AI for Recruiting: Best Tools and Practices

Human Resources Concept

Nowadays, recruitment is no longer a mere job announcement posting but a complex process, more of a relationship-building affair than a candidate-filling task.

Reasonably enough, the success of the recruitment process is judged mainly by two major parameters: 

  • the quality of hire
  • the time spent for this hire. 

Thus, the recruiters and hiring managers came to consideration of such tech advancements as artificial intelligence and how it can create a more efficient talent acquisition process.

Today AI for recruiting solutions is an essential piece of the HR technology ecosystem, designed to automatically screen thousands of resumes, assess candidates, and reduce time-consuming manual tasks.

According to recent report, 56% of HR companies are already using AI for their talent acquisition, while by 2023, this number is to reach  77% of HR organizations.

This blog post explores AI in recruitment, its last year’s reportbenefits, critical challenges in its application, and significant AI use cases for recruiting technology stack. 

What is AI for recruiting?

In its essence, Artificial Intelligence encompasses identifying the correlations of a vast amount of data by leveraging ML algorithms and predicting the possible outcomes to empower decision-making.

For recruitment, applying AI to the talent acquisition process means shortlisting your ideal candidate, interviewing, onboarding, and automating numerous minor tasks.

Employers worldwide are turning to AI powerd solutions in the war for a quality candidate.

While a single job posting can attract thousands of applicants, the talent competition is heating up, and recruitment gets even more challenging for HRs and hiring managers. 

The benefits of AI in recruiting

A fundamental purpose of AI recruitment is to streamline the process and automate manual parts, like auto-screening candidates, managing communication, more effective interviewing and assessing candidates.

AI has some applications to help recruiting professionals hire smarter, faster, and without bias.

1. Improved quality and objectivity 

In some way all human being are biased. It is humanly impossible to restrict one`s thoughts, opinions, and perceptions from influencing decisions and choices.

Therefore, making objective decisions is always a challenging task. 

No matter how well thought is the process, there is a personal bias in selecting candidates in the screening process.

Even though AI is designed to imitate human intelligence, it initially lacks the schemes related to opinion-making. Therefore, it proves to be efficient in unbiased decisions in candidate filtering.  

2. Less irrelevant applications

As we mentioned earlier, a job posting can attract thousands of applicants, yet attracting the most suitable candidate is its actual intent.

While there are many effective ways to attract candidates, you may receive many applications but not the right ones and end up with more work and fewer quality candidates.

AI-powered solutions can make suggestions to write or write a job description for you, ensuring it will address the right candidates.

Furthermore, AI chatbots can enable an opportunity to offer hidden positions to candidates that meet specific criteria. 

3. Saved money & time 

Evidently, time and money are the most valuable resources at our disposal. Particularly in the recruitment industry, where it takes from 36 to 42 days to fill an average position, and the costs per hire reach $4 425.

Besides, manually going through the applications of candidates takes a lot of time out of a resourceful worker’s schedule.

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

AI for recruiting represents an opportunity for recruiters to reduce the time spent on repetitive, time-consuming tasks.

Furthermore, the best AI-powered solutions integrate seamlessly with the current recruiting stack not to disrupt the workflow.

4. Enhanced candidate experience and employer brand

Nowadays, hiring is more about communicating and building relationships with candidates.

Besides, no candidate wants to feel like a nameless cog in the recruitment wheel but to be engaged and experience a quality hiring process. 

Data proves that when conversational AI has been a part of the recruiting process, candidates offered a job are 38% more likely to accept.

Besides, according to the 2020 Job Seeker Nation Survey, AI helps deliver a positive candidate experience that became an expected norm with most candidates now. 

The challenges of applying AI for recruitment 

Undoubtedly, using AI, hiring teams can remove repetitive, time-consuming tasks from their workflows and get more time to focus on relationships, candidates engagement, and  hiring teams  training.

However, the application of AI is also related to some challenges. These are challenges that can be omitted but are likely to occur at some given point in time.

1. AI needs a lot of data

To learn and imitate human intelligence accurately, AI needs vast amounts of data. The development of human-like intelligence is a complex process that requires programming, framework, careful analysis, and assessment. 

Thus, for instance, to screen resumes like a professional recruiter, an AI-powered solution needs to go through several hundreds of resumes for each particular position. 

2. AI learns human bias

The accuracy and efficiency of the AI in recruiting depend on the data it learns from. Therefore, like any other being with intelligence AI can learn human bias from the data it is fed with. 

AI for recruiting helps avoid unconscious bias by ignoring information such as a candidate’s age, gender, and race. However, it is trained to find patterns. Thus, any human bias that may already be in your recruiting process could be learned by AI.

3. AI lacks human touch

On the one hand, the impartiality and freedom from unconscious bias make AI-powered solutions perfect soldiers in the war for quality talent.

On the other hand, some aspects in the hiring process that only feelings and perceptions of a human mind can perceive accurately. 

While an AI can do an accurate surface-level assessment of skills and abilities, a deeper analysis of social life, family orientation, moral values, and other factors cannot be fully evaluated by it.

4. Limited to a specific candidate pool

A successful application of AI technologies in recruiting requires candidates` application via specific systems, as it is vital to maintain a sense of organized decorum for the AI.

While this factor limits the ways an application can be submitted, it can be disadvantageous for both the candidate who cannot get an opportunity and the recruiter who may lose out on a resourceful employee.

AI best practices in recruitment 

Globaly, companies are increasing their HR and recruiting investments in AI. Roughly 9 in 10 companies globally have already been using AI in some way for HR.

While 63 percent of talent acquisition professionals say AI has changed the way recruiting is done in their organization.

AI for recruiting has numerous potential applications for automating high-volume, repetitive tasks such as resume screening and pre-qualifying candidates. Slowly but sure, AI finds its way to every stage of the recruitment process.

First of all, the growing popularity of AI-powered solutions is motivated by their efficiency. The following important factor is their availability to the wide range of companies of various sizes and financial capacities. 

Today, costs for the application of AI recruiting solutions are comparable with website development costs.

It requires some considerable investments at first yet brings versatile, valuable results all the way through.

Here are the most innovative uses of AI in recruitment that will give you a more precise idea of the benefits your business can get. 

  • Physical interview robots

Physical interview robots are now widely applied in recruiting across industries. The solution combines natural language processing and interview analytics to assess a candidate’s soft skills and personality traits. 

The robot creates a realistic and comfortable job interview for the applicant and a positive experience. However, the software is only as fair as the data it gets fed.

Examples: Tengai Unbiased 

  • Conversation analytics

We are all well familiar with conversational AI in the form of a voice assistant like Apple Siri or Amazon Alexa that can engage in human-like dialogue, capture context, and provide intelligent responses. 

In recruiting, similar technologies are used to automatically transcribe job interviews and pull out valuable insights so that organizations can interview more effectively.

Voice technology makes it easier for HR teams to sort candidates, streamline communication, and even schedule interviews.

Examples: Humanly. Io recruitment chatbot, Mya, HireVue

  • AI-powered background checks

While background checks seem to be just a formality to some recruiters and candidates, the reality is that regulations tend to evolve, and laws vary from one country and role to another.

The technology helps companies study criminal records, screen social media, and anything else that’s public on the web.

Applying AI-infused background technology saves time, reduces bias, and keeps candidates’ privacy safe. 

Examples: Chekr, Onfido, Intelligo

  • Automated reference checking

Reference checking usually takes place at the final stages of the recruitment process. This time-consuming collection of reliable references discloses some practical matters for final decision-making.

An AI-driven reference check automates the process and helps gather all relevant information in one place.

Usually, referees respond to scientifically designed questionnaires and get automated reminders to avoid hiccups. 

Examples: Jointl, Robin, Cernt

  • AI for internal mobility

Internal hiring is widely recognized as an efficient practice to save time and money for the companies. Besides, in this case, there is a higher chance that your new ‘hire’ is your perfect hire. 

The software uses data, pattern recognition mechanisms, and natural language understanding to gather insights into employees and roles and offers better visibility of opportunities and better match skills and jobs. 44 percent of HR specialists already use AI as an effective way to identify the best internal candidates. 

Examples: Gloat, Phenom People, Eightfold

  • Assessing team strengths and bridging talent gaps

One of the key trends prevailing in HR in 2022 is shifting the focus from individuals to teams.

Therefore, AI-powered recruitment solutions are widely used to combine data analytics with scientific testing to understand the deep-level characteristics of individuals and how these characteristics influence collaboration and performance in a team.

The basic idea of better hiring decisions remains the same, but the decisions are made with the teams in mind. 

Examples: Talocity, Harver, Teamscope

  • AI-powered talent marketplaces

Talent marketplaces connect employees with career opportunities and resources for professional growth. Powered with artificial intelligence, these platforms have become ‘talent marketplaces 2.0’, as they match employees with career advancement opportunities based on an individual’s existing skills and future goals.

Apart from freelancers and active gig economy players, numerous world-famous companies now actively use AI-powered marketplaces to hire the best talents.

Examples: Fuel50, Oracle Talent Management Cloud, 365Talents

  • Determining compensation

Determining the correct compensation rate for a new employee is often a challenging task for compensation and benefits manager or HR generalist.

Numerous elements should be taken into account and carefully analyzed:

  • Salary
  • Overtime pay
  • Bonuses and commissions
  • Retirement
  • Stock options
  • Vacation
  • Sign-on bonuses
  • Healthcare benefits

Therefore, AI-based solutions can cope perfectly well with such complex tasks. These solutions enable companies to consider the specific skill and geographic data when they price high-demand jobs in competitive markets.

Examples: PayScale Differentials Engine, Beqom, 

The future of AI in recruiting 

As the application of AI-powered solutions in HR is becoming commonplace, numerous new tools and platforms with various functions appear in the market almost every day.

In the years to come, we will witness the rise of AI-powered interviewing, onboarding, and hiring itself. 

Clearly, artificial intelligence can and will improve recruiting efficiency and effectiveness. Furthermore, it will definitely change the recruiter role in the process through augmented intelligence, allowing recruiters to become more proactive in their hiring. 

The recruiters will focus more on building cordial relationships with job seekers and current employees, taking care of their experience and satisfaction, while AI will cope with the routine.

The impact of AI-driven workforce management systems will for sure lead to improved quality and employee satisfaction.

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