Applications per offer are rising, and AI is changing how candidates apply. But Workday data shows the key hiring challenge is fit, not volume alone.
Ross Brooks
Senior Research Writer
Workday
The story gripping hiring teams this year is simple and alarming: AI is flooding job boards with polished, lookalike applications, and recruiters are struggling to separate real fit from resume noise.
Workday’s October 2026 Global Workforce Report found the number of applications per offer increased to 69 (+19% YoY), with sharper jumps in technology and media, and financial services.
But a crowded candidate pipeline is not the same as a broken one. Hiring demand has remained broadly stable, and the median time to fill open roles remains unchanged at 60 days. And, job seekers are using AI to do more than mass-apply: some to apply better, and some to become more selective.
AI didn’t break hiring. It exposed a matching problem that was already there.
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Job openings haven’t surged; in fact, they’re slightly down year over year. Globally, companies created about 83 openings per month on average in March 2025 and about 79 in July 2026, a modest 4% year-over-year dip. The median time to fill open roles remains unchanged at 60 days.
That matters. If AI-generated mass applications were the only thing reshaping hiring, we would expect to see a more dramatic shift in hiring speed. Either employers would move faster because they can triage applications more efficiently, or slower because recruiters are buried in noise.
The real pressure point is conversion. In our research, 34% of hiring managers report roles remain unfilled because too few candidates have the required skills and 33% say it’s because candidate expectations around pay, location, or flexibility do not align.
In other words, the core challenge isn’t the growing stack of resumes hitting recruiters’ desks—it’s finding the right candidate for the role.
As Dr. Liz Pavese, Workday workplace psychologist, puts it: “The difficulty in hiring is likely not a lack of qualified people, but a misalignment of roles and skills.”
That distinction matters. A volume problem asks recruiters to screen harder. A matching problem asks organizations to understand work differently.
The difficulty in hiring is likely not a lack of qualified people, but a misalignment of roles and skills.
Dr. Liz Pavese, Workplace Psychologist, Workday
AI is clearly changing how people look for work.
In our survey, 84% of job seekers say they have used AI in some way during their search. The most common use case is not fully automating the job hunt. It’s improving how candidates present themselves: 47% report using AI to write or adapt their resume, CV, and cover letters, while 34% report using it to prepare for interviews and assessments.
That should not surprise anyone. Candidates have always tried to translate their experience for each role they are applying to. AI just makes that translation faster, smoother, and more polished.
The effect of AI on application volume is real, but not universal. Among job seekers using AI, 42% say AI has increased the number of jobs they’ve applied for. But, 30% say it has had no effect, and 28% say they have actually applied to fewer roles.
42% say AI has increased the number of jobs they’ve applied for. But, 30% say it has had no effect, and 28% say they have actually applied to fewer roles. That is not a picture of every candidate spamming job postings overnight.
That is not a picture of every candidate spamming job postings overnight. It is a picture of candidates using AI in different ways: some to apply more, some to apply better, and some to become more selective.
For hiring teams, though, the result can feel similar. More applications look complete. More resumes seem relevant. More candidates know how to mirror the language of the job posting.
AI increases polish. And polish can look a lot like fit until you look closer.
Again, the application flood is real, but it is not evenly distributed. It shows up most clearly in technology and media, and financial services.
These are two of the sectors with the sharpest increases in applications per offer: up 40% in technology and media, and 27% in financial services year over year. These are also two of the sectors where job seekers lean most heavily on AI.
Among external applicants, 93% in technology and 95% in financial services report using AI in their search. And among those applicants, 57% in technology and 53% in financial services say AI has increased the number of roles they’ve applied to.
That is the clearest connection between AI-assisted applications and a more crowded hiring landscape, but it doesn’t represent the whole market.
If the hiring bottleneck felt in many industries is caused by skills misalignment rather than application volume, then screening resumes harder is the wrong solution.
Pavese’s guidance is direct: “Legacy systems and mindsets are searching for specific titles and profiles. While skills demand has shifted, skills are fluid and scattered across traditional and nontraditional roles. So, hiring managers need to evolve from resume-bound screening to evaluating transferable and adjacent capabilities, while candidates need to figure out how to market their most in-demand skills.”
Hiring managers need to evolve from resume-bound screening to evaluating transferable and adjacent capabilities, while candidates need to figure out how to market their most in-demand skills
Dr. Liz Pavese, Workplace Psychologist, Workday
Phil Willburn, Workday’s VP of people systems, intelligence and support, adds that hiring managers are increasingly prioritizing a candidate’s ability to learn and adapt, especially as roles change with AI taking on more of the manual work. His advice to applicants navigating this job market is to highlight a successful track record of adjusting and learning along the way, not just a resume that lists the right keywords.
The goal is not a faster version of the same old screening process. It’s a better way to match changing roles with the skills, adaptability, and potential people actually have.
AI didn’t break hiring. It made a matching problem impossible to ignore.
The AI mass-apply story captures something real: hiring teams are facing a more crowded, more polished, and often harder-to-read candidate pipeline.
But the problem isn’t volume alone.
For employers, the real work is rebuilding how roles and skills get matched in the first place.
AI didn’t break hiring. It made a matching problem impossible to ignore.
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