Competing in the Age of Algorithmic Intermediation: A Dynamic Capabilities Framework for Algorithmic Readiness (Working Paper)

Abstract

As autonomous AI agents increasingly intermediate commercial transactions, organizations confront a fundamental strategic challenge: competing when algorithms, not humans, evaluate and select suppliers. We develop the construct of algorithmic readinessorganizational capacity to compete effectively in AI agent-mediated markets-grounded in dynamic capabilities theory. Through expert interviews with platform strategists and procurement executives, we identify distinctive capability requirements that extend beyond digital maturity. We theorize algorithmic readiness through sensing (detecting when algorithmic evaluation criteria diverge from human preferences), seizing (managing the transparency-protection paradox in data provision), and transforming (operating dual-mode systems for human and algorithmic audiences). We develop testable propositions linking algorithmic readiness to competitive outcomes, specify boundary conditions, and provide preliminary empirical validation. This research addresses critical gaps in understanding organizational adaptation when the nature of the "customer" fundamentally changes.

Rights Notice: © 2025, 2026 Paul F. Accornero. All rights reserved. Academic citation, quotation, and non-commercial scholarly use of this work are freely permitted with appropriate attribution. Commercial use — including incorporation into consulting deliverables, training programmes, client presentations, or commercial advisory services — requires a written licence. All proprietary frameworks, terminology, and methodologies referenced herein are subject to the Intellectual Property Terms of The AI Praxis™ (www.theaipraxis.com/legal-and-ip).

Keywords: Algorithmic Readiness, Artificial Intelligence Agents, Dynamic Capabilities, Digital Transformation, B2b Marketing, Platform Strategy, Agentic Commerce, AI Agents, The AI Praxis

JEL Classification: M10, L86, M15, M31, O33, D83