Imagine a job interview where your chances don’t depend on first impressions, the interviewer’s mood, or a slick resume—but on the skills you actually have.
Unstructured interviews have been the tradition for decades despite being as reliable as “flipping a coin” in predicting job success, said Belen Garcia, the behavioral science lead at LizzyAI. Garcia spoke alongside Yannis Niebelschuetz, the founder & CEO of LizzyAI during a From Day One webinar.
It can be difficult, or near impossible, to screen thousands of candidates and give each one the same level of rigor and empathy in the process. While traditional thinking favors unstructured interviews to reveal personality and passion, decades of research suggest a different approach.
“Most interviews don’t work,” Garcia said, citing data that shows 46% of new hires fail within 18 months and that 80% of turnover stems from hiring mistakes. “It’s not a people issue; it is a process issue,” she said. Outcomes inevitably vary when every hiring manager asks different questions, evaluates based on gut instinct, and brings unconscious bias to the interview room.
What organizations need is structure: a standardized set of job‑relevant questions, consistent scoring rubrics, and an evidence‑based framework that ties every answer directly to role requirements, says Garcia.
Harnessing Artificial Intelligence (AI) for Equity
AI, as presented during the webinar, is not a harbinger of a dystopic future where humans in the workforce are replaced with artificial intelligence. LizzyAI’s product, Lizzy, a fully autonomous AI recruiter, is designed to streamline the hiring process.
“Lizzy isn’t making hiring decisions,” Niebelschuetz said. “She provides data so you can make better decisions.” By coding a behavioral-interview model into an autonomous platform, Lizzy delivers identical prompts to each applicant, whether she’s screening entry-level store associates or senior analysts, and then tracks their responses against competencies drawn directly from the job description.
Around 30% of recruiters have already experimented with AI, while others expressed concern that it might exclude unconventional talent. Niebelschuetz called that concern valid. However, by focusing exclusively on concrete examples of past performance, “what happened, how you did it, why you chose that approach, and what happened afterward,” Lizzy eliminates bias tied to tone, appearance, or affinity. Every follow‑up question digs deeper into context and judgment without veering into impersonal, robotic territory.
Niebelschuetz gave a live demo, acting as a retail‑associate candidate. On screen, Lizzy greeted him in a friendly tone, outlined the role’s expectations, and invited him to share detailed stories about customer service and task prioritization. When Niebelschuetz pressed to know if past leadership experience counted for anything, the AI seamlessly adjusted: “Your sales‑management tenure at LinkedIn can provide valuable insights into customer focus and dynamic environments.”
As the demo unfolded, Garcia pointed out how Lizzy timestamps each response, maps strengths and gaps to technical and behavioral criteria, and compiles an evidence‑rich transcript. She auto-generates a scorecard that highlights must-haves, such as scheduling availability, competency scores with narrative rationales, and a recommendation after each interview.
From Evidence to Decisions
“It’s not about the number, it’s about the reasoning behind it,” said Garcia. Instead of guessing whether a candidate seemed confident, hiring managers can review verbatim snippets. The system even flags nonnegotiables, such as the ability to lift heavy merchandise or work weekend shifts, so overlooked disqualifiers don’t slip through human cracks.
By the end of the hour, three key themes had emerged. First, structure breeds validity. The rigor behind question design and scoring has a much stronger impact on predictive power than factors like interview length or the seniority of the role. Second, AI enhances rather than replaces. Recruiters still make the final decisions on whom to advance, while AI helps by filtering out noise, standardizing evaluations, and surfacing relevant evidence. Third, transparency builds trust. Providing full transcripts and cited examples makes feedback more explainable, which is essential for a positive candidate experience and for maintaining legal compliance.
Looking ahead, Niebelschuetz and Garcia envision a world where every organization, large or small, has an AI-powered first-round interview process that screens for core competencies, eliminates bias, and reserves human interaction for higher-order conversations. “This isn’t automation for its own sake,” Niebelschuetz said. “It’s a redefinition of what interviews could, and should, be.”
Editor’s note: From Day One thanks our partner, LizzyAI, for sponsoring this webinar.
Ade Akin specializes in the emerging applications of artificial intelligence.
(Photo by Alexander Sikov/iStock)
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