AI has been applied to nearly every stage of the hiring process. Some of it is genuinely changing how teams work. Much of it is marketing. Here's how to tell the difference.
Recruiting vendors have been adding 'AI' to their product descriptions faster than most teams can evaluate what it actually means. Depending on who you talk to, AI is either transforming hiring entirely or producing a new layer of junk for recruiters to manage. The truth is somewhere in the middle and depends heavily on what specifically you're talking about.
There are a few areas where AI has genuinely changed the day-to-day experience of hiring teams. There are more areas where the technology exists but hasn't delivered on the promises made about it. Being able to tell them apart is a practical skill at this point.
Where AI Is Actually Working
Resume screening and candidate ranking at high volume is the clearest win. When a role gets 500 applications, the ability to surface the top 10% based on structured criteria is genuinely useful — it compresses days of manual review into minutes. The quality depends on how well the criteria are defined, but the time savings are real.
Scheduling automation has also delivered meaningful improvements. AI-assisted scheduling tools that find mutual availability, send confirmations, and handle rescheduling have reduced coordinator overhead noticeably in teams that use them.
Interview question suggestion and feedback synthesis tools are improving. They're not replacing human judgment, but they're reducing the gap between structured and unstructured interviews by giving interviewers better scaffolding.
Where It's Still Mostly Hype
Predictive hiring — the promise that AI can predict which candidates will perform well or stay long-term — hasn't held up as well as early vendors suggested. The training data for these models is usually based on who performed well among past hires, which encodes existing biases rather than identifying genuine predictors of future performance.
AI-generated job descriptions are a mixed bag. They can produce serviceable drafts quickly, but they often reinforce generic, keyword-stuffed language that reads as impersonal. The best ones still require meaningful human editing.
What to Ask When a Vendor Says AI
The most useful question is: what is the AI actually doing in this feature, and what does the outcome look like? A vendor who can explain that precisely is usually delivering something real. A vendor who says 'AI-powered insights' without a clear mechanism is usually marketing a better search function.
Ask for data on outcomes: what happened to time-to-hire, quality of hire, or recruiter time saved for teams using this feature? Real improvements come with numbers. Honest vendors share them.
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