How AI is Reinventing Recruitment—And Why Your Job Descriptions Need an Upgrade
AI's potential to accelerate hiring depends on better data quality and interactive evaluations, signaling a major shift from traditional resumes.
In this episode of Anyreach Roundtable, Richard Lin speaks with Janis Kreilis, founder of Hyperscan, about the transformative impact of AI on the recruitment industry. They discuss Janis's journey from recruitment to entrepreneurship, the challenges and opportunities presented by AI, and the importance of rethinking traditional recruitment processes. The conversation also touches on the human element in AI adoption, practical applications of AI in business, and the future of software integration with AI.
Key Takeaways
• Reshaping Recruitment Standards - AI tools are transforming recruitment by speeding up processes but require a fundamental rethink of how resumes and job descriptions are structured.
• Input Determines Output - The quality of AI outputs is directly tied to the quality of input data; poorly written job descriptions and resumes can lead to ineffective AI results.
• Interactive Candidate Assessment - AI can facilitate more interviews and better candidate evaluations, moving beyond traditional resume screening to more interactive assessments.
• Voice-Enabled Recruitment - The recruitment industry must adapt to AI's capabilities, including using voice agents for initial candidate interactions, to improve efficiency and candidate experience.
• Automated Hiring Agents - Future recruitment processes may involve fully automated AI agents that act on behalf of companies, fundamentally changing job roles and requirements.
Janis, is the founder of HyperScan, an AI-powered platform designed to enhance recruitment processes on LinkedIn. With a diverse background in recruitment, international diplomacy, and entrepreneurship, Janis brings a unique perspective on the intersection of AI and talent acquisition. His insights are grounded in practical experience and a vision for the future of recruitment.
Janis's Journey
Janis shares his diverse background, from Latvia to New York, and how his experiences led him to found HyperScan. "If I was the recruiter, I would not hire myself," he jokes about his varied resume. His journey includes work in the energy industry, international diplomacy, and now entrepreneurship in the talent space. He recognized inefficiencies in traditional recruitment and saw the potential of AI to improve the process.
AI Transforming Recruitment
Janis discusses the two sides of the recruitment marketplace: the demand and supply of labor. He notes the emergence of AI tools on both sides, from filtering resumes to automating applications. "We've taken an old process...and multiplied the speed of it using AI, but the process is kind of still the same," he observes. He believes AI will fundamentally change the recruitment process, moving beyond simply speeding up existing methods. "I think we'll have actual agents...evaluating and trying to make better matches in that market."
He likens the current market to a messy, high-friction system, and AI's role is to reduce that friction and improve matching. "What you want is maybe like five good job interviews, so that's the goal here."
"What you want is maybe like five good job interviews, so that's the goal here."
Challenges and Misconceptions
Janis highlights the issue of candidates gaming AI filters, such as using white font to hide keywords. He points out a common misconception: "AI is only as good as the data." Job descriptions are often too concise and lack context, while resumes are formatted for human, not AI, processing. He emphasizes the need to rethink the fundamental data sets used in AI recruitment.
Improving AI Effectiveness
Janis suggests that employers should consider using AI for tasks like initial screening calls, even for roles like car mechanics, where traditional resume screening is inefficient. "Why are we evaluating car mechanics on documents? We should just talk to each one of them." He acknowledges the concern about losing the human element but argues that AI can provide opportunities for candidates who might otherwise be overlooked.
He also discusses the potential of voice agents to improve information processing and the importance of focusing on quality over quantity in recruitment.
The Human Element and AI Adoption
Janis addresses the fear of AI replacing jobs. He notes that AI may exacerbate existing inequalities, potentially benefiting highly creative individuals more than those with less innovative capacity. He also predicts the loss of purely data-processing jobs in recruitment. He emphasizes the need for reskilling and adaptation in the face of these changes.
The discussion touches on how AI can augment human capabilities, freeing up time for relationship building and strategic thinking.
Market Sentiment and HyperScan's Experience
Janis shares HyperScan's experience in the market, noting that users are accustomed to software working flawlessly, so even a small margin of error can impact perception. He also discusses the challenge of managing user expectations regarding processing speed. He mentions the development of features to improve prompt quality and warn users about poorly constructed questions.
The Future of AI in Recruitment
Janis predicts significant changes in software development in the next 3-5 years, with AI potentially enabling the automated creation of software based on user specifications. This could disrupt traditional software businesses and lead to the development of highly customized recruitment tools. He envisions fully agentic AI acting on behalf of companies, significantly altering the recruitment landscape.
He also discusses the potential for AI agents to expand job capabilities beyond the status quo. "It doesn't just manage the status quo of how you're doing the job, sometimes it even expands your cap."
How to connect with Janis from Hyperscan
Keywords: AI, recruitment, talent acquisition, Hyperscan, Janis Kreilis, AI transformation, job market, technology, automation, human resources