to create a customized resume and cover letter for each individual job. AIHawk takes care of that by creating original answers to screening questions. And AIHawk doesn’t just apply for jobs – it identifies opportunities that it sees as aligning with the job seeker’s background.
AIHawk’s creator, Federico Elia, said that the bot is meant to “balance the use of artificial intelligence in the recruitment process.” He told 404 Media, “By automating repetitive tasks and personalizing applications, AIHawk reduces the time and effort required from candidates, increasing their chances of being noticed by employers.”
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Candidates Want to Save Time, too
Job seekers will certainly appreciate AIHawk’s increased convenience, but employers shouldn’t ignore its ability to blast out dozens of applications a day. (One user said on GitHub that he’s applied for 2,800 jobs in three months.) Already, job hunters take a shotgun approach to searching, blindly applying for jobs on the theory that more is better. Employers lament the fact they get myriad applications that don’t match their needs. With AIHawk-type products, they’re going to get even more.
AIHawk already has thousands of users, with no apparent marketing effort behind it. As more companies create friendlier versions to run on more platforms, the volume of applications each company receives is sure to rise. That means TA teams will have to work harder to ensure their ATS – AI-driven or not – is identifying a complete set of matching candidates.
That may be more challenging than is apparent, given that with AIHawk, the candidate’s AI is talking directly to the employer’s AI, without involving a human. It’s a byproduct of scaling we don’t hear very much about, but must certainly consider.Other NewsCandidates Now Have a Tool to Automate the Job-Application Process
Word is beginning to spread about a bot that automates the application process for job seekers, to the point where they can apply for hundreds of jobs in less than a day. The bot, called Auto_Jobs_Applier_AIHawk, provides a hands-off approach for candidates, allowing them to easily apply to jobs on LinkedIn after they’ve completed a brief set-up process. Read more.
How One Industry Faces Reality as It Adopts AI
Advertising isn’t the same thing as talent acquisition, but there are similarities. Both seek to identify people with certain characteristics, raise awareness of a company’s brand and encourage some kind of contact. So, as CHROs consider their strategies with AI, it’s worth paying attention to developments in the ad industry. Read more.
Podcast: Findem's Brett Coin on AI and Talent Acquisition
I chat with Brett Coin, the chief transformation officer at Findem. We talk about AI and how it fits into talent acquisition, changing perceptions about it, and the dynamics of vendors and users. Listen here.
Podcast: AI's Role in HR Tech, with Oracle's Nagaraj Nadendla
I chat with Nagaraj Nadendla, senior vice president of product development at Oracle. We talk about some features that were recently added to Oracle Fusion Cloud HCM, the thinking behind them, and AI’s role in HR tech in general. Listen here.
Businesses Find LLMs Need Training to Tackle Industry-Specific Data
Businesses have discovered that the general models offered by the likes of OpenAI are only so useful. The reason: They work off a large set of general data, but haven’t been trained on the more specialized information unique to different fields or industries. Read more.