How AI in Recruitment Can Revolutionize Your Hiring and Talent Teams

The use of AI in recruitment is not exactly a recent phenomenon, but the rate at which companies are adopting AI recruiting tools is accelerating fast, and it’s clear that those who fail to adapt will soon be left behind.

At Business2Community, we want it to be easy for you to access the facts you need, so we’ve compiled this curated list of AI in recruitment statistics to provide powerful insights into the current state of the market and the direction it’s heading in.

How is AI Used in Recruitment? 

Recruiters are using AI recruiting tools to assist with almost all aspects of the hiring process, from posting job ads to screening resumes and conducting interviews.

By harnessing the power of data analysis, AI tools can help judge a candidate’s suitability for a role, including their cultural fit for a company, in a microsecond. They also help to reduce human bias that may unconsciously influence candidate selection.

A recent study by Tidio found that 65% of recruiters are already using some kind of AI tool in the recruitment process, and around the same percentage of candidates believe that AI has been used in their recruiting process.

Eightfold.ai’s 2022 Talent Survey places this number even higher. From the 250 HR leaders surveyed, 73% said they were already using AI in recruitment and hiring, and 41% said they were planning to increase their use of AI in this area in the coming year.

Meanwhile, LinkedIn’s Future of Recruiting 2023 report found that 68% of hirers were “very hopeful” or “cautiously optimistic” about the use of generative AI in the recruiting process. 74% hoped that generative AI would help them prioritize strategic work by automating repetitive tasks, and 67% hoped it would make it faster and easier to source candidates.

AI recruiting tools are certainly nothing new, though; the global AI recruitment market was valued at $661.56 million in 2023, according to MMR, and is expected to grow to $1.12 billion by 2030, a CAGR of 6.8%.

The most common applications of artificial intelligence in recruiting in 2023 are:

1. Process automation
2. Campaigning
3. Candidate screening
4. Candidate communication

This is expected to remain much the same as the market grows in the coming years.

Let’s explore some of the specific ways that companies are using AI in recruiting.

Writing Job Descriptions

Generative AI can write job descriptions much faster than humans and, with the right AI model and smart prompting, they can make them much better and less discriminative.

Even though it has been illegal to advertise jobs by gender in the US since 1973, it’s very easy for gendered wording to appear in job descriptions unintentionally.

A Harvard study found that stereotypically masculine words like “competitive”, “dominant”, “ambitious”, “assertive”, and “leader” were more likely to be used in job ads for male-dominated occupations (97%) than female-dominated occupations (70%).

Stereotypically feminine words like “supportive”, “compassionate”, “understanding”, “committed”, and “interpersonal” appeared in 57% of ads for male-dominated professions vs, 67% of female-dominated professions.

The study found that job ads using more masculine wording:

• Were perceived as having fewer women in the occupation
• Were perceived as being less appealing to women and more appealing to men
• Led women to have a lower sense they would belong in the position

This is just one example of how a job description can contain unintentional bias.

Generative artificial intelligence tools can be trained to identify potentially discriminative terms in job descriptions, as well as empty or cliched language that does nothing to help potential candidates learn about the role or the company.

When IBM implemented its own AI recruiting tool – Watson Recruitment – which includes job description analysis, the company was able to reduce its cost-per-hire rates and filled positions in 40 days in 2016.

Screening Candidates and Assessing Talent

Perhaps AI’s most obvious advantage in the world of recruitment is talent screening.

63% of the recruiters surveyed by Tidio believed that AI systems will completely replace human recruiters in the process of screening candidates.

43% also cite this stage as the most challenging part of the entire hiring process.

This is perhaps unsurprising; AI recruiting firm SmartAI stated that an average of 75% of applicants are unqualified, and sorting through them is a big time drain for recruiters. Searching through multiple job platforms looking for specific qualities and requirements to find a few strong candidates can take forever for humans but just a few seconds for AI models.

When Withum was contracted to assist with applicant screening for a government agency, it used natural language processing (NLP) AI tools to scan and extract data from resumes. It led to manual data extraction from resumes being all but eliminated and reduced the time to close on forms.

Communicating Via Chatbot

Chatbots are one way that AI is improving the candidate experience. These tools can answer common questions about the job or company and keep candidates updated during the various steps of the recruiting process.

Chatbots use NLP to understand questions and formulate replies.

Research firm Gartner estimated that by 2023, 75% of HR inquiries would begin with conversational AI platforms.

Global recruiting firm Adecco implemented an AI chatbot in the screening process to ensure only qualified candidates were able to progress to the next stage in the process. The company saw a 75% decrease in questions directed to HR and customer support and from its live chat function and phone calls were reduced 50%.

Scheduling and Conducting Interviews

According to Workable’s AI in Hiring 2024 Survey, recruiters are already implementing AI in the interview process:

• 37.6% use AI-powered tools for scheduling interviews
• 19.9% use AI-driven games or tests to assess candidates’ skills or personality
• 19.4% use AI to analyze video interviews for traits and sentiment

Some are even using AI to conduct preliminary interviews without human involvement, although candidates tend to find this experience unsettling and devaluing, according to a study from the University of Sussex.

Final Hiring Decisions

Workable’s Hiring Survey looked at how companies were using recruiting AI to make final hiring decisions across different industries.

Only 0.7% of respondents said they relied purely on AI recommendations for these decisions, although the accounting and finance sector is some way ahead at 3.8%.

6% of people said they rely mostly on AI recommendations, 21.1% said it’s equal between AI and human influence, and 56.8% said they use AI as a tool to support human decisions.

Interestingly, the technology sector – the birthplace of artificial intelligence – seems most reluctant to use it. This industry had the highest percentage (17.3%) of people who said they rely solely on human judgment for final hiring decisions, and none who rely solely on AI.

Who Is Using AI in Recruitment? 

MMR reports that the enterprise segment is the largest end-user of AI in recruitment, accounting for 22% of the global market. Geographically, North America dominates the market with a 37% share.

Here are four companies already using AI to find more qualified candidates, make more informed decisions, and ultimately improve the hiring process for all involved.

LinkedIn Recruiter

LinkedIn Recruiter launched in 2008 to help hirers find the right candidates on the business networking platform. Since then, the company has been able to scale the tool to meet the needs of today’s recruiters by leveraging AI in several different ways.

LinkedIn Recruiter’s Skills Match function, launched in March 2023,  aims to help recruiters find the best candidates based on their skills, rather than their employment history or education. It does this, in part, by pulling the relevant information from candidates’ resumes and making it easily accessible within the platform.

More recently, the company has added a feature that lets users send personalized messages to potential candidates using generative AI. Personalization brings a 40% increase in message acceptance rates, the company says, and this new AI feature helps recruiters engage with the right talent, faster.

This AI tool is trained on data from LinkedIn’s messaging system, helping it understand how to optimize a message for the best chance of engagement during candidate outreach.

National Safety Apparel & HireVue

Protective clothing manufacturer National Safety Apparel (NSA) used HireVue’s conversational AI and automation technology to capture, screen, and schedule interviews with candidates.

In just a few minutes, potential employees could find a role, complete a pre-screening check, and schedule an interview.

The results included:

• 5 times faster time to interview
• 4 times faster time to hire
• 50% reduction in cost per interview
• 25% reduction in cost per hire
• 10% increase in retention

PricewaterhouseCoopers (PwC) & Workday

One of the “big four” public accounting firms in the US, PwC reported processing 500,000 job requisitions in a three-year period, resulting in over 6 million applications.

The company turned to Workday’s applicant tracking system (ATS) to streamline the talent acquisition process and ultimately save an estimated 9,000 hours in a fiscal year. Even small efficiencies, such as automating requisition creation, added up to make a significant difference in a company of this size.

Workday uses AI and machine learning technology to reduce repetitive tasks for recruiters, focus on skill-based hiring, and diversify the candidate pool for each role.

Workday is the most popular ATS used by Fortune 500 companies, according to Jobscan. 26.3% used it in 2019, and this figure grew to 38.5% by 2023.

Workday also uses AI to assist HR teams with talent management, developing individual learning pathways for each employee based on their skills and personal goals, combined with the future needs of the business.

L’Oréal & Mya

Having to assess a million applications for 15,000 jobs each year, L’Oréal was able to make great savings by using chatbot Mya to screen candidates, answer queries, and gather information such as their availability and visa requirements.

For one internship program, which sees 12,000 people applying for 80 places, L’Oréal’s recruiting team saved 200 hours while also hiring their most diverse group of interns yet. The chatbot was able to screen for things like visa requirements and schedule availability.

Once past Mya, candidates progressed to another tool called Seedlink. This program scored candidates’ answers to long-form questions to help humans make decisions about whether to move a candidate along the recruiting process.

Benefits of AI in Recruitment

The Tidio survey found that 67% of recruiters were positive about the use of AI-powered tools in the recruitment process. The main benefits cited were:

• Freeing up recruiters’ time (44%)
• Providing valuable insights (41%)
• Making the recruiter’s job easier (39%)

Let’s look at the potential benefits in more detail.

Improving the Recruitment Process for Candidates

Applying for jobs can be a frustrating process for job seekers, and AI-powered technology has the potential to ease certain pain points along the way.

The most tiresome and frustrating parts of applying for a new job, according to Tidio’s survey, are:

• Lack of feedback after applying (48%)
• Long recruitment process with multiple stages (40%)
• Having to repeat information in a job application form that’s already on their resume (37%)
• In-person interviews (30%)
• Multiple unpaid screening assignments (26%)

Recruiting AI is helping on a number of fronts, including:

• Chatbots which are able to improve the candidate experience by providing updates and feedback
• Reducing the amount of time the hiring process takes
• Pulling information from resumes to populate application forms

Cutting Costs and Increasing Efficiency in the Recruiting Process

A recruiter may only spend around 7.4 seconds reading a resume, but the average number of applications received for a job ad is 118, meaning there is a lot of time spent on basic admin in recruitment.

AI recruiting tools can drastically reduce the time spent on administrative tasks, leaving recruiters with more time to focus on nurturing and interviewing the most suitable candidates.

Workable’s AI in Hiring 2024 Survey of 950 professionals who already use AI in recruitment reported the following benefits:

• Speeds up the hiring process (89.6%)
• Reduces time spent hiring (85.3%)
• Reduces the cost of hiring (77.9%)

The industries that benefited most from cost savings were:

• Construction: 86.7%
• Technology/SaaS: 85.4%
• Retail: 82.1%
• Accounting/Finance: 81.3%
• Manufacturing: 76.7%
• Healthcare: 72.5%
• Education: 66.3%

Data published by Market Research Future showed that in North America, companies that use AI in their HR processes save an average of 40%.

Cost savings were around 36% in Europe, 25% in Asia-Pacific, and 20% in the rest of the world.

Overcoming Recruitment Bias in Hiring Managers

68% of HR professionals think that using recruiting AI will help remove unintentional human biases from the process. However, only 43% of job seekers share the same view, Tidio reports.

95% of the HR leaders who contributed to eightfold.ai’s Talent Survey said they are already using AI to support their DEI efforts.

This includes skills-based hiring (45%) and blind resume reviews (26%), although this still represents a large proportion of those who are not yet making use of this technology to find top talent without bias.

Although AI has the potential to identify the most relevant candidates without considering age, gender, and ethnicity, there are other, less obvious ways that human biases can creep into AI systems unnoticed, as we will cover later on.

Challenges of AI in Recruitment

Despite all the potential benefits, employers may be reluctant to fully embrace AI recruiting because of poor public sentiment.

Pew Research reported in 2023 that 66% of American adults would avoid applying for a job if they knew the recruiter was using AI in the process.

The top reason, cited by 44% of people who would not apply, is that AI would miss the “human factor” in the hiring process. 10% said they had concerns about AI making mistakes and having design flaws.

41% oppose using artificial intelligence to review job applications, while 71% are against allowing AI to make final hiring decisions.

Here are some of the reasons why people are reluctant to allow AI into human resources processes.

Manipulation of AI Recruitment Tools

89% of applicants believe there is a use for AI tools on their side of the process, according to Tidio’s survey. However, the report also found that 90% of people believe AI-powered recruiting software has the potential to be manipulated in some way, for example, by using the right keywords in a resume.

This is supported by Workable’s hiring survey, which found that 31.2% of professionals already using recruiting AI were worried about tools placing too much emphasis on keywords. This results in them favoring applicants whose resumes are well-optimized and potentially overlooking other qualified candidates.

LinkedIn, for example, alongside releasing AI recruiting tools to help hiring managers, is also giving job seekers a hand optimizing their profiles with generative AI.

Meanwhile, tools like LazyApply are making it easier for candidates to apply for jobs across multiple job boards in bulk.

It’s easy to see how we will end up in a battle of artificial intelligence: the recruiting AI tools working to filter through thousands of AI-generated applications and sort the most qualified candidates from those who just knew which buttons to press.

Overlooking Unconventional Applicants

In the Tidio survey, the main concern recruiters expressed about the use of AI in recruiting was that it could cause them to overlook atypical talents and qualities – 39% cited this as a potential drawback.

This also emerged as a concern in a Pew Research study of American adults. Although 47% believed that AI tools would be better than humans at treating all job applicants in the same way, 44% said that AI would be worse at seeing potential in “out-of-the-box” candidates who didn’t perfectly fit the job description.

Algorithmic Bias

Although many HR professionals are hopeful that AI can help overcome unconscious bias in recruiting, this does remain a significant challenge for machine learning models.

An AI system can only make decisions based on the instructions and data that it is trained on, so any inherent bias in that data will result in an algorithmic bias when screening resumes.

Examples of this include:

• Giving preference to candidates with an unbroken work history which favors men who are less likely to have taken time off for parental and caring responsibilities.
• Matching candidates who are most likely to apply for jobs, which favors men who are typically more aggressive in submitting applications – a problem that LinkedIn’s recruitment algorithm experienced in the past.
• Training AI models based on past hiring decisions, which may include human gender discrimination, as Amazon discovered its algorithms were doing in 2015.
• AI models showing negative sentiment towards people with Afro-American names compared to those with Euro-American names, as reported in a paper published on Arxiv.

Hiring managers seem quite aware of this potential problem. In eightfold.ai’s Talent Survey, two of the stated barriers to adoption were:

• AI cannot make better decisions than humans (36%)
• AI is inherently biased (17%)

The Future of AI in Recruitment

The many exciting developments in AI recruiting are helping recruiters spend less money and time on finding the best candidates. These tools are proving particularly helpful with time-consuming tasks like screening resumes, although some are going as far as to let artificial intelligence make hiring decisions.

However, the general consensus across all sources we studied to gather these AI in recruitment statistics is that while AI can be a great help to recruiting teams, it is in no position to fully replace humans – at least not yet.

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