As artificial intelligence (AI) increasingly plays a role in hiring processes, job seekers in Britain are confronting a new form of interview: AI chatbot assessments. Nearly half of candidates have already encountered AI-driven interviews, according to data from the recruitment platform Greenhouse. These interviews can range from answering emailed questions analyzed by AI to participating in full video interview sessions conducted by chatbot algorithms.
Experts involved in designing these AI systems highlight key strategies candidates should adopt to advance to human-led interviews. Unlike traditional interviews, AI assessments typically offer no opportunity for follow-up questions, meaning candidates must deliver concise and comprehensive answers on the first attempt. Victoria McLean, founder of Hanover Talent Solutions, advises applicants to prepare thoroughly and practice responses on camera, ensuring they maintain eye contact with the camera lens rather than looking at other parts of the screen.
While video presentation matters, McLean notes that factors such as poor lighting or eye contact will seldom cause a candidate to fail. Instead, relevance of experience is paramount. Barb Hyman, founder of Sapia—an AI system used to interview candidates—emphasizes that practical experience aligned with the job description outweighs enthusiasm or a positive attitude, traits that might have carried more weight in traditional interviews.
For example, Hyman points to a client like Joe And The Juice, where although the brand attracts many applicants, the role primarily involves cleaning tasks. Therefore, candidates’ answers should reflect relevant skills and experiences pertaining to those duties rather than broader aspirations.
Teamwork is a frequent topic in AI interviews. Candidates are encouraged to provide clear, structured accounts of specific contributions rather than general descriptions of team projects. McLean explains that a strong response should briefly outline the context but focus on the individual’s actions and the positive outcomes achieved. Such specificity helps the AI identify whether candidates meet predefined criteria.
Similarly, when addressing scenarios like managing difficult customers, successful answers highlight the candidate’s problem-solving approach, ownership of the issue, and the resolution’s impact—rather than dwelling on the customer’s behavior.
Experts caution against attempts to “game” AI interviews through rehearsed keyword stuffing, as this can lead to unnatural responses and may be easily detected during human review of the recordings. Likewise, relying on AI tools such as ChatGPT to generate written answers is discouraged. Many companies now use software to detect AI-generated content, which can flag applications for closer scrutiny.
Moreover, McLean warns that using generic AI-produced responses may hinder candidates by removing the personal details employers seek. She argues that submissions blending in with numerous similar applications are more likely to be rejected, regardless of their surface quality.
While AI interview questions tend to mirror those posed by human interviewers, these systems generally avoid unexpected or tricky inquiries. Hyman notes that the primary goal of AI chatbots is to objectively assess candidates based on the evidence provided rather than to “catch them out.”
As AI continues to reshape recruitment, mastering the nuances of these digital assessments is becoming essential for job seekers aiming to move beyond automated screening and secure interviews with human decision-makers.