Human Bias or AI Bias in Hiring: Which Is Worse? | Deepali Jain

Deepali Jain is not a cheerleader for AI in hiring but something more useful: a talent acquisition professional with 15 years of experience who is genuinely uncertain about one of the most important questions in the field: whether human bias or AI bias does more damage in a hiring process. That conflict is named openly, which is rarer than it should be.

Her background spans three continents, four major consulting firms, and a range of organizations from global enterprises to family businesses. Today she sits on the Harvard Business Review Advisory Council and coaches leaders on navigating the intersection of technology and human judgment.

In this episode #25 of Xobin Talks, host Aman Kumar Tiwari asks her the questions HR functions are wrestling with in private: what does smart hiring actually mean, how do you manage AI bias you cannot fully see, and what does the next five years of talent acquisition look like.

What Does Smart Hiring Really Look Like in Today's Workplace?

Deepali's answer is immediate and does not start with a tool.

Deepali: "Our approach can completely change the outcome. Technology and tools will keep evolving, but we need to evolve with them. We have to be willing to look at things differently and change the way we work and respond."

AI as Time Liberation, Not Job Replacement

Her framing of smart hiring is specific: use AI to recover time, then spend that time on work that requires human presence.

Deepali: "Spend less time on this task and more time building real connections with candidates. I'd rather spend that time building relationships, listening to my clients and team, understanding what they need, and helping solve their problems. AI can support us, but I still think it has a long way to go before it can truly match the human side of those interactions."

AI adoption among HR professionals rose from 58% in 2024 to 72% in 2025 (SQ Magazine), and 93% of recruiters plan to increase AI use in 2026. That adoption curve is steep, but Deepali's point is that adoption without intention produces efficiency without improvement. The real question is how we should use AI, where it adds value, and what we need to protect.

Is AI Bias Better or Worse Than Human Bias in Hiring?

This is the question at the centre of the episode, and Deepali's answer is the most honest one in the series.

Deepali: "For me, it feels like a personal conflict, and honestly, I'm still figuring out the answer. We like to believe that we make hiring decisions objectively, but in reality, that's rarely the case. Bias can enter the process at almost every stage, when we write the job description, search for candidates, screen applications, conduct interviews, and even when we make the final decision."

Human Bias Has Always Been There

One starting premise matters above all: hiring has always been biased. Bias in a JD reflects whoever wrote it, screening bias reflects whoever designed the process, and interview bias reflects the interviewer's own frameworks. None of this is new.

Deepali: "Human bias is already difficult to manage. AI can sometimes make the problem worse. As more companies start using AI tools for hiring, we also need to look at how those tools were built and trained. The data and instructions behind an AI system can influence the job descriptions it creates and introduce hidden bias. You may see the same bias when the tool reviews resumes, finds candidates, or runs interviews."

Over 75% of HR leaders now rank demographic bias as a top concern when adopting new AI talent acquisition tools (TechRT). Only 26% of candidates trust AI to evaluate them fairly, according to Greenhouse's 2026 survey of nearly 3,000 job seekers across five countries (Greenhouse, 2026).

The Transparency Problem

Deepali names the core governance issue: most organizations cannot actually see how their AI hiring tools work, which makes managing their bias nearly impossible.

Deepali: "I don't think these tools show us clearly how they actually work. We don't really know how they're trained or whether they carry any bias. So, I tend to assume that AI can have its own biases too. And that's where things get complicated. Is human bias worse than AI bias, or is AI bias actually better? I honestly don't know."

Amazon's AI hiring tool exhibited gender bias due to historical hiring patterns, and the "black box" nature of many algorithms makes it difficult for candidates and HR professionals to understand or challenge decisions. Deepali's intellectual honesty here reflects a field-wide challenge that has not yet been resolved.

How Can HR Teams Use AI Hiring Tools Fairly?

Given that AI bias exists on a continuum and transparency is incomplete, Deepali offers two concrete directions.

Ask the Hard Questions of Your Vendor

Deepali: "Look for clear answers from the provider about what data the tool collects, how it uses that data, and what happens to it. What data has the tool been trained on? How does the tool actually work? Those are the first filters. Now, despite that, the answer might be that it's not bias free. It's probably on a continuum. But at least knowing whether a particular tool is 80% biased or 20% biased, there's a huge difference in that."

Approximately 67% of organizations have now embedded fairness audits and bias risk scoring into their AI development pipelines, and nearly three-quarters of Fortune 500 companies use multi-stakeholder AI governance boards including legal, technical, and ethics teams (TechRT). The infrastructure for accountability is building, but asking for transparency from vendors remains an essential individual step that many HR teams skip.

Use Both, But Not Uniformly

Deepali: "We're still learning whether humans or AI make fairer choices. Using both can help you make more balanced choices. But it's not one-size-fits-all. For some roles you could have minimal or no intervention, perhaps. For some you could have a largely greater human intervention compared to AI, even if you're using a tool. You have to pick and choose, and see in what way you will apply that tool and where human interaction comes in."

Her framework distinguishes between role type, business impact, and organizational culture, and the same AI tool should not be applied identically to a VP of Engineering hire and a batch of customer support roles. The consequences of a wrong hire differ by role, as does the data available and the human judgment required.

Which Skills Will HR Leaders Need to Succeed in the Future?

Deepali acknowledges the well-documented WEF research on future skills: communication, creativity, adaptability, but steers toward the more specific challenge she sees in HR.

Deepali: "HR teams should use AI to simplify daily tasks and make their work more efficient. Rather than worrying that AI will take people's jobs, we should look at how it can help teams work smarter and get more done. Give your employees the right skills and confidence to use AI. When people know how to work with it, they're more likely to see AI as a helpful tool, not something to be afraid of."

The Walk-the-Talk Requirement

Her advice to HR leaders is direct: model the behavior you are asking from your teams.

Deepali: "Do it yourself. Walk the talk. Get your team members to embrace it. Utilizing the time created because of using AI tools, utilizing it for what HR does best, is about building those relationships, listening to your stakeholders, understanding the context of problems and challenges, and solving it in a more collaborative and human way."

A 2025 Resume.org survey found roughly a third of US companies believe AI will likely run their entire hiring process by the end of 2026, rising to 62% among the subset already planning to expand their AI use (Resume.org, 2025). Even if the number changes, one thing is clear. AI now handles many of the routine and administrative tasks that HR teams used to manage. What remains is the relationship, judgment, and strategic work, which is exactly where Deepali argues human investment should concentrate.

How Will Talent Acquisition Change as Companies Hire Over the Next Five Years?

Deepali walks through the logical extreme before stepping back from it.

Deepali: "AI can take care of up to 80% of the tasks recruiters handle throughout the hiring process. Your team can use it to write job descriptions, review applicants, shortlist qualified candidates, and conduct interviews. Technically you could have zero touch, perhaps, if you really want to be creative and imaginative. Now is zero touch the answer or the right answer? I don't think so. At least personally I don't think that's the answer."

The Strengths Framework

Her alternative is not nostalgic. It is structural: understand what AI does well and what humans do well, then build a process that uses each at its strongest.

Deepali: "We help people understand what they do best and find roles where they can put those strengths to work. AI works the same way. We identify what AI does better and let it handle those parts of the process. Then, we bring human judgment and experience into the areas where people add the most value. Together, they make the process stronger by letting people and AI work side by side rather than replacing one another."

The practical implication is a process design question: map the hiring funnel stage by stage, identify where AI adds reliable signals and where human judgment is irreplaceable, then build the workflow accordingly, iteratively as both AI capability and organizational understanding improve.

One Piece of Advice for Organizations Starting Their Smart Hiring Journey?

Deepali: "Don't hesitate and start using AI today."

The advice is unambiguous and the gap is already compounding. Bias and transparency risks are real, but the organizations that engage with AI in hiring, even imperfectly, are building the judgment to use it better over time. Those standing on the outside are not.

About Deepali Jain

Deepali Jain is an HBR Advisory Council Member at Harvard Business Review, an ICF ACC certified coach, and a startup mentor with 15 years of experience in management consulting focused on human capital.

She has worked at PwC, Deloitte, Accenture, and IBM across three continents and more than ten countries, advising enterprises, SMEs, and family businesses on HR technology, talent, leadership, culture, and organizational transformation. Her final consulting tenure was five years with the Deco Group, where she held roles spanning Chief of Staff, P&L Leader, and Head of Transformation Office.

She approaches AI in HR not as an advocate or a skeptic but as someone who has spent fifteen years watching the field make assumptions about objectivity that the data consistently contradicts.

Connect with Deepali on LinkedIn