Date of Award

8-22-2025

Date Published

9-18-2025

Degree Type

Dissertation

Degree Name

Doctor of Professional Studies

Department

Information Science & Technology

Advisor(s)

John Jordan

Keywords

advertising technology;artificial intelligence;Google;innovation theory;Meta;technological revolutions

Abstract

This study explores the future of advertising amidst a digital landscape increasingly shaped by artificial intelligence (AI). Leveraging Carlota Perez’s Technological Revolutions and Financial Capital framework, it examines how AI is poised to further disrupt the advertising ecosystem through the key elements of automation, user data, and inventory. Collectively, these dynamics have become key drivers of platform power, with implications for user behavior, competitive strategy, and the societal diffusion of AI technology more broadly. Employing a thematic analysis across historical and contemporary cases of advertising technology, the research identifies five themes worthy of strategic and scholarly consideration. Two primary themes—Dependency and Differentiation, alongside sub-themes of Concentration, Resilience, and Transparency/Openness—illustrate advertisers’ and publishers’ increasing reliance on the differentiated capabilities of a small set of dominant platforms, reinforcing market concentration and challenging platform resilience in the face of regulatory, technological, and competitive friction. This study makes three contributions to innovation theory and techno-economic paradigm scholarship. First, it extends Perez’s framework by showing how financial and production capital increasingly converge within dominant platforms, rather than being deployed by disparate parties across distinct phases. Second, it further develops the Technological Revolutions and Financial Capital framework by positioning elements of modern production capital as self-optimizing and appreciating in value, rather than depreciating or depleting over time like the physical assets of prior eras. Third, it advances Zuboff’s concept of behavioral surplus by reframing user data not as excess extraction but as an operational necessity in AI-powered contexts. Collectively, these contributions offer a framework for understanding AI-era platform power with societal implications well beyond advertising. By leveraging historical and contemporary events to establish plausible trajectories—including agentic advertising, decentralized data ecosystems, and physical-world data capture—this research highlights both the enduring dominance of major platforms and the strategic options available to other stakeholders, calling for informed, collaborative, and proactive engagement from academics, industry professionals, policymakers, and users to shape AI’s future across industries.

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Open Access

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