With modern advancements in technology, there is a question most hiring managers have not really sat down to answer. Which parts of the recruitment process should AI do, and which parts should be done by humans?
It’s not a small question by any means. More than 87% of companies are now utilizing AI tools somewhere in their hiring process. The growth in usage has already boosted the market value of AI recruitment tools to a total of $703 million.
Why Are Businesses Using AI Recruiting Tools?
Artificial intelligence can significantly speed up the slowest parts of talent acquisition. It can help hiring teams sort through large volumes of applications in minutes, scheduling interviews, and drafting outreach and candidate summaries, likely in a fraction of the time it would take to do so by hand.
Apart from speed, AI also helps bring down the cost of hiring by automating administrative tasks that would otherwise require additional staff or longer hours. Furthermore, sourcing tools using AI technology can also scan job boards, professional networks, and public profiles to source qualified candidates that a human recruiter might not have found through traditional channels.
That said, these benefits only appear when AI is used in the right place. Used elsewhere, it could slow down the hiring process and even work against the company.
Which Part of Recruitment Should Be Automated?
The best way to determine which task is ready for automation comes down to two factors: how complex the work is and how much is at stake for the company. Work that is repetitive and follows a set of rules is the easiest to hand over to AI systems, especially when the cost of a mistake is small.
The tasks below are where most HR teams find the best results in automation.
1. Resume Screening and Initial Shortlisting
Applicant tracking systems using AI can easily scan thousands of resumes in minutes, filtering for the skills, candidate experience, and qualifications the vacant role calls for. The same criteria are applied to every application that comes in, which keeps human bias out of the equation.
A common setup can involve having AI auto-advance the top 15-20% of job seekers and auto-reject the bottom 50-60%. Talent acquisition professionals should then review the 20-30% of prospects who are in the middle.
2. Candidate Sourcing
AI models can scan professional networks, job boards, and talent databases at the same time. It can also surface passive candidates who might not be actively looking for work but whose profile meets or exceeds the job description and requirements for the role.
Automating the sourcing process helps free hiring managers, especially executive recruiters, to do more work that closes hires and builds long-lasting relationships for companies.
3. Interview Scheduling
Scheduling interviews is one of the most time-consuming and lowest-value tasks for recruitment teams. Automated scheduling tools can easily integrate with calendars, send reminders, reschedule, and coordinate multi-panel interviews without the need for human oversight.
The same principle can be applied to requesting reference checks and background screening.
4. Job Description Writing
Generative AI tools, especially those trained on employer-brand guidelines and role requirements, can help in writing job descriptions, job advertisements, and recruitment-related social content at scale. This removes the bottleneck that often happens as a result of poorly-written job briefs.
5. Candidate Communication
One of the easiest ways to lose potential candidates is slow response times. Thankfully, AI chatbots can be set up to intercept first-touch requests after hours, answer common questions about the role or company, and provide timely status updates.
Automating these communications can significantly improve candidate experience and reduce the risk of job seekers dropping off in the middle of the hiring process.
According to research, 50% of candidates reject offers due to slow timelines. Employers also lose 34% of candidates to competitors who respond faster.
6. Assessments and Skills Testing
Hiring managers can reduce time-to-hire by using AI to deploy pre-designed psychometric, cognitive, and technical assessments from validated providers. These tests can assess candidates and provide HR teams with scores and standardized data on the capabilities of candidates.
Assessments coupled with AI screening tools can help weed out false positives—candidates who may appear good on paper but lack demonstrable competence.
Which Part of the Hiring Process Should Not Be Automated?
Some parts of hiring carry real ethical and legal consequences if mistakes happen. These are the tasks that need human insight to prevent any issues that could damage your company’s reputation and cause unnecessary delays.
1. Final Hiring Decision
AI tools should only be used to inform hiring decisions, but never to make them unilaterally. Artificial intelligence can rank candidates and flag strong matches, but only an HR professional can see how likely someone is to work with a specific manager or if the job applicant’s experience can translate when they’re placed in a team.
Most employment regulations, including those covering discrimination, hold the employer responsible for any decisions made. If an AI system rejects a candidate on grounds it cannot explain, the company would be the one answering for it.
2. Soft Skills, Emotional Intelligence, and Cultural Assessment
A person’s empathy, adaptability, and leadership presence are things that can only come out during conversations. These mostly show up in how a candidate tells their story or presents themselves during interviews, or how they react when a question catches them off-guard—cues that AI cannot read reliably.
Interviews are also a great way of establishing rapport with a candidate. A report found 69% of candidates say their experience during interviews influences how they see an employer or company.
3. Interpreting Non-Standard Candidate History
AI can look at an applicant’s past hiring data, so it tends to favor candidates whose resumes and profiles are similar to those of the people the company has hired before. This means those with non-standard experiences, like veterans, career changers, and neurodivergent individuals, are at a disadvantage.
A human recruiter can see the gaps and growth of a candidate from their resume that an AI system would easily miss.
4. Offer Negotiation
One of the most relationship-intensive moments in the recruitment process is the offer stage. A personal call is preferred, especially for senior and competitive hires. Negotiation is an art. It requires emotional intelligence, which AI does not possess.
5. Diversity, Equity, and Inclusion
DEI work is not something AI should ever handle on its own. AI is designed to pick up patterns from past hiring data. If the data carries bias, the AI agent will carry that forward as well.
Amazon’s recruiting tool is a great example. It systematically discriminated against resumes containing the word “women’s” because it had more male resumes in its training set.
Key Takeaway
AI can accelerate the recruiting process, make it more standardized and easier to manage, but it should never take accountability out of the equation. It is best to use AI-powered systems to automate repetitive, rules-based tasks and leave decisions requiring a lot of judgment to trained recruiters and hiring managers.
It’s not the companies with the most automated hiring processes that have the best hiring processes. They’ll be the ones who think through the automation, who audit the AI-generated results on a regular basis, and keep the hiring decisions fair and human-led.
