Human Resource Outsourcing

The role of AI in the hiring process

Attracting and recruiting talent is one of the main concerns for companies that are competing for talent in the global market. But with each open posts attracting thousands of applications, it has become challenging for HR managers to sort through all the applications and select the right candidates. About 52% of the recruitment and talent acquisition specialists find screening candidates from the application pool the hardest part of the recruitment process. According to SHRM's 2024 Talent Trends research, 26% of organisations already use artificial intelligence to support HR, and 64% of those apply it to recruiting, interviewing, or hiring, which makes understanding the role of AI in recruitment and the hiring process worth getting right.

But if you can automate the screening step or even other repetitive tasks in the hiring process, recruitment can become more efficient and effective. This is where artificial intelligence (AI) in recruitment and HR management comes into the picture, offering recruiters opportunities to disengage from repetitive screening tasks and focus on recruiting the best candidates.

AI for recruitment: Opportunities and challenges

AI for recruitment is the integration of AI solutions in the recruitment process, where machine learning models can help you shortlist ideal candidates, automate manual tasks, streamline the recruitment workflow, and free recruitment managers from repetitive high-volume tasks. The applications of AI in the hiring process also help you generate insights from the available talent pool, build screening tests to eliminate bias, and identify successful traits from candidates who have remained with the company. You can gain many benefits and opportunities if you integrate AI in the hiring process, including:

• Saving recruiters’ time from repetitive tasks to focus more on the best candidates
• Better quality of hire via standardised job matching
• Improved interaction, communication, and engagement throughout the recruitment lifecycle
• Removal of bias from the recruitment process
• Access to a larger talent pool to find suitable candidates for the job

These are among the most cited benefits of AI in recruitment: in SHRM's 2024 Talent Trends survey, nearly nine in ten organisations using AI in recruitment adopted it to save time or increase efficiency, and close to one in three report improved diversity of hires.

But AI-powered recruitment is still evolving, and some of the challenges you need to look out for are:

• Higher upfront costs
• Need for a lot of data for training and engagement
• Potential to learn human bias from patterns in the existing recruitment process
• Potentially losing human touch in recruitment
• Scepticism and hesitation in adopting new technology

How can AI transform your hiring process?

So, you are considering implementing AI recruiting solutions. But how will they transform your hiring process? Automation and making smart decisions may save companies thousands of dollars per employee every year, in addition to improving the work life. Therefore, it is not surprising that several HR departments and providers are attempting to capitalise on the advantages of AI. Recruiters can use AI-assisted automated recruiting to pursue a candidate-first strategy. They can make better hiring decisions by evaluating massive volumes of data from the job market and connecting with prospects on a frequent basis. Here are a few ways AI in HR recruitment can transform your hiring process.

• Simplifying the sourcing process:

   Finding and attracting the right candidates for an open position is a struggle well-known to talent acquisition specialists. With AI-powered recruitment, you can scan online resumes and social profiles of potential candidates at scale to find a more diverse talent pool suitable for your open position. In practice, this means the tool interprets a job description contextually rather than matching on job titles alone, so it can also surface candidates with transferable skills who wouldn't turn up in a simple keyword search.

• Enhancing employee experience:

   Once sourced, AI solutions can contact potential candidates and lead them through the recruiting funnel quickly. This ensures a smooth and positive candidate experience, which is a critical contributor to talent recruitment and retention.

• Boosting screening:

   As AI tools are always learning, they can boost your screening process by not just relying on the candidates that have applied for the position but also reviewing past applications to select the most suitable candidate. Moreover, you can train AI models to remove unconscious bias from the recruitment process to ensure an inclusive and diverse workforce. Screening tools typically rank each application against the job's stated requirements and produce a shortlist with the closest matches first, which is what actually saves recruiters the manual read-through rather than just speeding it up.

• Assisting interview process:

   Before inviting candidates for an in-person interview, AI in talent acquisition can help you check a candidate’s fit by offering job simulations, undertaking personality testing, and conducting a pre-set virtual interview. As a result, you can ensure that not only the candidates meet the job requirements but will also fit your company culture.

• Improving onboarding experience:

   AI-powered HR solutions go beyond just screening and interviewing and extend to onboarding as well. Automating repetitive tasks, such as conducting background checks, putting together the paperwork, and getting employees started with the necessary documentation, helps employees begin work quickly and enables the HR department to focus on other critical tasks.

How to use AI in hiring: Where to start

Most HR teams don't roll AI out across the entire hiring process at once. A narrower, staged approach makes it easier to check results before expanding further:

• Start with one high-volume step: Resume screening and interview scheduling are the two most common starting points, since they're repetitive, high-volume, and easy to measure against a clear baseline.
• Set a baseline before you switch on the tool: Record your current time-to-hire, cost-per-hire, and recruiter workload so you can tell afterwards whether the change actually helped.
• Connect it to your existing systems: A tool that integrates with your ATS and calendar tools avoids creating a second, disconnected workflow for recruiters to manage.
• Keep a human in the loop for final decisions: Use AI to narrow the pool and surface a ranked shortlist, but keep the actual hiring decision with a recruiter or hiring manager.
• Monitor and audit regularly: Periodically check the model's shortlists and outcomes against your workforce's real diversity and performance data to catch bias before it compounds.

How can Infosys BPM help?

Infosys BPM Recruitment Outsourcing solutions and services offer you end-to-end solutions for your talent supply chain, from sourcing and screening to onboarding. Infosys BPM Recruitment Outsourcing solutions and services can give you automated hiring system solutions custom designed to meet your recruitment goals. Whether you're just starting to explore how to use AI in hiring or already running AI-assisted screening, our team helps you apply it in the right places across the recruitment lifecycle.

Frequently asked questions

Will AI replace human recruiters in the hiring process?

No. AI is best at high-volume, repeatable steps such as screening, matching, and scheduling, and it shortens those steps rather than removing the recruiter. Judgement calls, such as assessing culture fit, negotiating offers, and building relationships with candidates and hiring managers, still sit with people, which is why most organisations keep a human decision-maker at the end of every AI-assisted step.

Is it legal to use AI in recruitment?

In most markets yes, but it is increasingly regulated. New York City, for example, requires annual bias audits of automated employment decision tools, and the European Union's AI Act classifies AI used in hiring as high-risk, with stricter documentation and human-oversight obligations. The employer remains responsible for discriminatory outcomes even when the recommendation came from a vendor's tool.

What data does AI in HR recruitment need to work well?

It needs structured, representative data more than sheer volume: accurate job requirements, clean historical hiring records, and outcome data showing which past hires succeeded. If the historical records reflect biased decisions, the model will learn those patterns, so the data should be reviewed and the model audited before it influences live hiring decisions.

How is AI in recruitment different from an applicant tracking system (ATS)?

An applicant tracking system (ATS) is the system of record: it stores applications and moves candidates through workflow stages, but every judgement is still manual. AI in recruitment is an intelligence layer that works on top of that record, ranking applications against requirements, predicting fit, and recommending next actions. Most AI recruiting tools plug into an existing ATS rather than replacing it.

How long does it take to start using AI in hiring?

It depends on the entry point. Tools for a single contained step, such as interview scheduling or candidate chat, can typically go live in a few weeks because they need little historical data. Screening and matching models take longer, since they must be configured on your job requirements and validated for accuracy and bias before they influence real shortlists.

Which benefits of AI in recruitment show up first?

Time savings appear first, because automated screening and scheduling remove manual effort from day one and are easy to measure against your previous time-to-hire. Benefits such as better quality of hire and improved workforce diversity take longer to demonstrate, because they can only be judged once AI-assisted hires have spent time in the role.