Working Paper
How do capital markets value the integration of artificial intelligence and advanced analytics (AIAA) into traditional industries? Grounded in the “financialized” dynamic capabilities construct, the authors develop and test an empirical framework for evaluating AIAA deals, analyzing stock market reactions to 397 announcements by biopharmaceutical (biopharma) firms between 2001 and 2020. Their central finding is that observable firm characteristics predict economically substantial variation in returns, a 3.5 percentage point “value spread” between firms positioned to capture value and those for whom identical investments destroy wealth. While average announcement returns are modest (0.58%), this mean masks economically substantial heterogeneity.
Deal attributes matter with markets assigning premiums to discovery-focused deals (+1.3%) and multi- indication platforms (+1.1%), rewarding investments that expand opportunity sets over those optimizing current operations. More consequentially for understanding market reactions, organizational readiness (proxied by R&D intensity and asset turnover) dramatically moderates returns. High-readiness biopharma firms achieve +2.6% returns on discovery-focused deals while low-readiness firms experience -0.9% returns on identical deal types. This spread reflects that operational excellence could become a liability when pursuing discovery-focused AIAA investments. Finally, exploratory temporal analysis suggests markets learn to price integration friction over time, exhibiting a “Valuation J-Curve.” Their findings highlight the nuanced relationship between AIAA deals and market valuation. Moreover, their framework demonstrates that dynamic capabilities, traditionally considered unobservable, function as priced assets whose valuation can be understood through publicly available data.
Faculty
Associate Professor of Technology and Operations Management
