Document Type

Dissertation

Degree

Doctor of Business Administration

Major

Business Administration

Date of Defense

11-7-2025

Graduate Advisor

Joseph Rottman

Committee

Michael Seals

John Merit

Abstract

The field of AI has undergone significant evolution over the past few decades. While AI is heralded as one of the most transformative technologies, scholars caution that its strategic impact may still not be fully realized. Given the strategic importance of AI in today's firms, it is essential to consider AI as a strategic orientation and understand its determinants in detail. Our study examines AI Orientation, defined as a firm's deliberate application of AI technologies to achieve its strategic objectives. Drawing on multiple theoretical perspectives, this study investigates the determinants that shape a firm’s AI orientation. This study employs a qualitative research approach based on 20 semi-structured interviews with senior AI leaders across various industries. This study makes three interrelated contributions. First, it presents a revised theoretical model of AI Orientation by integrating RBV, UET, ABC, TOC, and LOC, refining six determinants (leadership influence, AI capability, enterprise alignment, AI scalability, AI governance and organizational learning orientation) and documenting sub-themes to illustrate how organizations can apply AI towards its strategic goals. Second, it demonstrates a hybrid methodological approach by combining traditional manual coding in Quirkos with AI-assisted analysis through QualiGPT, illustrating how human–AI collaboration can enhance triangulation and analytical depth. Finally, the study provides a practical framework for leaders seeking to strengthen AI Orientation, especially in organizations where AI adoption remains fragmented or disconnected from strategic priorities.

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