Examining the Effect of a Firm’s AI Specialization on the Technology Firms it Acquires: A Real Options Perspective

Abstract

The digital revolution is transforming global business practices. As organizations increasingly embed artificial intelligence (AI) within their operations, they face unprecedented uncertainty regarding future technological trajectories and competitive landscapes. To maintain competitiveness in the emerging technological space, they need to promptly acquire advanced knowledge to enrich their technological portfolio. Drawing on real options theory (ROT), our study integrates AI-based acquisitions with internal AI development. We posit that a firm’s AI specialization represents the accumulation of critical technological knowledge and creates a portfolio of strategic options. These options can subsequently be exercised as AI acquisitions to secure complementary external capabilities. Moreover, the efficacy of these options is contingent on distinct uncertainties, including technical, modal, and complementarity uncertainties, captured by target R&D intensity, target self-fluidity, and product market overlap, respectively. Using a sample of US public firms that carried out acquisitions from 2004 to 2015, we find support for our hypotheses.