Wells Fargo Joins Stanford HAI Corporate Affiliate Program | Stanford HAI
Stanford
University
  • Stanford Home
  • Maps & Directions
  • Search Stanford
  • Emergency Info
  • Terms of Use
  • Privacy
  • Copyright
  • Trademarks
  • Non-Discrimination
  • Accessibility
© Stanford University.  Stanford, California 94305.
Skip to content
  • About

    • About
    • People
    • Get Involved with HAI
    • Support HAI
    • Subscribe to Email
  • Research

    • Research
    • Fellowship Programs
    • Grants
    • Student Affinity Groups
    • Centers & Labs
    • Research Publications
    • Research Partners
  • Education

    • Education
    • Executive and Professional Education
    • Government and Policymakers
    • K-12
    • Stanford Students
  • Policy

    • Policy
    • Policy Publications
    • Policymaker Education
    • Student Opportunities
  • AI Index

    • AI Index
    • AI Index Report
    • Global Vibrancy Tool
    • People
  • News
  • Events
  • Industry
  • Centers & Labs
Navigate
  • About
  • Events
  • AI Glossary
  • Careers
  • Search
Participate
  • Get Involved
  • Support HAI
  • Contact Us

Stay Up To Date

Get the latest news, advances in research, policy work, and education program updates from HAI in your inbox weekly.

Sign Up For Latest News

newsAnnouncement

Wells Fargo Joins Stanford HAI Corporate Affiliate Program

Date
April 04, 2023
Your browser does not support the video tag.

The Stanford Institute for Human-Centered Artificial Intelligence (HAI) is pleased to share that Wells Fargo has joined as the inaugural member of the Financial Services & AI Corporate Affiliate Program. 

The program is geared specifically to the financial sector, offering cutting-edge research and educational programming in areas including fintech, insurance, and banking, as well as visiting scholar opportunities.

As a founding member, Wells Fargo participated in a new Stanford HAI tailored professional education program, which engaged over 4,000 of the financial institution’s employees via an innovative webinar series. Wells Fargo will continue to learn from top-tier faculty about the ways AI is changing the industry.

“Stanford HAI’s mission focuses on how to properly design and build human-centered AI to have positive human impacts,” said James Landay, vice director and director of research for Stanford HAI. “This is particularly integral in the banking industry, where it affects everyone from bank employees whose jobs will be transformed, to customers whose businesses and personal finances will be impacted by advances in technology.”

“Generative AI is transforming the financial industry, enabling financial institutions to better serve their customers by generating more accurate predictions, automating complex processes, and identifying new opportunities for growth,” said Panos Madamopoulos-Moraris, Stanford HAI managing director of the partnerships and industry program. “We look forward to collaborating with Wells Fargo and our other corporate affiliates to explore the transformative potential of AI in the financial industry, and to help ensure its safe, responsible, and ethical use for the benefit of society as a whole."

“The future of banking will depend on collaboration and partnerships to create value for our customers across a variety of ecosystems,” said Chintan Mehta, Chief Information Officer and Head of Digital Technology & Innovation at Wells Fargo. “HAI continues to be a priority engagement for Wells Fargo’s innovation plans, specifically in the AI/ML space. Its cross-discipline approach and resulting access to deep subject matter expertise approaching the problems from different perspectives is an essential path to solve hard problems of explainability and bias for what will be an acceleratingly complex ecosystem of AI.”

Learn more about Stanford HAI corporate programs.

 

Share
Link copied to clipboard!

Related News

How AI is Transforming Scientific Discovery While Keeping Humans at the Center
Shana Lynch
May 27, 2026
News

From designing new antibodies to simulating 1,000 years of climate in a day, AI is transforming what's possible—but humans remain the ones deciding what matters.

News

How AI is Transforming Scientific Discovery While Keeping Humans at the Center

Shana Lynch
Sciences (Social, Health, Biological, Physical)Generative AIMay 27

From designing new antibodies to simulating 1,000 years of climate in a day, AI is transforming what's possible—but humans remain the ones deciding what matters.

AI Hiring Tools Can Yield Racial Bias and Systemic Rejection
Rishi Bommasani, Sarah H. Bana, Kathleen A. Creel, Dan Jurafsky, Percy Liang
May 26, 2026
News
A 3D isometric conceptual illustration showing a single glowing yellow human icon standing out among a grid of identical blue figures

The first large-scale study of hiring algorithms in the wild finds concerning patterns to how systems reject candidates.

News
A 3D isometric conceptual illustration showing a single glowing yellow human icon standing out among a grid of identical blue figures

AI Hiring Tools Can Yield Racial Bias and Systemic Rejection

Rishi Bommasani, Sarah H. Bana, Kathleen A. Creel, Dan Jurafsky, Percy Liang
Machine LearningEthics, Equity, InclusionWorkforce, LaborMay 26

The first large-scale study of hiring algorithms in the wild finds concerning patterns to how systems reject candidates.

New Approach to Scaling Laws Could Change How AI Models Are Trained
Andrew Myers
May 21, 2026
News
Digital image symbolizing neural nets

Leveraging statistical concepts from measurement science and education, AI researchers have greatly reduced the computational demand of predicting how the largest of large language models will scale up in the future. It could save millions of dollars in training costs.

News
Digital image symbolizing neural nets

New Approach to Scaling Laws Could Change How AI Models Are Trained

Andrew Myers
Natural Language ProcessingGenerative AIMay 21

Leveraging statistical concepts from measurement science and education, AI researchers have greatly reduced the computational demand of predicting how the largest of large language models will scale up in the future. It could save millions of dollars in training costs.