How AI can help or hurt fair hiring, and how McQuaig supports smarter, more human people decisions.
When it comes to bias, does AI help or hurt? The answer isn’t a simple yes or no. AI can either magnify existing biases or help organizations make more consistent, evidence-based decisions. The difference lies in how the technology is designed, what it measures, and how it’s used alongside human judgment. What matters most is whether AI is applied with clear role expectations, transparency, and accountability. Used thoughtfully, it can support fairer decisions, but it should never replace the people responsible for making them.
Bias has always been part of people decisions. Humans rely on experience, intuition, and mental shortcuts, especially when making decisions under pressure. These tendencies are natural, but they can lead to inconsistency and decisions that are difficult to explain or defend.
What has changed is awareness. In a 2024 global HR survey, 75% of HR leaders identified bias as a top concern when evaluating AI tools, second only to data privacy. That concern reflects a growing expectation that technology should help improve fairness, not complicate it.
AI doesn’t remove bias by default. When trained on historical data without context or safeguards, it can reflect the same patterns organizations are trying to move away from. The goal, then, isn’t to remove humans from decisions, but to support them with better structure and clearer insight.
When grounded in sound behavioral science, AI can help reduce bias by introducing consistency where subjectivity often dominates.
Research published in 2024 comparing AI-supported hiring decisions with human-only decisions found that audited AI models produced more consistent and fair outcomes across demographic groups in many hiring scenarios. In some cases, female candidates experienced up to 39% fairer outcomes and racial minority candidates up to 45% fairer outcomes when structured, AI-supported criteria were used.
These findings don’t suggest that AI is “better than people.” They highlight the value of clearly defined, job-related criteria applied consistently, something humans often struggle to maintain at scale.
Read more: Strike A Balance Between Tech And Human Insight
Best practice is to use AI to support recruiter and HR judgment, not to narrow the field too early or screen out strong candidates.
This starts with being clear about the role. When expectations are defined upfront, AI can help assess candidates against the job instead of assumptions or past hiring habits. Without that clarity, even well-meaning tools can overlook capable people whose strengths don’t show up in typical ways.
It also means avoiding AI as an early pass-fail filter. Automatically screening candidates by resumes, credentials, or keywords increases the risk of missing strong talent, especially those with nontraditional or transferable experience. Used more thoughtfully, AI can help organize information and highlight areas to explore, while leaving decisions to people.
Transparency matters as well. Recruiters and hiring managers should understand why AI is surfacing certain insights. Clear, job-related criteria support better conversations and more consistent decisions.
Candidate expectations are shifting too. In a 2024 study, 49% of job seekers said AI could help reduce bias in hiring when it’s used responsibly.
Reducing bias begins by being clear about what a role actually requires.
The McQuaig Job Survey helps organizations define the behavioral demands of a role before evaluating candidates or employees, rather than relying on assumptions or legacy job descriptions. This clarity matters because bias often enters when expectations are vague. Anchoring decisions to shared, role-specific criteria helps reduce reliance on familiarity, similarity, or subjective “fit.”
Once the role is clear, the next step is understanding how an individual is likely to respond to those demands. The McQuaig Word Survey provides insight into a person’s natural behavioral tendencies, including:
The Word Survey does not label people or assign value judgments. Instead, it offers context that supports more balanced conversations about fit, onboarding, and development. By focusing on behavior rather than background or style, organizations can reduce bias while reinforcing that growth is always possible.
McQuaig Maven, our newest AI-powered tool uses the technology to support human judgment, not replace it.
By combining insights from the Job Survey and Word Survey, McQuaig Maven helps HR teams and hiring managers focus on what matters most: alignment between role demands and behavioral tendencies. Maven translates complex behavioral data into clear, role-relevant guidance which supports structured interviews, more objective comparisons, and constructive development conversations.
Rather than adding complexity, Maven helps ensure insights are applied consistently and thoughtfully, while keeping people firmly in control of the decision-making.
As of 2025, approximately 67% of organizations use some form of AI in recruitment. The differentiator isn’t whether AI is used, it’s whether it supports clarity, consistency, and human-centered decision-making.
Read More: How can you trust AI powered decisions?
Bias doesn’t end once a hiring decision is made. It can surface in performance feedback, promotion discussions, and leadership development.
Behavioral insight supported by AI helps organizations:
When conversations are grounded in shared expectations and observable behavior, they tend to feel more constructive, and less subjective.
AI shouldn't be a risk to fair hiring and development. Used thoughtfully, it helps organizations make people decisions that are more consistent, transparent, and human.
McQuaig’s approach, combining the Job Survey, the Word Survey, and over 50 years of behavioral science, helps organizations reduce bias by focusing on what truly matters: how people are likely to perform and grow in specific roles.
Interested in learning more about using technology in hiring? Then join our upcoming webinar on AI in HR this February 26th. Click below to learn more!
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