From Alliances to Swarms: Rethinking Competition and Collaboration in the Age of AI

Established frameworks for inter-organizational strategy—alliance theory, ecosystem analysis, and platform economics—have been developed primarily for a world in which coordination between firms is deliberate, contract-governed, and mediated by human managers. The proliferation of agentic artificial intelligence is rendering these assumptions progressively inadequate. This paper argues that competition and collaboration in AI-enabled environments increasingly occur through what the authors term swarms: temporary, real-time configurations of agentic agents, data, capabilities, and protocols drawn from multiple firms and ecosystems that assemble to execute a specific interaction, compete and collaborate simultaneously, and dissolve upon its completion. Swarms represent a qualitatively new unit of inter-organizational strategy—distinct from alliances (which are durable relational structures) and from ecosystems (which are enduring participation environments)—and require a correspondingly new analytical framework. The authors propose a three-layer model in which capability bundle (the capability base defined by M&A and alliances), context (the ecosystem environment within which capabilities can interact), and dynamics (the swarms through which capabilities create and capture value in real time) operate as interdependent competitive layers. We further introduce the Swarm Stack, a six-layer architecture—capability, interface, agent, coordination, competition, and governance—that describes the infrastructure of swarm-based inter-organizational competition. The authors identify five sources of swarm advantage (selection, prediction, coordination, latency, and trust), examine the distinctive governance challenges that cross-organizational agentic interaction creates, and discuss implications for strategy theory and the reconceptualization of strategic leadership.