AI Employer Visibility Checklist: 15 Things to Fix This Quarter
AI Employer Visibility Checklist: 15 Things to Fix This Quarter
You've run your AI employer brand audit. You've seen the gaps. Now what?
An AI employer visibility checklist is a prioritised set of specific, actionable steps that employers can take to improve how accurately and completely AI models represent them to candidates. This checklist is designed to be completed within a single quarter — no multi-year roadmaps, no vague strategy documents. Just 15 things you can do, ranked by priority and difficulty.
Overview: The 15-Item Checklist at a Glance
| # | Action | Priority | Difficulty | Impact |
|---|---|---|---|---|
| 1 | Run an AI employer brand audit | 🔴 High | Easy | Baseline measurement |
| 2 | Publish salary ranges on careers page | 🔴 High | Easy | +53% salary accuracy |
| 3 | Add Organisation schema markup | 🔴 High | Medium | +40% AI visibility |
| 4 | Create an llms.txt file | 🔴 High | Easy | Direct AI briefing |
| 5 | Unblock AI crawlers in robots.txt | 🔴 High | Easy | Enables all other fixes |
| 6 | Add JobPosting schema to roles | 🔴 High | Medium | Accurate role data in AI |
| 7 | Publish an FAQ page with schema | 🟡 Medium | Medium | Direct answer extraction |
| 8 | Convert PDFs to HTML pages | 🟡 Medium | Medium | Benefits/policy visibility |
| 9 | Add transcripts to videos | 🟡 Medium | Easy | Culture content accessible |
| 10 | Publish a "Working Here in 2026" page | 🟡 Medium | Easy | Recency signal |
| 11 | Create structured careers blog content | 🟡 Medium | Medium | Topical authority |
| 12 | Submit sitemap to AI crawlers | 🟢 Low | Easy | Faster indexing |
| 13 | Add breadcrumb schema | 🟢 Low | Easy | Site structure clarity |
| 14 | Implement review response strategy | 🟢 Low | Medium | Review data counterbalance |
| 15 | Set up monthly AI monitoring | 🟢 Low | Easy | Ongoing measurement |
High Priority Actions
1. Run an AI Employer Brand Audit
Priority: 🔴 High | Difficulty: Easy | Time: 5 minutes | Who: HR / Employer Branding
Before you fix anything, you need to know what's broken. An AI employer brand audit shows you exactly what ChatGPT, Claude, Perplexity, and Google AI Overviews say about your company right now.
What to do:
- Go to openrole.co.uk and enter your company name
- Review the audit results across all AI models
- Note factual errors, missing information, and outdated claims
- Save your baseline AI visibility score — you'll track improvement against this
Expected impact: This doesn't directly improve your AI visibility, but it's the foundation for everything else. You can't fix what you can't measure. According to OpenRole's UK employer visibility report, 88% of UK employers have never audited what AI says about them.
2. Publish Salary Ranges on Your Careers Page
Priority: 🔴 High | Difficulty: Easy | Time: 1–2 hours | Who: HR / Talent Acquisition
Salary data is one of the most commonly requested pieces of information from AI, and one of the most frequently wrong. OpenRole's salary accuracy research found that employers who publish salary ranges see AI salary accuracy of 91%, compared to just 38% for those who don't.
What to do:
- Add salary ranges to all active job postings on your careers page
- Use "from £X to £Y" format in plain text (not images or PDFs)
- If you can't publish exact ranges, publish bands (e.g., "£45,000–£55,000")
- Include the salary data in JobPosting schema markup (see item #6)
Expected impact: Dramatic improvement in salary accuracy across all AI models. This single action reduces the most common source of AI misinformation about your company.
3. Add Organisation Schema Markup
Priority: 🔴 High | Difficulty: Medium | Time: 2–4 hours | Who: Web team / Developer
Organisation schema markup is structured data that tells AI models the basic facts about your company in a machine-readable format. It's the single most impactful technical action you can take for AI visibility.
What to do:
- Use OpenRole's free schema markup generator to create your Organisation schema
- Include: company name, description, founding date, employee count, industry, headquarters address, logo URL, social profiles
- Add the generated JSON-LD to the
<head>section of your careers page and homepage - Validate using Google's Rich Results Test tool
Expected impact: Companies with Organisation schema markup score an average of 2.3x higher on AI visibility tests according to our schema markup guide. This gives AI authoritative facts to cite instead of relying on third-party sources.
4. Create an llms.txt File
Priority: 🔴 High | Difficulty: Easy | Time: 30 minutes | Who: HR / Employer Branding
An llms.txt file is a structured text document placed at the root of your website that provides AI models with a curated summary of key information about your company. Think of it as a briefing document for AI.
What to do:
- Use OpenRole's free llms.txt generator to create your file
- Include: company overview, culture, benefits, salary approach, hiring process, locations, recent changes
- Upload to your website root (e.g., yourcompany.com/llms.txt)
- Add a reference to it in your sitemap
For a comprehensive understanding, read our complete guide to llms.txt.
Expected impact: Provides AI models with a direct, authoritative source of employer information. Early adopters report improved accuracy in AI responses within weeks for browsing-enabled models.
5. Unblock AI Crawlers in robots.txt
Priority: 🔴 High | Difficulty: Easy | Time: 15 minutes | Who: Web team / DevOps
If your robots.txt file blocks AI crawlers, none of your other improvements will matter. AI models can only use content they can access.
What to do:
- Check your robots.txt file (yourcompany.com/robots.txt)
- Look for blocks on: GPTBot, ClaudeBot, Google-Extended, PerplexityBot, Bytespider
- Remove or modify these blocks to allow crawling of careers-related pages
- At minimum, allow:
/careers,/about,/jobs,/llms.txt,/blog
Expected impact: Immediately enables AI crawlers to access your content. Without this, items 2–4 and 6–11 have zero effect on AI models that use web crawling.
6. Add JobPosting Schema to All Roles
Priority: 🔴 High | Difficulty: Medium | Time: 4–8 hours | Who: Web team / ATS configuration
JobPosting schema markup is structured data that provides AI models with detailed, machine-readable information about specific roles, including salary ranges, benefits, location, and employment type.
What to do:
- Add JobPosting schema to every active job listing on your careers page
- Include all available fields: title, description, salary range, location, employment type, benefits, date posted, application deadline
- If using an ATS, check if it supports schema markup output (many do, but it's often not enabled)
- Use the schema markup generator to create templates
Expected impact: AI models can cite specific, accurate role information. This directly addresses the most common candidate queries: "What does [Company] pay for [Role]?" and "What benefits does [Company] offer?"
Medium Priority Actions
7. Publish an FAQ Page with FAQPage Schema
Priority: 🟡 Medium | Difficulty: Medium | Time: 4–6 hours | Who: Employer Branding + Web team
FAQ content with FAQPage schema markup is one of the most powerful tools for AI visibility. When AI encounters structured Q&A pairs, it can extract and cite them directly in response to candidate questions.
What to do:
- Identify the top 15–20 questions candidates ask about your company (use AI queries from your audit as a guide)
- Write clear, factual answers for each (100–200 words per answer)
- Publish as an FAQ page on your careers site
- Add FAQPage schema markup to the page
- Update quarterly as policies or information change
Example questions to include:
- What's the salary range for [common role] at [Company]?
- What benefits does [Company] offer?
- Does [Company] offer remote or hybrid working?
- What's the interview process like at [Company]?
- What career progression is available at [Company]?
Expected impact: Direct answer extraction by AI models. When a candidate asks "What benefits does [Company] offer?" and you have this answered in schema markup, AI is significantly more likely to cite your answer.
8. Convert Key PDFs to HTML Pages
Priority: 🟡 Medium | Difficulty: Medium | Time: 8–16 hours | Who: Employer Branding + Web team
Most AI crawlers cannot read PDF files. If your benefits guide, D&I report, or career progression framework exists only as a PDF download, it's invisible to AI.
What to do:
- Identify all PDFs on your careers site (benefits guides, policy documents, culture reports)
- Convert the most important ones to HTML pages on your website
- Prioritise: benefits overview, D&I summary, career progression paths, office/location information
- Keep PDFs available for download, but ensure the core content also exists as web pages
Expected impact: Makes previously invisible content accessible to AI. Benefits and D&I information are among the most commonly missing categories in AI responses about UK employers.
9. Add Text Transcripts to Employee Videos
Priority: 🟡 Medium | Difficulty: Easy | Time: 1 hour per video | Who: Employer Branding
Employee testimonial videos are valuable employer branding content, but AI cannot watch videos. Adding text transcripts makes this content AI-accessible.
What to do:
- Identify your most important employee videos (culture, testimonials, office tours)
- Create text transcripts for each (use AI transcription tools for speed)
- Publish transcripts on the same page as the video, in visible HTML text
- Ensure transcripts include relevant keywords (culture, benefits, career progression)
Expected impact: Turns invisible content into AI-readable text. Each transcript adds to the volume of first-party employer information available to AI models.
10. Publish a "Working Here in 2026" Page
Priority: 🟡 Medium | Difficulty: Easy | Time: 2–3 hours | Who: Employer Branding
Recency is a powerful signal. A page explicitly titled "Working at [Company] in 2026" tells AI that this information is current, helping to counteract outdated review data.
What to do:
- Create a dedicated page: "What It's Like to Work at [Company] in 2026"
- Include current information: hybrid/remote policy, benefits, salary approach, culture initiatives, recent achievements
- Reference specific dates ("As of Q1 2026...")
- Update quarterly with new information
- Add Organisation and FAQPage schema markup
Expected impact: Provides AI with a clearly current source of employer information. This is particularly valuable if your company has undergone significant changes in the last 2–3 years.
11. Create Structured Careers Blog Content
Priority: 🟡 Medium | Difficulty: Medium | Time: Ongoing (2–4 posts/month) | Who: Employer Branding / Content team
Regular blog content about working at your company creates ongoing AI training signals. Each post adds to the volume of first-party data available to AI.
What to do:
- Publish 2–4 blog posts per month about working at your company
- Use clear H2/H3 headings with keywords candidates search for
- Include data tables, numbered lists, and FAQ sections (AI extracts these formats preferentially)
- Cover topics that match common AI queries: day-in-the-life, team profiles, career progression stories, benefits deep-dives
Expected impact: Builds topical authority over time. Companies with active careers blogs have 34% higher AI visibility scores than those without, according to OpenRole's industry benchmarks.
Low Priority (But Still Valuable) Actions
12. Submit Your Sitemap to AI Crawlers
Priority: 🟢 Low | Difficulty: Easy | Time: 30 minutes | Who: Web team
Submitting your sitemap ensures AI crawlers can discover all your careers-related pages efficiently.
What to do:
- Ensure your XML sitemap includes all careers pages, job listings, FAQ pages, and blog posts
- Reference your sitemap in robots.txt
- Submit to Google Search Console (for AI Overviews)
- Ensure your llms.txt file is included in the sitemap
Expected impact: Faster discovery of your content by AI crawlers. This is a low-effort action that ensures your other improvements are found quickly.
13. Add Breadcrumb Schema to Careers Pages
Priority: 🟢 Low | Difficulty: Easy | Time: 1–2 hours | Who: Web team
Breadcrumb schema helps AI understand the structure of your careers site, making it easier to navigate and extract information from specific sections.
What to do:
- Add BreadcrumbList schema to all careers pages
- Use a clear hierarchy: Home > Careers > [Department] > [Role]
- Ensure breadcrumbs match your URL structure
Expected impact: Improves AI's ability to navigate and understand your careers site structure. Minor but cumulative benefit.
14. Implement a Strategic Review Response Plan
Priority: 🟢 Low | Difficulty: Medium | Time: Ongoing (2–3 hours/week) | Who: Employer Branding
Your responses to Glassdoor reviews become part of AI training data. Strategic responses can counterbalance negative review data.
What to do:
- Respond to all reviews (positive and negative) on Glassdoor and Indeed
- Include current, factual information in responses (salary ranges, new policies, recent changes)
- Use keywords that match AI queries ("remote work policy", "career progression", "benefits package")
- Reference improvements: "Since 2024, we've implemented..."
- Keep responses substantive (100+ words) — longer responses contribute more training data
Read more about why this matters: how AI models use Glassdoor reviews.
Expected impact: Gradual improvement in AI's characterisation of your company as review responses enter AI training data. This is a long-term strategy, not a quick fix.
15. Set Up Monthly AI Monitoring
Priority: 🟢 Low | Difficulty: Easy | Time: 30 minutes/month | Who: HR / Employer Branding
Regular monitoring ensures you catch new issues and track improvement over time.
What to do:
- Run an AI employer brand audit monthly
- Track your AI visibility score over time
- Compare your score against industry benchmarks
- Document new AI responses that are incorrect or outdated
- Adjust your content strategy based on findings
Expected impact: Ongoing awareness and improvement. Companies that monitor monthly improve their AI visibility scores 2x faster than those that audit once and forget.
Implementation Timeline
Here's a realistic 12-week plan for completing all 15 items:
| Week | Actions | Time required |
|---|---|---|
| 1 | #1 Audit, #5 Unblock crawlers, #4 llms.txt | 2 hours |
| 2–3 | #2 Salary ranges, #3 Organisation schema | 6 hours |
| 4–5 | #6 JobPosting schema | 8 hours |
| 6–7 | #7 FAQ page with schema, #10 "Working Here" page | 8 hours |
| 8–9 | #8 Convert PDFs, #9 Video transcripts | 12 hours |
| 10 | #12 Sitemap, #13 Breadcrumbs | 2 hours |
| 11 | #14 Review response plan, #11 First blog posts | 6 hours |
| 12 | #15 Monthly monitoring setup, #1 Re-audit | 1 hour |
Total estimated time: 45 hours across 12 weeks — less than 4 hours per week. For most companies, this work can be split between HR (content and strategy), a web developer (schema and technical), and employer branding (review responses and blog content).
Measuring Progress
Track these metrics before and after implementing the checklist:
| Metric | How to measure | Target improvement |
|---|---|---|
| AI visibility score | OpenRole audit | +30% from baseline |
| Salary accuracy | Compare AI-stated salaries to actual | 90%+ accuracy |
| Source coverage | Count categories AI addresses accurately | 80%+ coverage |
| Hallucination rate | Count fabricated claims per AI response | <10% |
| Review data dominance | % of AI response sourced from reviews | <40% |
Frequently Asked Questions
Q: Do I need to complete all 15 items to see improvement?
A: No. The first six items (high priority) will deliver approximately 70% of the total impact. If you can only do six things, do those. The medium and low priority items provide incremental improvement and are worth pursuing, but they're not essential for a meaningful baseline improvement.
Q: Which AI models will respond fastest to these changes?
A: Google AI Overviews and Perplexity respond fastest because they pull from live web data — changes can appear within days. ChatGPT with browsing enabled will pick up changes within weeks. Static ChatGPT and Claude responses based on training data may take months to reflect changes, though both models periodically retrain and update their knowledge.
Q: What if our ATS doesn't support schema markup?
A: Many ATS platforms have schema markup capabilities that aren't enabled by default — check with your provider first. If your ATS doesn't support it, you can add schema markup via a tag manager (Google Tag Manager), a WordPress plugin, or direct code injection. OpenRole's schema markup generator produces code that can be added via any of these methods.
Q: How do we prioritise if we have limited developer time?
A: If developer time is the bottleneck, focus on the items that don't require development first: salary range publishing (#2), llms.txt creation (#4), video transcripts (#9), the "Working Here" page (#10), and the review response strategy (#14). These are all content tasks that HR and employer branding can own directly. Then use the limited developer time for schema markup (#3, #6, #7) and crawler access (#5).
Q: Can we use an agency to implement this checklist?
A: Yes, but ensure the agency understands AI employer branding specifically, not just traditional SEO. The technical implementation (schema markup, robots.txt, sitemap) is standard web development. The content strategy (what information to publish, how to structure it for AI) requires understanding of how AI models process employer data. OpenRole can provide both the audit data and ongoing monitoring to support agency implementation — visit openrole.co.uk/pricing for details.