The Future of Recruitment: Use of AI for Better Hiring

Recruitment has become one of the toughest, most challenging, and most time-consuming functions of HR (human resources).

Finding the suitable talent for the appropriate position at the right time is very important for the success and growth of any organization. 

Especially in MNCs, the challenges related to streamlining the whole talent acquisition process carefully while maintaining the goals of organizations in terms of the cost of hiring, the duration of hiring, and the quality of hires are crucial. 

However, these challenges can be addressed using a few modern technologies.  

The latest study from Workable states that, to find a qualified candidate for a single position, a single recruiter can spend 15 hours per week on average.

Also, 52% of recruiters feel that screening a candidate from a large list of applicants is the most difficult part of recruitment. 

In recent years, there has been a drastic increase in the use of artificial intelligence (AI) and machine learning (ML), which has simplified the hiring process.

What is AI in Recruitment?

AI technology is purely based on machine learning, where large amounts of information are deployed into the system, enabling it to replicate the decision-making skills of a human. 

The technology tries to keep it updated daily by learning from human behavior, allowing it to complete challenging tasks on time.  

Organizations can manage hundreds of CVs, screen and shortlist applicants, and conduct the first round of virtual interviews with the shortlisted candidates using AI sourcing tools.

These tools look for exact matching of profiles according to the job description without compromising quality. 

AI involves technologies such as machine learning, natural language processing, deep learning, speech recognition, text analysis, and image processing.

However, many vendors use AI to examine your present candidate pool for the best former candidates to determine the relevant candidates for the new role.

This list might consist of possible profiles that have been ignored for months or years.   

Machine Learning

Machine learning is used in recruitment to simplify the process of recruiting, reduce costs, and enhance the interview feedback of candidates.

However, the truth is that many organizations and recruitment agencies don’t want robots or chatbots to do all tasks.

Human-to-human communication is still required for both job advertisements and applicants, so there is no guarantee that AI can overtake everything. 

Moreover, in the era of recruitment, you can expect numerous fresh trends:

1. Quicker processing of data
2. Faster job postings
3. Automated engagement of candidates in a better way

Machine learning can simplify recruitment in the below-mentioned ways:

1. Recruiters have to find their problems and then implement machine learning to obtain results.
2. Evaluation strategies can be created using machine learning. Hiring managers can store the evaluation criteria in their machine learning model. In the end, they will be able to monitor its performance and make evaluations according to the criteria defined by you.
3. Machine learning assists in preparing the data, which is collected by you. It filters, formats, integrates, and processes the information.
4. Mistakes encountered due to human intervention can be eliminated by automated learning processes.
5. You can produce a complex model according to the type of inspection you want to execute.
6. Re-examine the problem that you wish to solve and adapt the algorithms to expect the desired results.

Generative AI   

Based on pre-existing data, generative AI produces fresh data. Large language models (LLM), including ChatGPT (versions 3.5 and 4), are a subset of generative AI.

They can produce human-readable text by understanding and making them valuable for activities starting from categorization and sentiment analysis to customization and content creation. 

The use of generative AI for recruiting has generated customized emails, targeted job advertisements, and job descriptions.

How is AI being used in Recruiting?

The process of recruiting the best talent is not an easy task, and it is expensive and subjective. Hence, organizations are moving towards emerging technologies to revolutionize this process.

So, they have adopted artificial intelligence (AI) and machine learning (ML) to optimize hiring workflows and talent acquisition due to their excellent capabilities.  

Recruiters use both of these technologies to identify relevant matches between companies and job seekers, accelerate the search for qualified candidates and resources, and save time throughout the hiring cycle.  

Simultaneously, personalization of customized content throughout the staff and candidate journey is important for a better experience.

AI can enhance the job candidate experience by displaying dynamic content related to job offers that are relevant to them.

AI personalization can create a comfortable atmosphere in the workplace by customizing career improvement paths, training programs, and internal advancements to match individuals.

The use of AI for recruiting speeds up the adaptive recruiting process by matching the needs of the organization, enhancing efficiency and accuracy.     

Listed below are a few examples of how AI is used in recruitment:

1. AI can manage various activities simultaneously, which can weaken the efficiencies of HR teams
2. AI-driven bots can manage pre-screening and the first round of interviews
3. It can alleviate employees from the onboarding process and allow fresh joiners to progress via the onboarding process. From assisting with training materials to providing surveys or questionnaires to check whether they grasp source deliverables or whether they require enough time

In addition, AI monitors all features of the process, ensuring nothing is missed.

To make proper use of AI in recruitment, businesses need to prepare well in advance, stick to the latest best practices, including identifying time-consuming areas, and reduce biased behavior.

According to LinkedIn, approximately 70% of recruiters are interested in deploying AI practices into the recruitment process to automate the recruiting cycle.

How is AI Transforming the Hiring Process for Companies?

Experts believe that AI will move into recruiting via augmented intelligence.

This is based on the idea that human abilities cannot be entirely replaced by technology; instead, technologies will be developed to increase human aptitudes and abilities. 

As said earlier, recruitment automation tools will automate boring tasks and use data intelligently.

Here’s how:

1. Hiring managers now have enough time to concentrate on hiring approaches, spending time with applicants to get to know them, and rapidly wrapping up workflows.
2. Automate the task of paid matching of talent and job
3. Automate multi-channel interactions and communications
4. It also guarantees that human bias is removed while customizing recruitment
5. Background verification of a candidate is one of the most complicated and time-consuming tasks, but it is equally important as evaluating skills. According to Unleash.ai, 92% of companies use AI for background checks to reduce risks. With AI-based background checks, companies can successfully follow private procedures to protect both the candidates and the company.
6. AI is used for candidate reference checking during the recruiting process. It’s not easy to gather profiles of candidates from various references, as it’s a tedious process. Employers ask for at least two to three references from candidates, and these references witness the ability of the candidate to do the job.

Moreover, the manual process of performing reference checks is complicated, as the few people added as references may not respond to calls or emails.

AI-enabled reference checking automates the whole process and assists hiring managers in assembling much-needed information at once.

Different Methods to Implement AI in Recruitment

The two critical elements for AI recruitment are streamlining and automation.

Recruitment automation means AI recruitment tools can scan through thousands of CVs based on the capabilities of the software. 

Resume review and automation

Recruitment software searches for particular keywords in resumes along with experience and other factors to pass them through to the second level of the recruitment phase.

This indicates that human recruiters are not involved in the first level of reviewing resumes.   

After scanning the resumes, personal information can be scanned by AI. Later, it can forward the data of interviewed candidates to the recruiter to review and inspect. 

Interviews and Scheduling

Scheduling and organizing the hiring process can be simplified by using AI.

Usually, AI programs have built-in calendar integration that enables job seekers and recruiters to look at each other’s schedules.

Like this, candidates can meet recruiters through automated interviews scheduled by the software. 

The reason for this automation is that it enables recruiters to spend more time with the most eligible candidates.

This enhances the possibilities for candidates to get recruited by an organization that suits them and lets recruiters completely evaluate the approach a candidate is likely to use in the workplace. 

Major companies, including Lensa and Checkr, are using AI in recruiting to improve their user experience.  

Types of AI Tools for Recruitment

Below-specified are the top AI recruiting tools:

Smart Screening

Smart screening is a software solution used primarily to automate the complete resume-screening procedure through AI.

The software updates itself by learning about the movements of candidates, types, and unsuccessful and successful employees based on their performance, tenure, and turnover rates and learning about present employees’ skills, experience, and so on.

Later, these insights are deployed for identifying fresh candidates, scoring them, and shortlisting the appropriate ones. 

These solutions might obtain candidate data from publicly available data sources such as social media profiles, industry databases, previous employers, and job boards. 

Personalized communication

As explained, AI-based chatbots can manage pre-screening and the first round of interviews.

They can ask a few questions to the candidates to determine whether they are suitable for the organization.

Organizations use bots for the interview process to ensure consistency and eliminate bias. 

Also, they can engage candidates by providing persistent contact and helping recruiters build a connection with passive candidates.  

Digitized interviews

AI models learn to understand parameters and data via machine learning. When it slowly becomes smart, HRs can expect more accuracy.

When it starts getting more training and collecting enough information related to assessing interviews, it smooths the recruitment cycle. 

How to Use Machine Learning for Recruiting?

ML in talent acquisition ensures better-personalized candidate experiences and enhances retention rates.

Let’s explore how ML is used in recruitment: 

Fetch information associated with candidates  

Machine learning is used by recruiters to identify a candidate’s data points, including work history, contact details, etc.

It allows candidates to concentrate on assessing the untouchables. 

Filling the hiring gap

Vacant job positions can have a bad impact on the productivity of an organization.

Recruiters rely on machine learning to use the relevant recruitment resources to close job openings by replacing unfilled positions with top talents. 

With abundant sources of data obtainable, recruiters use such sources to set acceptable expectations for clients by allocating suitable resources to fill job roles without losing accuracy. 

Reviewing resumes and social behaviors

Machine learning algorithms can look at resume data to understand the likes and dislikes of applicants.

They can decide the suitability of a candidate by looking at behavioral data from blogs, and social media channels.

This gives enough information regarding the candidate, such as experience, education, etc. 

How AI Hiring Tools are Transforming an HR Manager’s Role?

In the present competitive job market, businesses are using generative AI to optimize the hiring process.

AI-driven recruitment tools are transforming the whole hiring approach, enhancing efficiency, dependence on data, and cost-effectiveness.

AI hiring tools have revolutionized the HR manager’s role in the following ways:   

Efficient hiring processes

AI-powered talent sourcing strategies let you combine keywords and qualified candidate match points with its search tools.   

As the Applicant Tracking System (ATS) searches social channels, job boards, and various other combined tools, it will fetch top talents for the next screening and review. 

Increase in job acceptance rates

The majority of the latest hires indicate that straightforward, and transparent interaction processes allowed candidates to choose to come on board. 

AI-powered tools allow you to bring this experience to all candidates and hire the perfect talent via automated updates. 

Predictive analytics

Predictive analytics in recruitment can forecast the possibilities of candidate retention within a specific role. 

Scoring and ranking

Recruiters can form a strong connection with candidates who have done well in the interview when AI helps score and rank top resumes.   

What are the Benefits of Machine Learning and AI in Recruitment?

Here’s a detailed overview of the benefits of AI and ML in the recruitment process:

Smart recruitment automation

The applicant tracking system (ATS) is a recruitment software that provides a certain level of automation.

Hiring managers use it to store CVs neatly in the cloud, where they can maintain the applicant database.

Hence, AI in recruitment automation can help recruiters look through that applicant database. 

Apart from this, merging AI in ATS for different activities including recruitment marketing and video interviewing, businesses can increase their team’s performance.     

Improved integration of analytics

For detailed analysis, combining the data can lead to mistakes via human eyes, but the use of ML and AI can convert into a thorough approach where applicants are chosen according to their capabilities.  

Enhanced quality of hire

Both AI and ML can process huge amounts of data and provide insights that help companies make strategic decisions associated with hiring.

Next-generation recruiters use artificial intelligence to assess word choices and candidates’ facial expressions to evaluate whether they deserve the job.   

Eases internal recruitment

It eases internal recruitment within the organization. This includes employee referrals, promotions, and transfers between departments.

ML and AI sourcing tools for recruiting can access the database of an organization to extract data related to the hiring you’re planning.

It uses yearly candidate performance data and other sources accessible only to the organizational staff to make productive conclusions and recommend who of the present employees has the needed skills to fill vacant positions. 

Disadvantages of AI and Machine Learning in Hiring

Cost of implementation

For smaller companies, the implementation of ML and AI in recruitment can be costly.

This cost involves obtaining the technology, training employees, and maintaining and updating systems.   

Lacks human judgment

Interviews conducted by AI may lack the judgment that human recruiters can establish.

Candidates can feel ignored due to the absence of personal interaction in the initial phase of the hiring process.

They may not feel comfortable communicating with chatbots, resulting in a negative candidate experience.  

Data privacy concerns

AI-based recruitment tools depend purely on the analysis of thousands of pieces of data associated with candidates to make informed decisions, which raises data privacy concerns.

Data breaches, misutilization of data associated with the candidate, and biased algorithms can hurt candidates and employers. 

As candidates apply for jobs, there is a possibility that their personal and professional data might be misused.

They might not be sure how their data is being shared. So, companies need to ensure that their data is protected by data protection laws. 

Inaccurate recruiting decisions  

Even though AI can process thousands of pieces of data speedily, it leads to inaccurate outcomes. 

There is still doubt that it can 100% accurately evaluate a candidate’s capability.

What are the Challenges of AI Recruitment?

AI-powered recruitment has become a trend as many companies have adopted it, and the common challenges you have to look for are as follows:

AI tools never replace humans

Hiring recruiters and managers is still required for a few tasks, and AI recruitment tools never automate the entire process of recruiting.    

Chatbots can’t manage complexity

Multiple chatbots and tools with similar features can respond to simple queries, but they frequently run into trouble when facing more difficult queries. 

Overlooking eligible or qualified candidates

According to AI algorithms and criteria used for reviewing vast amounts of documents or sourcing candidates, it is possible to overlook eligible candidates that a recruiting manager would usually notice can be missed. 

Doubt regarding emerging technologies

HR experts are frequently bombarded with the newest trend that disappears just as rapidly.

Arguably, talent acquisition and hiring professionals can be doubtful of any software that guarantees to ensure their jobs aren’t difficult and improves the features of their hiring ecosystem. 

However, professionals and HR managers are a little slower to adopt AI and automation in recruiting.

A few people are still unclear about merging AI into the hiring process. This is still a challenge that remains completely uncovered.

Best Practices to Use Artificial Intelligence for Talent Acquisition

To make proper use of artificial intelligence in the recruitment process, it’s necessary to plan and follow basic best practices, as listed below:

1. Determine which regions are time-consuming, expensive, and manually handled
2. Adjust procedures to allow AI implementations
3. Validate the results for accuracy regularly after deploying AI
4. Get rid of biased behavior immediately to make sure the AI system won’t incorporate such biases
5. Observe and track performance to make sure the AI system is improving the process

What is the Future of AI in the Recruitment Process?

AI and automation can examine a candidate’s online presence, including their public data and social media profiles.

These technologies have the calibre to make predictions according to this data. For instance, consider how likely a candidate is to accept a job and in which role he or she might be interested.

Also, they can examine candidates’ profiles to identify whether they have started a job within the organization. 

By merging all this information, AI recruitment tools can find suitable candidates with similar skills and personalities.

They can categorize which candidates might be interested in specific roles and target them through personalized job advertisements.

So, AI in recruitment involves the execution of tasks such as visual and vocal recognition, translation, and decision-making. 

The majority of recruiting industry experts believe that AI is shaping and will continue to shape the recruiting industry.

The AI-driven Applicant Tracking System (ATS) will match and rank applicants automatically; identify cultural and technical fit; forecast the possibilities of applicant acceptance and evaluate expected time; and instantly “clone” matching candidates by sourcing nearly identical or dozens of profiles.

In simple words, AI has access to large databases of job requirements and candidate profiles.

This allows AI in recruitment and selection to find possible matches perfectly. This has reduced the search process and significantly enhanced the applicant placement rate. 

The objective of AI and ML is not to replace humans with technology. The arrival of automation is intended to produce more opportunities and improve human capabilities.

With fresh talent coming in, recruiters need to shift their attention to improving engagement so that they can understand the organization’s culture and objectives and work properly.

Recruiters need to understand that human communication can create a powerful foundation for the company, which builds the company’s reputation and results in major growth.

Conclusion

Recruiters are using AI and ML techniques to find top talents and predict their probable success. The recruitment sector is using artificial intelligence for candidate assessment to make the hiring procedure easier.

The future of AI and automation leads to intelligent data-oriented decisions by studying the behaviors of candidates. AI-driven applications aren’t replacing employees in your organization; instead, they can free up their time to perform many important tasks.

References:

The Role of AI in the Hiring Process

7 Effective Uses of AI in Recruitment

AI Recruiting: Uses, Advantages, & Disadvantages 2024

How will AI/ML Define the Future of Recruitment Industry

Using AI for recruiting: Complete guide for HR pros

Pros and Cons of Using AI in Recruiting

The 12 pillars of an effective recruitment process

AI Recruiting: Trends, Implications, and Usage in Tech Recruiting