HiPeople’s AI Interviews are built on well-established structured interviewing principles from industrial-organizational psychology. The process is designed to assess job-relevant competencies in a consistent, transparent, and evidence-based way.

Structured interviews are among the most effective and reliable methods for evaluating job-relevant competencies. Unlike unstructured interviews, where questions and evaluation criteria may vary from candidate to candidate, structured interviews create a consistent process that allows candidates to be assessed against the same standards. This consistency helps reduce variability in interviewer judgments and increase the likelihood that hiring decisions are based on relevant evidence rather than subjective impressions.

HiPeople’s AI Interviews are designed around these same principles. Every candidate receives a comparable interview experience, and responses are evaluated against predefined criteria that are established before the interview begins.

The interview itself and the evaluation of candidate responses are completely separate processes.

During the interview, the AI recruiter asks candidates a series of structured, job-relevant questions. Its role is to gather information only. It does not score responses, make hiring decisions, or reveal evaluation criteria during the conversation.

To ensure a fair and consistent experience, interviews follow structured interviewing best practices, including asking one question at a time, avoiding leading questions, and using only brief clarifying follow-ups when needed. Questions can also be personalized based on a candidate’s resume to make the discussion more relevant to their background.

Once the interview is complete, responses are evaluated separately against predefined competencies selected by the hiring team.

Each competency is assessed using Behaviorally Anchored Rating Scales (BARS), a widely used methodology in industrial-organizational psychology that improves consistency and transparency in evaluations.

Competencies are not evaluated using generic or universal definitions. Instead, they are configured for the specific role and organization. Hiring teams identify the knowledge, skills, experiences, and behaviors that are genuinely relevant to success in the position. These requirements are then translated into observable evidence that can be identified within interview responses. This role-specific approach helps ensure that candidates are assessed on factors that are directly connected to job performance rather than abstract or unrelated characteristics.

Each competency is translated into concrete evidence that candidates should demonstrate in their responses, such as:

A common challenge in interviewing is that different evaluators may interpret the same answer differently. Behaviorally Anchored Rating Scales (BARS) help address this challenge by defining in advance what different levels of evidence look like.

For each competency, the evaluation framework specifies what would constitute strong, medium, weak, or absent evidence. It then asks whether the candidate demonstrated the specific behaviors and evidence associated with the competency. This makes evaluations more transparent, easier to review, and more consistent across candidates.

Past experiences and demonstrated behaviors are often more informative than general statements about strengths, personality, or self-perceptions. For this reason, HiPeople’s interviews are designed to encourage candidates to provide concrete examples of how they have approached situations relevant to the role. The evaluation process focuses on the evidence contained within those examples rather than on broad impressions of the candidate.

For example, if a role requires stakeholder management, the evaluation does not simply assess whether a candidate claims to be a strong communicator. Instead, it looks for evidence of specific actions, decisions, challenges, and outcomes that demonstrate the competency in practice.

A key principle of our approach is that every score should be explainable.

Each competency rating is accompanied by supporting evidence from the interview transcript and a rationale describing why the evidence aligns with a particular rating level. This allows recruiters and hiring teams to understand how conclusions were reached and independently review the underlying evidence.

While AI is used to conduct the conversation and evaluate responses against predefined criteria, the underlying methodology follows established structured interviewing principles. The AI does not create evaluation criteria on the fly or make judgments based on intuition. Instead, it applies the same competency definitions and behavioral anchors to every candidate, helping ensure evaluations remain consistent, transparent, and tied to job-relevant evidence.

The goal is not to replace human judgment, but to provide a structured, evidence-based framework that supports more consistent decision-making. Users always have the ability to override the AI’s decision and adjust the candidate’s match level.

To maintain fairness and focus on job-relevant information, HiPeople’s AI Interviews do not evaluate:

Evaluations are based solely on the content of a candidate’s responses.

The quality of the evaluation depends on the quality and relevance of the competencies selected for the role. To support this, HiPeople includes compliance and quality checks to help ensure that interview criteria remain job-related, appropriate, and aligned with hiring best practices.