Summary

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In this episode of Recruiting Future, host Matt Alder speaks with Diana Tsai, co-founder and CEO of Upwage. Upwage builds AI interviewing agents proven to reduce turnover by as much as 48%. Diana discusses her book, "AI for Good: How AI Can Transform Hiring for Good," which presents a positive vision for the future of recruiting where AI enhances, rather than replaces, human connection. They delve into this optimistic future, discussing a roadmap to 2035 involving three waves of AI transformation in recruiting. The conversation explores how AI is changing the role of recruiters, the data needed to build effective AI agents, and how to mitigate bias in AI hiring. Ultimately, the vision is one where AI takes on automatable tasks, freeing up recruiters to focus on deeper relationship building and strategic insights.

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What you'll learn

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• How AI can transform recruiting for good, creating a more human process.
• A positive vision and roadmap for AI in hiring leading up to 2035.
• The three distinct waves of AI transformation expected in recruiting.
• The evolving role of the recruiter and the concept of the "AI-empowered recruiter".
• What data inputs are crucial for building effective and robust AI interviewing agents.
• Strategies for employers to reduce bias in hiring when deploying and building AI.
• Diana Sai's perspective on the balance between AI and human recruiters in the future.
• Key signals that indicate progress through the different stages of AI transformation in recruiting.

Key Takeaways

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• The future of recruiting, according to Diana Sai, can be optimistic and focused on leveraging AI for good rather than fearing job displacement.
• The transformation is envisioned in three waves: the transformation of recruiting tasks (already happening, expected mainstream by 2026/2027), the emergence of AI managers for coordinating agents (expected 2028/2029 or sooner), and the transformation of the labor market through universal interviewers (expected 2030+).
• AI adoption leads to significant business growth advantages through faster hiring, better hires, and lower turnover, making it economically compelling for businesses to adopt.
• The role of the recruiter is shifting from manual tasks (screening, scheduling) to becoming AI-empowered, focusing more on relationship building with candidates and hiring managers, and deeper insights. They become decision-makers supported by a team of AI agents.
• Building effective AI interviewers requires more than just resumes and job descriptions; it benefits greatly from rich data like company values, performance reviews, and previous interview guides.
• Mitigating bias in AI hiring requires going beyond current regulations, considering product design (like redacting PII), and being mindful of how factors like interview scheduling times and video format can inherently exclude certain candidates.
• The ultimate human advantage in recruiting lies in relationships, nuance, and the "last 20%" of the process that AI handles less effectively. This includes providing white-glove service, deep engagement with internal talent, and understanding team-specific dynamics.
• Transformation progress can be measured by the adoption and proliferation of AI agents ("bees"), which is a prerequisite for the emergence of coordinating AI managers ("queen bees") and ultimately, the universal interviewer.

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In this episode we cover:

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• Introducing Diana Sai and Upwage's work (approximate timestamp: 1:00) - Diana introduces herself as co-founder and CEO of Upwage, which builds AI agents to decrease turnover, increase performance, and extend recruiting teams.
• The vision behind the book "AI for Good" (approximate timestamp: 2:30) - Diana discusses the motivation for writing the book, which is to paint an optimistic vision and roadmap for leveraging AI in hiring for good, combating potential negative impacts.
• The three waves of AI transformation in recruiting (approximate timestamp: 4:30) - Explanation of the three waves: transforming recruiting tasks (Wave 1, by 2026/2027), emergence of AI managers (Wave 2, 2028/2029+), and transforming the labor market with universal interviewers (Wave 3, 2030+).
• Why the predicted time scales were chosen (approximate timestamp: 4:45) - The time scales emerged from future thinking discussions based on inputs from deploying thousands of AI agents and talking to TA leaders.
• Transformation of recruiting tasks (Wave 1) (approximate timestamp: 5:15) - Focus on AI-driven interviews and top-of-funnel proliferation driven by economics and ROI, leading to faster hiring and business growth for adopters. This wave also means the transformation of the recruiter role.
• Emergence of AI managers (Wave 2) (approximate timestamp: 7:15) - Driven by the need to manage large numbers of deployed AI agents, coordinate information exchange between them, and unlock deeper insights for strategic decision-making.
• Transformation of the labor market (Wave 3) (approximate timestamp: 9:00) - The vision of a universal interviewer powered by underlying job interviewing agents, replacing traditional applications and helping job seekers find the right opportunities faster, creating a safety net against layoffs.
• Skills and competencies for TA leaders and recruiters (approximate timestamp: 12:00) - Insights from TA leaders on equipping teams for the fierce new reality of AI adoption, meeting increased candidate expectations, and freeing recruiters from manual tasks.
• The role of the AI-empowered recruiter (approximate timestamp: 13:30) - Recruiters leveraging AI agents to handle initial tasks, gaining bandwidth to deepen relationships with candidates and hiring managers, shifting from defense to offense mode.
• Data requirements for future AI agents (approximate timestamp: 17:45) - Discussing the need for robust data inputs beyond resumes and job descriptions, such as company mission, values, interview guides, and even performance reviews, to build effective AI interviewers. Introduction of Upwage's AI builder agent that aggregates this context.
• Reducing bias in AI hiring (approximate timestamp: 21:45) - Strategies include exceeding current regulations, scrutinizing product design (like PII redaction), considering accessibility factors (interview scheduling), and being mindful of how interface choices (like video vs. chat) can introduce bias.
• The balance between AI and humans in recruiting (approximate timestamp: 26:00) - AI handles automatable tasks (the "first 80%"), opening up space for humans to focus on relationships, white-glove service, engaging internal talent, understanding nuance, and deeper strategic work (the "last 20%").
• Signals of transformation progress (approximate timestamp: 30:45) - Key indicators are the widespread adoption of foundational AI agents ("bees"), which is a prerequisite for the emergence of management-level AIs ("queen bees") and the universal interviewer. This adoption creates network effects.

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