Abstract

Big-tech firms such as Alphabet (Google), Amazon, Apple, Meta (Facebook), Microsoft, NVIDIA, and Tesla are leading the development and commercialization of artificial intelligence (AI) by leveraging their strategic partnerships to access data, talent, and technical resources. These partnerships enable AI innovation and market expansion among big-tech firms, accelerating their dominance. This paper shares the results of a systematic literature review (SLR) of 74 papers to examine the motivations, operational practices, and challenges of big-tech AI partnerships. The findings highlight three key insights: first, AI partnerships are primarily formed to acquire strategic resources, reduce costs, and enhance reputation; second, big-tech firms rely on existing networks and complementary strengths, raising concerns about governance frameworks and power imbalances; and, third, smaller firms face tensions related to dependency, data control, and ethical considerations, requiring careful negotiation and governance mechanisms. Highlighting the understanding of these partnerships using the AI tech-stack frameworks of big-tech firms, and analysing polarities such as dominance versus dependency, this paper advances theoretical perspectives on strategic partnerships in AI ecosystems. It also highlights practical implications for partner managers navigating the changing power dynamics in AI strategic partnerships. The paper concludes with research gaps, including the need for research on decision-making tools for practitioners. We hope these insights support practitioners and academics to better understand the evolving role of big-tech strategic partnerships in shaping their unique AI ecosystems.

This work is licensed under a Creative Commons Attribution 4.0 License.