'Theorizing AI Adoption in Established Firms: An Empirical-Based, LLM-Augmented Approach', a seminar by Professor Pinar Ozcan (Oxford)

Theorizing AI Adoption in Established Firms: An Empirical-Based, LLM-Augmented Approach

by Professor Pinar Ozcan (Saïd Business School, University of Oxford)

Abstract

Established firms increasingly seek to expand (i.e., scale) their adoption of artificial intelligence (AI). Yet most firms struggle to transition from early ad-hoc experimentation to sustained value. Existing research often treats AI adoption as a discrete decision or as shaped by isolated factors, thus limiting insight into how adoption unfolds over time. Existing research is also limited by the lack of successful empirical examples of AI adoption beyond a few early projects. Using a novel hybrid research method, we extend prior research by combining configurational and processual perspectives to theorize how established firms effectively engage in AI adoption over time. First, we conduct a qualitative analysis of extensive data from original interviews within established firms and secondary sources to identify four critical organizational attributes of AI adoption. These attributes ground our theorization in rich empirical data. Second, we use a novel, AI-augmented theory-building method to theorize a developmental pathway of three successive configurations that are comprised of these attributes. Specifically, as data and technology architectures mature, effective AI adoption configurations progress from 1) controlled experimentation to 2) programmatic scaling of efficiency-oriented use cases and exploratory probes of broader AI applications to 3) transformative scaling of federated, quality-focused AI initiatives. Thus, effective AI adoption emerges from successive coherent configurations, not from single attributes or simple best practices. Overall, we contribute to theory a configurational process framework for effective AI adoption over time within established firms, and an emphasis on the temporality of a sequence of configurations. Our novel hybrid research method that follows empirical, qualitative insights with AI-augmented conceptual theory development exemplifies how to use human-AI collaboration to support abductive theorizing when empirical evidence is limited.

About the speaker

Pinar Ozcan is Professor of Entrepreneurship and Innovation. She is also the academic director of the Oxford Entrepreneurship Centre and the Oxford Future of Finance and Technology (Fintech) Initiative. A globally recognised expert in fintech, strategy, AI governance, and digital transformation, Pinar advises governments, regulators, and boards on innovation strategy in fast-moving, highly regulated sectors.

Her current work focuses on AI-enabled business models, digital platform and ecosystems, the role of technology in financial inclusion, and the evolving role of Big Tech in regulated industries. She brings 20+ years of strategic insight working with organisations ranging from Silicon Valley startups to European regulators and global financial institutions. She has served as advisor to bodies including the UK’s Competition and Markets Authority (CMA), Financial Conduct Authority (FCA), European Commission, OECD, and the Bank of England on fintech, data, and AI regulation.

Pinar holds a PhD in Management Science and Engineering from Stanford University, where she also earned her master’s and dual bachelor’s degrees. Her academic work has received multiple international awards and is widely cited in management, technology, and policy circles. Since completing her PhD, Pinar had the honour to be selected to the Top 40 Business School Professors under 40 by Poets and Quants. She was also selected to the global Thinkers 50 list for emerging thinkers with the potential to make lasting contributions to management theory and practice in 2018.

In 2021, Pinar was chosen to the Global Women in Fintech Powerlist by Innovate Finance. In 2023, Pinar was selected to the Advisory Committee of the OECD Digital for SMEs Global Initiative (D4SME), which aims to help SMEs seize the benefits of digitalisation. In 2024, she was selected as an Academic Advisor to the Bank of England Digital Pound Initiative, and in 2025, she started her role as member of the World Economic Forum Global Council on Financial Education.