AI was supposed to make hiring fairer, smarter, and more efficient. Instead, many organizations are discovering that automation has amplified noise, weakened trust, and obscured real performance signals. Richard Stein, CEO of talent intelligence advisor HSiQ – a Hunt Scanlon Company – examines why the next evolution of hiring will not come from more automation—but from talent intelligence that connects hiring decisions to real-world outcomes, leadership durability, and accountability.
In “AI Has Made Hiring Worse But It Can Still Help,” Tomas Chamorro-Premuzic in the Harvard Business Review delivers a long-overdue reality check. Despite years of hype around AI-powered recruiting, talent markets remain inefficient, trust has deteriorated, and hiring has become noisier and more dehumanized rather than more precise.
His diagnosis resonates deeply across boardrooms, search firms, and talent leaders globally. AI has unquestionably scaled speed and volume. What it has not scaled is judgment, accountability, or outcome quality.
Mr. Chamorro-Premuzic’s central insight is that AI has become an arms race of automation. Candidates now use generative AI to perfect résumés, fabricate achievements, and coach interview performance.
Employers, in turn, rely on algorithms to screen and rank applicants. The result is a mutual exhaustion loop – an ecosystem flooded with artificial polish, declining signal quality, and rising distrust.
The Signal Has Been Corrupted
“AI without outcome intelligence simply accelerates bad decisions,” says Richard Stein, CEO of HSiQ, the talent intelligence advisory unit of Hunt Scanlon. “The core failure isn’t technology; it is the absence of validated performance data, tenure outcomes, leadership impact metrics, and post-hire accountability. You can’t predict what you don’t measure.”
The HBR article makes the same point: most hiring AI is trained on shallow or biased proxies of who gets hired, who gets promoted, who looks impressive in interviews, but not on who actually performs, sustains impact, and builds enterprise value over time. Without rigorous outcome data, AI optimizes visibility rather than performance.
This is where talent intelligence not just talent technology becomes decisive.
From Automation to Accountability
Under Mr. Stein’s direction, the HSIQ intelligence platform integrates post-hire performance signals, leadership durability, role stability, mandate success, tenure patterns, and exit outcomes into the hiring and succession process.
Rather than automating résumé screening, HSIQ grounds hiring decisions in empirical evidence of what actually predicts success in real executive and leadership roles.
“AI without outcome intelligence simply accelerates bad decisions.”
At Hunt Scanlon, this intelligence layer is being operationalized into how leadership markets are interpreted and how boards, CEOs, and CHROs make decisions.
“The industry has confused automation with insight,” says Scott A. Scanlon, CEO of Hunt Scanlon and Co-Founder of HSiQ. “AI has made it easier to process candidates, but not to understand leadership risk, cultural fit, or long-term performance. What’s missing is a trusted intelligence layer that connects hiring decisions to real-world outcomes.”
Mr. Chamorro-Premuzic correctly argues that AI works best when it enforces structure, consistency, and discipline, reducing noise rather than pretending to add superior intelligence.
Used properly, it standardizes early screening, reduces interviewer drift, and frees humans to do what machines cannot: interpret context, assess motivation, exercise ethical judgment, and build trust.
The real future of hiring is not full automation. It is augmented accountability.
“AI has made it easier to process candidates, but not to understand leadership risk, cultural fit, or long-term performance.”
A better model looks less like replacing recruiters and more like combining structured AI, validated behavioral data, and outcome intelligence with experienced human judgment.
“This is exactly the architecture the HSIQ team is advancing,” says Mr. Stein. “A system where technology scales consistency, intelligence grounds decisions in evidence, and humans remain responsible for meaning, ethics, and final judgment.”
AI has not failed hiring. But hiring has failed to evolve beyond surface level automation.
The next phase will not be about faster screening. It will be about smarter, more accountable leadership decisions built on real data, real outcomes, and real intelligence.
HSiQ Insights Lab was created to examine exactly this intersection – where data, technology, and human potential converge. As the workforce contracts, advantage will not come from doing more with less. It will come from seeing more of what already exists – and using it intelligently.
For more information on how HSiQ can help your business succeed, please contact us today.
Article By
Richard Stein
Richard Stein is CEO of HSIQ. He has a distinguished career supporting the C-suite of many of the world’s top corporations and financial services organizations in all aspects of talent acquisition, development and retention. Richard is one of the industry’s top advisors with experience across the Americas, Europe and Asia Pacific.
