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Visibility of job vacancies in AI
The way candidates search for information is changing rapidly. Where Google and other search engines used to dominate, AI language models such as ChatGPT, Perplexity.ai, and Google’s AI Overview are now playing an increasingly important role. Candidates ask their questions directly to these models, which generate answers based on text, videos, images, and external sources. For employers, this means that traditional SEO is no longer enough. A new discipline is emerging: Generative Engine Optimization (GEO).
In this article, you’ll learn how SEO and GEO relate to each other, how AI language models work, key insights from our webinar, and how to make your vacancies, employer stories, and content optimally discoverable. You’ll also find a practical checklist and six strategies you can apply right away.
In this article, you’ll learn how SEO and GEO relate to each other, how AI language models work, key insights from our webinar, and how to make your vacancies, employer stories, and content optimally discoverable. You’ll also find a practical checklist and six strategies you can apply right away.
How do AI language models work?
During the webinar, we explored the workings of Large Language Models (LLMs) in detail:
- Training: Models learn from massive amounts of data—text, audio, video, and images. They calculate relationships between words and concepts rather than simply matching exact keywords.
- Functioning: Users provide a prompt (a question or instruction). The model generates an answer by combining relevant patterns.
- Application: LLMs pull answers not only from web pages, but also from video subtitles, image descriptions, and external platforms such as LinkedIn, Glassdoor, YouTube, and TikTok.
- Limitations: Models can hallucinate (produce incorrect or illogical answers) and do not have up-to-date knowledge beyond their last training point. This makes current, accessible content crucial.
- “What is it like to work at NS?” AI models combine information from career websites, Glassdoor, news articles, and employee videos into a summarized answer.
- “What does a day in the life of a technician look like?” Videos from 2022 and 2023 were used as sources, highlighting the importance of up-to-date, well-described video content.
- Prompt fan-out: AI often expands a question into sub-questions based on previous search or chat behavior, making the context increasingly personalized.
Key trends and insights
Google AI Overview
Google’s AI Overview combines traditional search results with a generated answer. Key features:
Users increasingly get their answers directly within search engines or AI models, without clicking through. For employers, this means your brand and content must already be visible in that first answer.
The role of structured data
Structured data such as jobPosting is essential for helping search engines and AI understand what a page is about. Without these signals, systems lose context.
Video and visual content
AI also uses videos and descriptions. YouTube descriptions and LinkedIn posts are included in answers. Content must therefore be multi-format and well-documented.
Employer branding and sentiment
AI models evaluate not only facts, but also sentiment. Negative reviews or unclear messaging can harm your brand’s position. Authenticity and consistency are key.
Google’s AI Overview combines traditional search results with a generated answer. Key features:
- A detailed summary at the top of the search page
- Links to relevant websites
- Source references displayed on the right
- Potential future ads (already being tested in the US)
Users increasingly get their answers directly within search engines or AI models, without clicking through. For employers, this means your brand and content must already be visible in that first answer.
The role of structured data
Structured data such as jobPosting is essential for helping search engines and AI understand what a page is about. Without these signals, systems lose context.
Video and visual content
AI also uses videos and descriptions. YouTube descriptions and LinkedIn posts are included in answers. Content must therefore be multi-format and well-documented.
Employer branding and sentiment
AI models evaluate not only facts, but also sentiment. Negative reviews or unclear messaging can harm your brand’s position. Authenticity and consistency are key.
Six strategies for discoverable job vacancies
1. Write helpful content
- Answer questions clearly: “What does a developer do at our company?” or “What is the application process for a BBL trainee?”
- Each paragraph should provide a complete answer on its own.
- Use schema.org tags such as jobPosting.
- Always publish first on your own careers website so you remain the original source.
- Create short, specific videos per role or target group.
- Regularly update company profiles, job descriptions, and vacancies.
Checklist for job postings
- Structure and clarity: title, subtitle, location, salary, application process
- FAQ section: answer common questions such as “How long does the application process take?” or “What can I expect in my first month?”
- Personal and concrete: write as if you’re speaking directly to a candidate
- Differentiation: explain why your organization is different from competitors
- Reviews and testimonials: include stories from employees, ambassadors, and external reviews
- Authority: highlight certifications, awards, or other trust signals
Conclusion The future of job visibility lies in the combination of SEO and GEO. SEO remains essential for being found in search engines, but AI models require content that is current, accessible, and above all helpful.
Organizations that invest in structure, rich storytelling, structured data, employer branding, and multi-channel publishing increase their visibility, strengthen their employer brand, and attract better candidates. Key takeaway: SEO is the foundation. GEO is the future. Together, they ensure your job vacancies are not only found but also chosen.
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