About

Prasanna (Sonny) Tambe is a faculty member involved in the Wharton Human-AI Research initiative, focusing on advancing human-centered artificial intelligence for business innovation. His work explores the design, impact, and governance of intelligent systems across organizations and society, emphasizing responsible and ethical AI implementation. Tambe's research includes examining how AI influences workplace transformation, the adoption of AI agents, and the development of frameworks for accountable AI deployment. He contributes to the understanding of AI's role in business solutions, policy, ethics, and governance, and is actively engaged in webinars, conferences, and industry reports that analyze AI's impact on industries, organizational models, and the economy. His efforts aim to bridge behavioral science and AI adoption, addressing barriers to trust and effective integration of AI agents in enterprise settings.

Research topics

• Computer Science
• Artificial Intelligence
• Business
• Knowledge management
• Economics
• Microeconomics
• Engineering
• Marketing
• Labour economics

Selected publications

• From Mainframes to Machine Learning: Skill Gaps over the Technology Life Cycle

  2026-01-01

  articleOpen accessSenior author
  PublisherDOI

• From Mainframes to Machine Learning: Skill Gaps over the Technology Life Cycle

  SSRN Electronic Journal · 2026-01-01

  preprintOpen accessSenior author
  PublisherDOI

• Navigating Political Shifts: Dobbs v. Jackson and Startup Applicant Behavior

  Academy of Management Proceedings · 2025-07-01

  article

  We demonstrate that changes in the local political environment impact startup applicant behavior. Using data from a leading job search platform for technology startups, we analyze application patterns before and after the Supreme Court’s ruling in Dobbs v. Jackson Women’s Health Organization in affected states. We find that following the ruling, the number of applications to jobs in trigger-law states (states where abortion became immediately illegal) dropped about 7% compared to states where abortion remained legal. The decline was most pronounced from applicants from protected states, and the decline occurred only for in-person jobs (remote jobs were unaffected). Finally, startups in trigger-law states had to offer 15% higher compensation to maintain application volumes. These findings indicate that while unexpected shifts in the local political environment may adversely impact startups’ talent attraction, flexible job designs that leverage remote work designs or offer wage premia may act in offsetting ways.

  PublisherDOI

• The Death of a Technical Skill

  Information Systems Research · 2025-03-19 · 3 citations

  articleSenior author

  For managers, we show that opportunities for skill development strongly influence matching in online information technology (IT) markets. Employers cannot easily circumvent labor scarcity by adopting older technologies, as workers avoid projects with declining future skill value absent substantial wage premiums. However, older workers, having shorter career horizons, are less sensitive to declining skill value, suggesting potential benefits in matching them with legacy technologies. For policy makers, our research demonstrates that labor market tightness persists across both new and old technologies in online IT markets. This challenges the notion that employers can engage in labor arbitrage by avoiding cutting-edge technologies. Policy frameworks therefore need flexibility to address skill shortages wherever they emerge. Additionally, our findings highlight the need for more granular data collection on technical skill evolution beyond broad occupational categories. Our online context provides unique insights into how corporate decisions about technology standards cascade into labor markets. The findings underscore the importance of policies promoting continuous learning and adaptability, while suggesting that age-diverse hiring practices could help address both skill shortages and age discrimination concerns in technical fields.

  PublisherDOI

• Unpacking How GenAI is Revolutionizing and Reshaping the Human Experience in Creative Work

  Academy of Management Proceedings · 2025-07-01

  articleSenior author

  In recent years, the rollout of generative artificial intelligence (GenAI) for public use has sparked intense debates on the use of this tool for creativity purposes (Amabile, 2020). While some creative professionals have welcomed the use of such tools by creating new categories in creative competitions (ADC Awards, 2024), others have actively resisted GenAI based on concerns of their intellectual property being violated (Akers, 2024; Andersen, 2022). In response to this, an increasing number of studies have examined the use of GenAI in organizational creativity (Berg, Raj, & Seamans, 2023; Doshi & Hauser, 2024; Jia, Luo, Fang, & Liao, 2024). However, as the use of GenAI becomes an inevitable part of the creative process, we argue that the key question is no longer how GenAI affects the creative output, but rather how using GenAI fundamentally changes the way individuals navigate creative work. This change in focus prompts the need to bring the human experience back into the relationship between GenAI and creativity, and explore the situational factors affecting the human experience. This symposium hence aims to showcase the current research on the individual and contextual factors affecting GenAI and creativity. This symposium embarks on an insightful journey through four distinct yet interconnected research streams, delving into different experiences of when and how individuals navigate their creative work when using GenAI. Employing a diverse array of quantitative and qualitative methodologies at multiple levels of analysis, these studies reveal the contingencies involved when incorporating GenAI for creative work, and also mark a paradigmatic shift in our theoretical understanding of creative work. Generative AI and the Reallocation of Creative Effort Author: Nelberto Nicholas Marcos Quinto; University College London Author: Sarah Harvey; Effects of initial AI use and competition outcome on subsequent reliance on AI Author: Velvetina Siu Ching Lim; Author: Yamon Min Ye; Author: Tianyu He; National University of Singapore Creative Markets in the Age of Generative AI: Strategic Shifts and Labor Market Health Author: Eric Zhou; Boston University Author: Dokyun Lee; Author: Gordon Burtch; Boston University Author: Daniel Rock; University of Pennsylvania Author: Prasanna Tambe; Monsters of Our Own Creation: AI, Occupational Cannibalization, and the Future of Work Author: Kevin Woojin Lee; The University of British Columbia

  PublisherDOI

• Reskilling the Workforce for AI: Domain Expertise and Algorithmic Literacy

  Management Science · 2025-09-30 · 7 citations

  article1st authorCorresponding

  This study provides evidence that AI and algorithms act as complements to domain expertise, creating the greatest value when algorithmic literacy is broadly diffused among workers. Unlike earlier business technologies that concentrated expertise in IT specialists, AI and algorithms are most effective when domain experts themselves can interpret and apply them. Using two workforce datasets, I show that demand for algorithmic skills is rising among domain experts, frontier firms diffuse these skills broadly, and markets reward firms’ AI and algorithmic investments more when such capabilities are dispersed. The spread of no-code and natural language tools accelerates this shift by lowering barriers to use and allowing domain experts to integrate algorithms into their decision-making processes. These patterns underscore the importance of workforce training and organizational design in realizing productivity gains from AI adoption. This paper was accepted by D. J. Wu, Special Issue on the Human-Algorithm Connection. Funding: The Wharton Mack Institute provided financial assistance. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2022.03968 .

  PublisherDOI

• Startup Jobs in a Polarized Era: How Dobbs v. Jackson Shifted the Geography of Remote and In-Person Applications

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• Out of Unstructured Data, Atlas! Mapping Strategic Landscapes with Generative AI

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• The New Digital Divide

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• A Brave New World of Human Resources Research: Navigating Perils and Identifying Grand Challenges of the GenAI Revolution

  Journal of Management · 2025-04-10 · 23 citations

  articleOpen access

  This paper reviews the transformative role of Generative Artificial Intelligence (GenAI) in Human Resource (HR) management, from a practice perspective, highlighting both opportunities and challenges and laying out a use-inspired future research agenda. This scoping review is grounded in insights from a unique Summit held in Spring 2024, which brought together HR academic scholars with dozens of Fortune 500 Chief Human Resource Officers (CHROs) and their top technical leaders to discuss the workforce implications of GenAI. The paper identifies six key themes from the Summit practitioners: GenAI as disruptive and transformative, data as competitive advantage, adoption challenges, potential ethical abuses, the experimentation imperative, and the critical role of CHROs. These six themes provide a foundation for future research directions, which are discussed regarding six functional HR areas: recruitment and selection, training and development, performance management, job and work design, talent management, and compensation and benefits. The research agenda in each area emphasizes the need for academic researchers to understand and address the practical challenges posed by GenAI. Overcoming these substantive challenges will demand meaningful effort and a keen willingness to learn, on the part of both HR leaders and scholars. The paper concludes with a call to action for management scholars to engage in use-inspired research that bridges the gap between academic knowledge and practical HR challenges.

  PublisherOA PDFDOI

Frequent coauthors

• Lorin M. Hitt

  University of Pennsylvania

  47 shared

• Erik Brynjolfsson

  National Bureau of Economic Research

  15 shared

• Peter Cappelli

  11 shared

• Dokyun Lee

  10 shared

• Valery Yakubovich

  California University of Pennsylvania

  8 shared

• Ashwini K. Agrawal

  6 shared

• Zhaoqi Cheng

  Boston University

  5 shared

• David H. Hsu

  University of Pennsylvania

  5 shared