AI and Transformative Tech

A groundbreaking course at Columbia Business School equips future leaders with a framework to address technology's most pressing ethical challenges.

New Columbia Business School research challenges assumptions about AI art's impact: Rather than diminishing human creativity, the presence of AI-generated art can actually enhance the perceived value of human-made work.

Your Google search for “climate change” may show emotional images — or calm, scientific visuals — depending on where you are. A new CBS study reveals how search algorithms shape climate perceptions worldwide.

In this episode, Morris joins CBS Professor Stephan Meier to discuss how Walmart is building a resilient, tech-powered, and people-led workplace.

Statistical bias could be misleading your product and feature testing, according to research from Columbia Business School Professor Hannah Li, but solutions might be easier than you think.

Award-winning research from Professor Laura Doval tackles the “limited commitment” problem in economics, offering a model that helps governments and firms adjust rules and strategies based on new information over time.

Generative AI is revolutionizing market research by offering unprecedented ways to understand customers, assess competitors, and extend data-driven decision-making organizationally. Research with pioneering companies reveals four key opportunities: gen AI supports existing practices by making them faster and more scalable; replaces traditional methods with synthetic data that can match conventional results with greater accuracy; fills insight gaps by providing evidence for decisions previously based on intuition; and creates innovative applications like digital twins for testing customer interactions. Survey data shows 45% of market researchers already use gen AI, with most employing it to analyze transcripts and data. While acknowledging limitations around bias and representativeness, this framework helps business leaders navigate gen AI's transformative potential in gathering customer and market insights more efficiently and effectively than ever before.

New Columbia Business School research reveals how analyzing real-time customer journey data — from search queries to filtering behavior — can predict preferences with remarkable accuracy, even without historical data.

In new research, Professors Dante Donati and Hortense Fong find that the brief TikTok outage in January benefited Meta as advertisers turned to its platforms to reach users. Small businesses, less able to switch, lost out.

Columbia Business School researchers discover that the amount of variety in a consumer’s past purchases predicts their openness to algorithm-based recommendations.