A new analysis of nearly 1.4 million U.S. job listings points to something most hiring managers would not guess: vague job postings, not unrealistic requirements, are what leave some roles with plenty of clicks and no applicants.

That sounds like a copywriting issue. It is not.

A job posting is the first place an organization defines work for someone who has never worked there. When that definition is missing, candidates do not fill in the blanks generously. They move on. The problem is not that the bar is too high. The problem is that no one can see the bar.

Key takeaways

  • A JobLeads study of about 1.4 million U.S. job postings found that listings with clicks but zero applications asked for about the same number of skills and paid about the same as other jobs. The difference was that they were vaguer.
  • Words like “motivated,” “hardworking” and “following directions” describe signals, not standards. They give candidates nothing to measure themselves against.
  • A Greenhouse survey of more than 2,800 job seekers found 81% had been rejected in the past year without ever being contacted, and 96% wanted a way to show employers more than an application allows.
  • Hiring is where the definition of work starts. Leaders who name the real skills, systems and early measures of success give candidates a bar they can actually see.

What the research says about vague job postings

On October 21, 2026, the job platform JobLeads published a study of roughly 1.4 million U.S. job postings that drew at least one click between April and June 2026. It isolated 2,984 “zero-apply” postings: listings with 10 or more clicks and not a single application. The researchers expected those roles to be asking for too much. They were not. Zero-apply postings listed an average of 4.4 skills, compared with 4.5 for all clicked jobs, and median salaries differed by only 2–4%.

What did stand out was the language. In zero-apply postings, “motivated” appeared 4.5 times more often than in the baseline, “hardworking” 4.3 times more often, and “following directions” 10 times more often. Equipment such as “laptop” and “smartphone” showed up as requirements far more often too. The study’s conclusion was blunt: the problem “isn’t that the bar is too high. It’s that there’s no visible bar at all.”

HR Dive covered the findings on October 26, noting one irony in the data: HR roles were 28% more likely than the baseline to be clicked but not applied to, even though, as the report puts it, HR is “the function most often responsible for writing job ads.” The study has real limits worth naming. It reflects only JobLeads’ own platform, which puts applications behind a payment, it covers a single quarter, and its findings are correlational rather than causal. Still, the pattern is hard to ignore.

The candidate side of the story arrived the same week. HR Dive reported on October 23 on a Greenhouse survey of more than 2,800 job seekers in the U.S., U.K., Ireland, Germany and Australia. Seventy-one percent said they took an extra step to get noticed. Eighty-one percent said they had been rejected in the past year without ever being contacted. Thirty-one percent said being rejected without speaking to anyone, human or AI, happens often or almost always; among Gen Z respondents in the survey, that figure was 38%.

AI is now on both sides of the table. Seventy-seven percent of U.S. job seekers in the survey had used AI in their job search, and 40% of those who tried to get past AI screening said they added skills or keywords they did not have. Meanwhile, 96% wanted a way to show employers more than an application allows. Greenhouse chief people officer Sharawn Tipton summed it up: “For the first time I can remember, neither side thinks hiring is working.”

Why vague job postings are a definition-of-work problem

In The Next Turn, I describe two changes happening at once. The first is the definition of work: what people believe work is for, what it should provide and what it is worth. The second is the structure of work: how work actually flows, which AI is now reshaping. Hiring sits right where the two collide.

In Chapter 11, “Where It Breaks,” I name hiring as one of the four pressure points where the collision becomes operational. Candidates are evaluating the exchange a role offers. When the meaning of the role is never translated, the process breaks before it starts. This research shows that happening at the very first step.

Communication now has to do more than direct the work. It has to define the work.

The Next Turn

A job posting used to be able to get away with being a template. When the shared definition of work was stronger, “hardworking self-starter” carried an understood meaning. That shared meaning is weaker now. In Chapter 4, “Why Does This Feel Different?”, I make the point this way:

Organizations do not get loyalty upfront. They get scrutiny upfront.

The Next Turn

A posting is the first thing that gets scrutinized. If it cannot answer “What will I actually do, and what does good look like here?”, the scrutiny ends with the back button.

Then there is the language itself. In Chapter 13, “Building a Shared Definition of Good Work,” I separate standards, which are what the organization actually needs (quality, reliability, accountability, sound judgment, follow-through), from signals, which are the visible cues we use to infer them (time, visible effort, presence, endurance). “Hardworking” and “motivated” are signal words. They describe how someone might look while working, not what the work requires. The standard underneath might be “closes every payroll cycle accurately and on time” or “spots the problem in a data set before it reaches the client.” Those are bars a candidate can check themselves against.

Standards and signals are not the same thing.

The Next Turn

The Greenhouse findings add the structure-of-work side. When AI can generate a polished resume and hundreds of applications, the application itself becomes a weaker signal, which is the collapse of effort as a signal I describe in Chapter 7. As Greenhouse’s Ophir Samson put it, AI “can’t show an employer how someone thinks or learns.” That is exactly where Chapter 8, “The Rise of Judgment,” puts the center of value. Candidates are asking for a way to show judgment. Most hiring processes are still built to screen signals.

None of this is a generational story, even though Gen Z respondents reported more silent rejections. Every candidate reading a vague posting is doing the same thing: trying to figure out whether this work, in this place, makes sense for them. Leaders are not struggling here because they lack care. They are relying on a definition of work that used to be shared and no longer is.

Your next turn

If you lead a team that is hiring, or you sign off on job postings, try these this week:

  1. Circle the trait words. Pull your three most recent postings and circle every word like “motivated,” “hardworking,” “detail-oriented” or “team player.” For each one, ask: what standard is this standing in for? Write that instead.
  2. Name the skills, the systems and early success. The JobLeads study recommends naming the skills the role actually uses, the systems a new hire will work in, and what success looks like in the first few months. If you cannot write those three things, the role is not defined yet, and that is worth knowing before you interview anyone.
  3. Define the exchange, not just the role. One of the seven moves in Chapter 12, “Defining Work Again,” is to define the exchange. Say what the role offers: what someone will learn, who they will work with, and what growth looks like.
  4. Define AI’s role in the work and in the hiring process. Say where AI is part of the job. And tell candidates where AI is used in screening or interviews. In the Greenhouse survey, 88% of job seekers wanted at least one legal requirement that employers disclose AI use in interviews.
  5. Give candidates one way to show their thinking. Add a short, realistic scenario to the process and ask, “Talk me through how you would decide.” It tells you more than another keyword match.

If HR writes the posting and the hiring manager knows the work, put them in the same room for 30 minutes. That conversation is where the definition of the role actually gets built. For more on how leaders are redefining work, visit the Next Turn blog.

Frequently asked questions

Why do vague job postings get fewer applicants?

According to JobLeads’ analysis of about 1.4 million U.S. postings, zero-apply listings asked for roughly the same skills and pay as others but leaned on generic traits like “motivated” and “hardworking.” Candidates could not tell whether they qualified or what the job really involved. Without a visible bar, many simply did not apply.

What should a job posting include now that AI is changing hiring?

Start with the specific skills the role uses, the systems a new hire will work in, and what success looks like in the first few months. Then describe what the role offers in return and where AI fits in the work. When AI makes applications look more alike, a clear definition of the work becomes the most useful filter for both sides.

Should employers tell candidates when AI is used in hiring?

Candidates increasingly expect it. In Greenhouse’s survey of more than 2,800 job seekers, 88% wanted at least one legal requirement that employers disclose AI use in interviews, and 55% wanted advance notice. Being clear about where AI is used, and where humans make the decisions, builds trust before the first conversation.

The posting is the first promise

Hiring has always involved some guesswork on both sides. What has changed is how little the old shorthand now tells anyone. AI has made applications easier to produce and harder to read, and candidates are scrutinizing roles before they commit a single hour to them.

The response is not a better template. It is a clearer definition of the work.

If a strong candidate read your last job posting, could they tell what good work looks like in that role?

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