Prasanna Tambe

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

• Digital Capital and Superstar Firms

  National Bureau of Economic Research · 2020-12-01 · 138 citations

  reportOpen access1st authorCorresponding

  General purpose technologies like information technology typically require complementary firmspecific investments to create value. These complementary investments produce a form of capital, which is typically intangible and which we call digital capital. We create an extended firm-level panel on IT labor investments (1990-2016) using data from LinkedIn. We then apply Hall's Quantity Revelation Theorem to compute both prices and quantities of digital capital over recent decades. We find that 1) d…

  PublisherDOI

• Paying to Program? Engineering Brand and High-Tech Wages

  Management Science · 2020 · 41 citations

  1st authorCorresponding

  We test the hypothesis that information technology (IT) workers accept a compensating differential to work with emerging IT systems and that employers that invest in these systems can, in turn, capture greater value from the wages they pay. We show that much of the utility IT workers derive from these systems is from skills acquired on the job. This is principally true for younger workers at employers where skill development is encouraged, and the effects are stronger in thicker markets where wo…

  PublisherDOI

• InnoVAE: Generative AI for Understanding Patents and Innovation

  SSRN Electronic Journal · 2022 · 23 citations

  Senior authorCorresponding
  PublisherDOI

• Remote Work and Job Applicant Diversity: Evidence from Technology Startups

  Management Science · 2024-04-15 · 21 citations

  articleSenior author

  A significant element of managerial post-COVID job design regards remote work. In an era of renewed recognition of diversity, employers may wonder how diverse (gender and race) and experienced job applicants respond to remote job listings, especially for high-skilled technical and managerial positions. Prior work has shown that while remote work allows employee flexibility, it may limit career promotion prospects, so the net effect of designating a job as remote-eligible is not clear from an app…

  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 skil…

  PublisherDOI

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

Similar researchers at University of Pennsylvania

• Joseph E. Gyourkoh-72
• Itay Goldsteinh-65
• David Mustoh-31