Research shows that women apply for jobs only when they meet 100% of the qualifications, while men apply at 60%. Gendered language, unnecessary requirements, and credential inflation in job descriptions silently exclude qualified candidates before they even apply.

AI catches biased language that humans miss and rewrites descriptions to attract the widest possible talent pool.

The inclusive job description prompt

``` Write an inclusive job description for [position] at [company type].

Requirements (must-have skills only): [list] Nice-to-haves: [list] Salary: [range — always include this] Location: [remote/hybrid/onsite] Reports to: [title]

Rules:

• Remove gendered language (“rockstar,” “ninja,” “aggressive”)
• Focus on skills and outcomes, not years of experience
• Don’t require a degree unless legally necessary
• Use “you” language (“You will…” not “The candidate must…”)
• Include benefits and culture information
• Keep requirements to 5-7 items max (long lists deter applicants)
• Add: “We encourage applications from candidates who meet most but not all requirements” ```

Bias detection

Run any existing job description through AI:

``` Prompt: “Review this job description for biased or exclusionary language.

[paste job description]

Flag:

• Gendered words (he/she, mankind, manpower, guys)
• Aggressive language (crush it, dominate, killer)
• Unnecessary requirements (degree when skills matter more)
• Age-coded language (digital native, young and energetic, 10+ years)
• Ability-coded language (must be able to lift, stand for 8 hours — unless essential)
• Cultural bias (beer Fridays, ping pong table — signals specific culture)

For each flag, suggest an inclusive alternative.” ```

Before and after examples

Biased	Inclusive
”Looking for a rockstar developer"	"Looking for a skilled developer"
"Must have 10+ years experience"	"Experienced in building production applications"
"Bachelor’s degree required"	"Bachelor’s degree or equivalent practical experience"
"Young, energetic team"	"Collaborative, motivated team"
"Must be a native English speaker"	"Strong English communication skills"
"Fast-paced environment"	"Dynamic environment where priorities evolve”

Salary transparency

Always include salary ranges. AI can help benchmark:

``` Prompt: “What’s a competitive salary range for a [position] in [city/region]? Company size: [employees] Industry: [industry] Experience level: [junior/mid/senior]

Provide: low end, median, and high end. Note factors that affect the range.” ```

Including salary ranges increases applications by 30-40% and disproportionately helps underrepresented candidates who are less likely to negotiate.

Tools

Tool	What it does	Price
Textio	Real-time bias detection in job posts	Enterprise
Datapeople	Job description analytics + optimization	From $99/mo
ChatGPT	Write and review descriptions	Free / $20/mo
Gender Decoder	Free gendered language checker	Free (genderdecoder.com)

For most HR teams, ChatGPT + the Gender Decoder is sufficient. Textio is worth it for companies hiring at scale (50+ positions/year).

The template

Every job description should follow this structure:

1. About the role (2-3 sentences — what you’ll do and why it matters)
2. What you’ll do (5-7 bullet points — outcomes, not tasks)
3. What you bring (5-7 requirements — skills, not credentials)
4. Nice to have (3-4 items — clearly labeled as optional)
5. What we offer (compensation, benefits, culture)
6. How to apply (simple, clear process)
7. Equal opportunity statement (genuine, not boilerplate)

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