21 Days of AI for HR Professionals

The Concept

Every hire begins before the first CV lands. It begins the moment a job description is written — or, more often, recycled. In most organisations, job descriptions are drafted once, approved once, and then quietly reused for years. Requirements accumulate. Vague language hardens into convention. A role that has fundamentally changed still carries the fingerprints of who held it five years ago. By the time a candidate reads it, the description has drifted far from what the job actually is.

This is not a minor administrative problem. It is a hiring quality problem, a diversity problem, and a time problem — because a poorly written job description attracts the wrong applicants, filters out strong candidates on irrelevant criteria, and gives the hiring manager and the recruiter different mental pictures of what they are actually looking for.

Why Job Descriptions Matter Before the First Interview

The job description is the first filter in your funnel. Before any human judgement is applied, the words you choose determine who applies, who self-selects out, and who a sourcer goes looking for. Research from LinkedIn and multiple academic studies has consistently shown that long lists of requirements suppress applications from women and underrepresented groups significantly more than they suppress applications from majority-group men — who, on average, apply when they meet 60% of listed criteria while other groups wait until they meet 100%.

This means that an inflated requirements list is not a neutral document. It is an active force shaping who walks through your door before you have made a single decision. The same logic applies to language: words like "aggressive," "competitive," and "ninja" carry associations that nudge certain readers away while encouraging others. None of this is usually intentional. That is precisely why it is so hard to catch with human review alone.

The Hidden Cost of Vague Qualifications

"Strong communication skills." "Ability to work in a fast-paced environment." "Five or more years of experience." These phrases appear in thousands of job descriptions and mean almost nothing to a candidate trying to decide whether to apply. What kind of communication? To whom, about what, at what level of complexity? What does fast-paced mean in your organisation versus another? And does five years of experience actually correlate with performance in this role — or is it a proxy for something more specific that should be named directly?

The cost is paid in two places. Qualified candidates who cannot see themselves in a vague description do not apply. Unqualified candidates who have learned to pattern-match job description language apply anyway, flooding your funnel with effort that adds no value. Precision attracts; vagueness wastes everyone's time.

How AI Spots What Human Reviewers Miss

When you read a document you have seen many times, your brain fills in meaning from context. You know what "dynamic team player" means because you know the team. A language model does not have that context — and that limitation is useful. It reads what is actually there, not what you meant to write. It can flag that a phrase is undefined, that a requirement appears twice in different forms, that the listed qualifications are significantly above what the role's described tasks would require.

AI does not know your culture, your hiring manager's real preferences, or your organisation's compensation band. It cannot tell you whether the role is the right role. But it can produce an honest audit of whether the description communicates clearly — and that audit is often more revealing than the rewrite.

Building a Habit Before Every Posting

The goal of today's exercise is not a one-off polish job. It is the start of a practice: running every job description through a structured AI review before it goes live. In fifteen minutes, you can produce a clearer description, a cleaner requirements section, and a set of questions to take back to the hiring manager. Over time, that habit changes the quality of every hire your organisation makes. Start with one real posting, run the prompt, and take the audit list into your next conversation with the hiring manager. That conversation alone is worth more than the polished document.

You are a senior HR business partner and inclusion specialist. I need you to rewrite the job description below for the role of [JOB TITLE] at [COMPANY NAME], a [BRIEF COMPANY DESCRIPTION, e.g. 'mid-size logistics company'].
Here is the current job description: [PASTE FULL JOB DESCRIPTION HERE]
Please do the following in order: 1. Identify and list every piece of vague, inflated, or exclusionary language in the original (e.g. 'rockstar', 'must have degree', years-of-experience requirements that do not reflect actual complexity) 2. Rewrite the description using outcome-focused language — describe what success looks like in the role, not a list of tasks 3. Replace jargon and corporate filler phrases with plain English equivalents 4. Rewrite the requirements section to distinguish between genuine must-haves and nice-to-haves 5. Suggest two alternative job titles that would attract a broader candidate pool
Keep the hiring manager's intent intact. Do not change the scope or seniority of the role.