Definitive Guide to AI in Recruitment

Whether you’re new to AI or looking to deepen your knowledge, this blog post will equip you with the essential information and practical tools needed to integrate AI into your recruitment practices effectively.

To explore AI-powered recruitment in greater depth and enjoy visually engaging content, we highly recommend downloading the complete Definitive Guide to AI in Recruitment. 

This blog post includes shorter versions of the following chapters:

• Essential terminology
• Key data sources
• Benefits of using AI in recruitment
• Use cases for AI-powered recruitment
• One example of an AI tool: TalentAdore Hire

The full guide includes all the chapters above and also the following: 

• Practical examples: 5 AI-based recruitment tools
• Pitfalls of AI-powered recruitment
• Cautionary examples
• Privacy & data security of AI in recruitment
• AI legislation

Essential AI terminology

Let’s start with a short “crash course” in basic AI terminology, so reading the rest of this blog entry will be a breeze!

The Internet is full of definitions for artificial intelligence, machine learning, deep learning, and artificial general intelligence. To successfully use AI in recruitment, you should know some basics. Here you will learn simple explanations for some of these terms and in the visual guide even more.

LLM (Large Language Models): A large language model is an AI system that has been trained on large datasets to generate human-like text and to understand and communicate in natural language.

Natural Language Processing (NLP): Natural language processing enables computers to analyze, understand, and generate human-like language.

Generative AI: Generative artificial intelligence refers to AI models and algorithms capable of developing new, synthetic data like images, audio, text, or code based on training data.

Artificial Intelligence or AI: Artificial intelligence refers to computer systems capable of performing tasks that typically require human-like intelligence, such as visual perception, speech recognition, decision-making, and language translation.

Machine Learning: Machine learning involves the use of algorithms and statistical models that allow computer systems to perform specific tasks effectively without being explicitly programmed by learning from data.

Deep Learning: Deep learning is a subset of machine learning that uses artificial neural networks with multiple layers to learn from and make intelligent predictions on data such as images, sound, and text.

Artificial General Intelligence: Artificial general intelligence (AGI) refers to the hypothetical ability of an artificial intelligence system to understand and learn any intellectual task that a human being can in an intelligent, conscious manner.

Data sources

How can you leverage data effectively when using AI in recruitment? You can harness valuable human resource data from three primary sources: Applicant Tracking Systems, HR management systems, and various online platforms.

For example, recruitment processes and employment relationships generate vast amounts of data, typically stored in applicant tracking systems (ATS) and HR management systems. Unfortunately, many companies fail to systematically enrich or effectively utilize this data.  Fortunately, AI tools can help you unlock the potential of this information. 

Additionally, online platforms provide standardized public data sets, though the company using this data does not own it. A good example of an online platform is ESCO, the European multilingual classification of Skills, Competencies, and Occupations. ESCO works like a dictionary, describing, identifying, and classifying professional occupations and skills relevant to the EU labor market and education and training.

Benefits of using AI in recruitment

According to a study by Ideal, HR managers lose an average of 14 hours per week on manual tasks that could be automated.

Over the next decade, AI will heavily affect how we attract, hire and retain talent. But why should you use AI in recruitment in the first place? These are the top 5 reasons. 💡

1. Improve the quality and objectivity of recruitment

Recruiters, being human, are inherently prone to bias. This means that recruiter A might hire a candidate whom recruiter B wouldn’t even consider for an interview. Much of recruitment is influenced by subjective feelings, and the criteria used can often be arbitrary.

AI has the potential to significantly reduce human bias in recruitment through various mechanisms and strategies. Here is one example: 

Blind recruitment: AI systems can anonymize candidate information, such as names, genders, ages, and ethnicities, during the initial screening process. This helps prevent unconscious bias related to demographic factors.

2. Attract the right candidates and receive fewer irrelevant applications

Attracting the most suitable candidate is an important goal for any organization. While there are plenty of ways to attract candidates and new methods are often introduced, job ads still have their place.

But what happens if the job ad doesn’t give the right impression? You may receive many applications but not the right ones. You end up with more work and fewer quality candidates.

Artificial intelligence can help you by giving tips for writing a job ad, or even writing a job ad for you. Also, chatbots and matching technology can be used to direct candidates to apply for relevant jobs and also do the pre-screening on your behalf.

3. Never overlook candidates again

We often tend to evaluate candidates on the wrong merits, such as the visual excellence of a CV –  even when graphic skills are not relevant to the position at hand. This can lead to bias in the screening process.

AI can evaluate candidates without depending solely on keywords or the recruiters’ personal preferences. It analyzes the entire content of candidates’ documents, understanding the expertise and skills behind the words. This comprehensive approach helps ensure that no qualified candidate is inadvertently overlooked.

4. Save time and fill positions faster

A common problem in recruitment is that the process often takes too long, causing top candidates to accept offers from faster-moving companies. Wouldn’t you prefer to streamline your recruitment process and avoid frustrating both yourself and your candidates?

According to a study by Ideal, HR managers lose an average of 14 hours per week on manual tasks that could be automated. AI can save significant time across various stages of recruitment, including writing job descriptions, analyzing candidates, and communicating with them. By leveraging AI recommendations, you can prioritize and contact the most suitable candidates first, filling open positions more quickly.

5. Enhance the candidate experience and employer brand

Communication with candidates significantly improves candidate experience and in the end, enhances your employer brand. Based on the study by Career Arc, 69% of job seekers believe the response time to candidates awaiting a recruiting decision can be improved the most.

With AI, you can efficiently communicate with job candidates, even if you receive thousands of applications annually.

• AI chatbots can automatically answer candidates’ questions
• AI assistants can help craft personalized messages to each candidate, keeping them informed about the recruitment process.
•  AI matching can recommend the most suitable positions for candidates before you even speak with them.

How to use AI in recruitment?

Unlock the potential of artificial intelligence in recruitment with these practical use cases designed to enhance your hiring process and improve candidate selection.

1. Candidate Communication 💌

Communicating with candidates via status updates, chatbots, and feedback messages. 

2. Sourcing Candidates 🔎

Sourcing tools for finding candidates automatically from internal talent communities.

3. Predictive Analytics & Simulations 📊

Predicting what kind of a person would fit the team and recognizing when a new employee is needed. 

4. Matching Candidates 🧩

Automatic recommendations of the most suitable candidates to enhance the diversity in recruitment. 

5. Intelligent Analytics ⭐️

Metrics about candidate experience and candidate relevancy to develop the recruitment process. 

6. Content Creation ✍️

Creating better-targeted job ads to avoid irrelevant applications and save valuable time. 

How about the downsides?

AI can be a powerful tool when used correctly, but the age-old adage “an excellent servant but a terrible master” exists for a reason. AI is not infallible, as it is created and operated by humans who are also imperfect. 

Therefore, while it is crucial to recognize the benefits of AI, it is equally important to understand the pitfalls to avoid in its application.

To learn about the pitfalls of AI in recruitment, AI legislation, and cautionary examples, download the full Definitive Guide to AI in Recruitment.

TalentAdore Hire AI Assistant

AI has been a part of TalentAdore’s solution since our company’s inception in 2014. Features in our ever-growing suite of AI products are built specifically for recruitment tasks and are designed to improve the lives of recruiters and candidates alike. We also strive to make our product the most secure recruitment software in the market.

Meet your personal AI Assistant – a seamless part of our end-to-end recruitment software, TalentAdore Hire. Streamline your recruitment processes by removing bottlenecks in job ad creation, screening, and communication. Provide superior candidate experiences to each applicant – every step of the way.

Request a personal demo to see our AI-assisted recruitment software in action. ✨