Forging the Future of Work
AI-powered Analysts
We explore how brokerage firms’ investments in artificial intelligence (AI) affect their analysts’ information production. We find that analysts employed at brokerage firms with greater AI integration issue more accurate earnings forecasts. Cross-sectional analyses reveal that AI’s benefits are more pronounced for analysts with less firm-specific experience and when the firm’s disclosures are more readable. Further tests indicate that a key mechanism driving the improvement in forecast accuracy is that AI adoption helps mitigate the adverse effects of analyst decision fatigue and optimism bias. Finally, we find that forecast revisions made by AI-powered analysts are more informative to capital markets. Overall, our evidence points to the advantageous impact of AI on information production capabilities of financial analysts.
Michael Kimbrough, Musa Subasi, Yang Liu
Transforming Products into Platforms: Unearthing New Avenues for Business Innovation
NIM Marketing Intelligence Review, October 2024
It is impossible for brands to ignore digital platform opportunities. Network effects are one of the strongest sources of power and defensibility ever invented and underlie some of the most valuable businesses in the world. Managers and entrepreneurs can leverage the power of platforms by adding some platform elements to their existing products or services, by distributing their brands via existing platforms or by developing their own new platforms. By using one’s own brands as platforms requires creativity but can help businesses unlock new value and build resilient ecosystems around their products. There are three key methods. The first is to invite third-party sellers to enhance existing products. Examples include selling advertising space around products or creating app stores to extend offers. The second is to connect one’s customers by enabling interactions among users to add value. Third, brands might reach out to customers’ customers by enhancing the end-user experience in a way that benefits both themselves and their direct customers. If thoughtfully implemented, any platform strategy will create self-reinforcing feedback loops sparking growth and keeping competitors at bay.
Andrei Hagiu, Associate Professor of Information System, Boston University; Bobby Zhou, Associate Professor of Marketing, University of Maryland
How to Talk When a Machine Is Listening: Corporate Disclosure in the Age of AI
The Review of Financial Studies, March 2023
Growing AI readership (proxied for by machine downloads and ownership by AI-equipped investors) motivates firms to prepare filings friendlier to machine processing and to mitigate linguistic tones that are unfavorably perceived by algorithms. Loughran and McDonald (2011) and BERT available since 2018 serve as event studies supporting attribution of the decrease in the measured negative sentiment to increased machine readership. This relationship is stronger among firms with higher benefits to (e.g., external financing needs) or lower cost (e.g., litigation risk) of sentiment management. This is the first study exploring the feedback effect on corporate disclosure in response to technology.
Sean Cao, Associate Professor (with tenure), Robert H. Smith School of Business, University of Maryland, United States of America