Most HR professionals have already worked with AI powered resume screening or applicant tracking systems.
Agentic AI is different.
Instead of waiting for human instructions at every stage, these systems can make a series of decisions on their own.
For example, an AI agent may search multiple job portals, shortlist candidates, send interview invitations, answer applicant queries, recommend salary ranges and prepare a final hiring report before a recruiter even reviews the applications.
This level of automation undoubtedly saves time.
At the same time, it raises an important question.
Who is responsible if the AI makes a wrong decision?
From a legal perspective, the answer is becoming increasingly clear.
The responsibility remains with the employer.
Using AI does not transfer accountability to the software vendor. HR professionals must therefore treat AI decisions with the same seriousness as decisions made by their own recruitment team.
Protecting Candidate Data Is No Longer Optional
Recruitment involves collecting a significant amount of personal information.
Resumes often contain educational qualifications, employment history, salary details, addresses, mobile numbers, email addresses and, in some cases, identity documents.
The DPDPA places clear responsibilities on organizations that collect and process this information.
Before implementing any AI recruitment platform, HR should ask a few practical questions.
Has the candidate been clearly informed about how their data will be used?
If the AI decides to consider the same candidate for another position, has fresh consent been obtained where required?
Can the candidate request deletion of their personal information after the recruitment process is completed?
Does the system permanently remove the data when such a request is made?
These questions are no longer matters of good practice. They are becoming important compliance considerations for every employer.
HRMIT Insight
Collect only the information genuinely required for recruitment. Holding unnecessary personal data increases both compliance obligations and organizational risk.
Hidden Bias Can Enter Recruitment Without Anyone Realizing It
Most organizations believe bias occurs only when a recruiter intentionally favours or rejects someone.
Artificial Intelligence can create a different kind of bias.
It learns from historical data.
If historical recruitment decisions contain hidden patterns, the AI may unknowingly repeat them.
For example, suppose an AI model learns that most successful employees in the organization graduated from a handful of well known institutions.
Without careful monitoring, it may begin giving lower preference to candidates from lesser known colleges even when they possess similar skills.
The same issue can arise with location.
An AI system may favour candidates living closer to a metropolitan office because it predicts lower commuting challenges.
Although this may appear logical from an operational perspective, it could unintentionally disadvantage applicants from smaller cities or rural areas.
Similarly, language models trained primarily on international English may incorrectly assess candidates who naturally use Indian English or regional expressions during interviews.
These situations demonstrate why AI recommendations should never be accepted without human review.
Technology should support recruitment decisions.
It should never replace professional judgement.
Human Oversight Remains Essential
One of the biggest misconceptions about Agentic AI is that it can completely replace recruiters.
In practice, the most successful organizations use AI to assist HR professionals rather than replace them.
AI can efficiently identify suitable resumes, automate interview scheduling and answer routine candidate questions.
However, final hiring decisions should continue to involve experienced recruiters and hiring managers.
Human judgement becomes especially important when assessing qualities such as integrity, cultural fit, leadership potential, communication style and ethical behaviour.
These qualities cannot always be measured accurately by algorithms.
A meaningful human review before releasing the final shortlist not only improves hiring quality but also reduces legal and reputational risk.
Disclaimer: For information only. The legal landscape is moving fast; always take professional legal and financial advice for specific compliance decisions.
By Mit - HR Professional
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