AI and more specifically Large Language Models (LLMs) are changing the world of recruitment.

Recruitment has already become exponentially more data driven than it used to be.

Billions of candidate profiles are to be found across a variety of platforms and every profile has become more data rich than ever with people becoming more active on social media like LinkedIn, in forums like Reddit and professional open source websites like GitHub.

To be able to do something with this vast amount of data you cannot rely anymore on your human abilities only; it’s impossible to shift through a billion profiles one by one. That’s why we’re already using AI systems in recruitment like search engines which deploy AI to get from millions of profiles to just your top 100 candidates.

But the AI systems that are being used are becoming a lot more sophisticated with the more recent introduction of LLM’s like OpenAI GPT (GPT 3.5 and GPT4) but also a wide variety of other LLM’s like Google’s LaMDA + Bard and open source LLMs.

These new AI systems also allow for ‘Generative AI Recruitment’, which means they can generate content on top of being able to analyse them like conventional AI systems. 

Next to the fact that AI has already been proving itself as more than just a trend, the practical value for this technology, in the recruitment industry specifically, has also become a lot more clear.

The recent introduction of language models is particularly interesting for the recruitment industry.

Recruitment comes down to basically the processing of language.

Think about your daily activities as a recruiter:w

• Writing a job description
• Searching for certain job titles and keywords
• Looking at what a candidate has written on their profile
• Communicating with candidates

Language is the primary driver of recruitment activities and hiring decisions.

Recruitment = the interpretation of language and the enticement through language.

Being aware of the role that language plays in the recruitment profession is the start of better understanding the impact of language models in recruitment.

Examples of GPT powered recruitment solutions

Although AI language models can be powerful, they mean nothing without the right data. If you let GPT for example work on a limited database, you can also expect limited output. The size and relevancy of the data of the AI recruitment software are key in determining its usefulness for you.

Here are some examples of AI recruitment solutions in the market and their features:

AI Recruiter (Uwi)

AI Recruiter Uwi is a completely autonomous AI recruitment assistant. Uwi recruits talent for your job tirelessly by completely automatically search, screen and reach out to potential candidates based on your requirements and her general knowledge from the web.

Data: 1 billion profiles worldwide across a variety of platforms like LinkedIn, GitHub, Stack Overflow

Outreach: next to searching and screening, outreach is also completely automated with hyper-personalized prompted messaging and auto-follow up

RecruitGPT

RecruitGPT is a recruitment solution built by HeroHunt.ai. RecruitGPT can create a shortlist of candidates from just a single line description of who you’re looking for. You ask RecruitGPT for example “Hey RecruitGPT, find me a full-time java developer with Python, C# and API skills in Amsterdam” and it will give you the list with top matches in seconds.

Data: 1 billion profiles worldwide across a variety of platforms like LinkedIn, GitHub, Stack Overflow

Outreach: completely automated with messaging on autopilot and auto follow ups with verified personal email addresses

Seekout Assist

Seekout is a profile database. It allows recruiters to find hard-to-find talent with boolean search, but recently also with a more automated way of searching based on language models. Seekout also indexes profiles from GitHub, research papers, and patents. 

Data: 700 million profiles worldwide

Outreach: partly automated outreach with email (not always verified)

PeopleGPT

PeopleGPT is a very early stage recruitment solution based on the GPT language model with a database of primarily US profiles. The idea of PeopleGPT is that users can find talent based on a chat interface.

Data: database with a selection of LinkedIn profiles limited to US

Outreach: semi-automated with templates but one on one sending