Comparative Study of Competitive M&A Strategies within the Generative AI Platform Ecosystem

This study demonstrates that companies’ Mergers & Acquisitions (M&A) activities in a rapidly evolving generative artificial intelligence (GenAI) platform ecosystem are not merely transactions but dynamic competitive response strategies. In particular, to overcome the shortcomings of existing M&A theory, an AMC framework was applied that analyzes companies’ competitive behavior into three pillars: awareness, motivation, and capability. Through this, M&A cases of four companies representing GenAI, including OpenAI, Google, Perplexity, and Microsoft, were classified into four types: internalization of technological resources, diversification of products and services, expansion of core capabilities, and strengthening of market power and analyzed in-depth. As a result of the analysis, it was confirmed that the type and outcome of M&A strategies are determined by how each company perceives competitive stimuli, converts them into specific objectives, and executes them based on what criteria. This study reinterprets M&A as a dynamic process that has a macroscopic impact on ecosystem competition, and shows that the AMC framework is a key tool to understand a company’s strategic choices in the entire context. It also expands the existing theory by revealing that M&A is a platform’s private regulatory means and a key mechanism to absorb talent and tacit knowledge. As a result, M&A provides management with practical implications that it should be pre-checked and planned through a framework of awareness-motivation-capability, not just financial transactions.