Steering the AI Race: An Exploratory Study of How Boardroom Dynamics Shape Competitive AI Actions and Performance

Artificial intelligence (AI) has become a pivotal engine of innovation and strategic transformation across industries. While firms are increasingly investing in AI to gain competitive advantage, many still struggle to translate these investments into meaningful performance outcomes. This study investigates how firms deploy AI through competitive actions—strategic moves such as AI-driven acquisitions, R&D projects, product innovations, and partnerships—and how these actions influence firm performance. We further explore the moderating and mediating roles of board governance, highlighting how variations in board structures shape the effectiveness of AI strategies. Grounded in the Attention-Based View (ABV) of the firm, we propose that the deployment and impact of AI are contingent on how strategic attention is allocated at the top. Board members influence this attention by shaping firm priorities and the governance environment in which AI actions are conceived and executed. To examine these dynamics, we pose three interrelated research questions: (1) How do competitive AI actions affect firm performance? (2) How do board governance characteristics—specifically board involvement in technology and power disparity—moderate this relationship? (3) Do board characteristics influence performance by shaping the breadth or scope of AI-driven competitive actions? We draw on a panel dataset of S&P 500 firms from 2010 to 2022, using detailed media reports and governance data. Our results reveal that firms engaging in more frequent and broader AI-driven competitive actions experience superior performance, especially when board members are actively involved in overseeing technological strategy. We find that board power disparity has a double-edged effect—enhancing market-based performance while dampening operational efficiency. Additionally, we show that board characteristics indirectly affect performance by influencing the scope of AI actions. Specifically, the presence of a CTO on the board and technical expertise among directors are associated with broader AI action portfolios, while board independence tends to constrain AI scope, likely due to increased scrutiny and risk aversion. This study contributes to strategic management and information systems literature by linking corporate governance to the execution and performance of AI strategies. It advances the ABV framework by demonstrating how boardroom dynamics shape the strategic attention paid to AI initiatives. From a practical perspective, our findings suggest that firms should not only invest in AI capabilities but also ensure that their governance structures are equipped to guide and support AI-driven transformation. Boards that actively engage with technology issues, balance power, and include members with technical expertise are more likely to convert AI initiatives into sustained performance gains.