Workforce & Skill Development

How Neuroscience and AI Could Reshape Leadership Pipelines

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For decades, leadership identification has relied on personality inventories, interviews, and performance history. These tools are valuable, but they often capture who people are, not how they think and adapt under pressure. New research from Elizabeth “Zab” Johnson (Executive Director) and Michael Platt (Faculty Director) of the Wharton Neuroscience Initiative (WiN), Korn Ferry, and Lazul.ai, shows how neuroscience-informed, AI-enabled assessments can add a powerful new layer to leadership pipelines, especially at early career stages.…Read More

Gen AI in the Enterprise: From Hype to Human Capital

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Generative AI has rapidly shifted from experimentation to everyday utility in large enterprises. In the final installment of our Fall 2025 AI Horizons webinar series, Wharton Human-AI Research Faculty Co-Directors Stefano Puntoni and Prasanna (Sonny) Tambe joined Jeremy Korst, Partner at GBK Collective, to share findings from the 2025 AI Adoption Report: GenAI Fast-Tracks into the Enterprise. Here are the key takeaways from their talk.…Read More

Reskilling the Workforce for AI: Why Domain Experts Need Algorithmic Skills

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AI is no longer just the territory of engineers and data scientists. Increasingly, the most valuable use cases happen when business professionals – marketers, healthcare workers, financial analysts, and managers – use AI tools themselves. That’s the central message of new research by Prasanna “Sonny” Tambe, professor at Wharton and Faculty Co-Director of Wharton Human-AI Research. His paper in Management Science, Reskilling the Workforce for AI: Domain Expertise and Algorithmic Literacy, shows that firms capture more value from AI when algorithmic expertise is distributed across domain experts rather than concentrated in IT departments.…Read More

The Complexities of Auditing Large Language Models: Lessons from Hiring Experiments

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As AI becomes a fixture in hiring, evaluation, and policy decisions, a new study funded by the Wharton AI & Analytics Initiative offers a rigorous look at a critical question: Do race and gender shape how Large Language Models (LLMs) evaluate people? If so, how can we tell? The answer is, according to Prasanna “Sonny” Tambe, Faculty Co-Director of Wharton Human AI Research, and others, is complex, and the implications matter for every organization deploying LLMs at scale. Here are the key takeaways you need to know from Tambe’s latest research on LLM bias and auditability.…Read More