Abstract
With the growing significance of artificial intelligence (AI), the examination of a compa-
ny's overall strategic alignment towards the development and use of AI, referred to as AI
orientation, has captured increased attention in the literature. However, the impact of
technology-focused TMT roles on such strategic alignment in U.S. companies remains
ambiguous. Building on Upper Echelons Theory, this study investigates the influence of
chief information officers (CIOs) and chief technology officers (CTOs) on firms' AI ori-
entation by analyzing question-and-answer sections from earnings conference calls.
Based on the premise that IT and AI investments are strongly interdependent within firms,
this study also explores the moderating effect of industry IT intensity. Using a panel da-
taset comprising 3,811 firm-year observations of U.S. S&P 500 companies from 2012 to
2020, the results confirm a positive effect of CTO presence on AI orientation. Unexpect-
edly, no significant effect of CIO presence or a moderating effect of industry IT intensity
on the relationship between CIO, CTO and AI was identified. These findings not only
highlight the strategic importance of the CTO role in U.S. companies but also underscore
differences between CIO and CTO roles. This study contributes to the literature by ex-
ploring the distinct impacts of specific TMT roles on AI orientation in U.S. firms and
identifying relevant areas for future research, such as a deeper analysis of the differences
between IT and AI in companies and the role of AI literacy within the TMT.
Keywords: AI Orientation, Chief Technology Officer, Chief Information Officer, Indus-
try IT Intensity, Top Management Team, Upper Echelons Theory
Table of Contents
1 Introduction
2 Theory and Hypothesis
2.1 Artificial Intelligence
2.1.1 Overview AI
2.1.2 AI in the Corporate Environment
2.1.3 AI Orientation & Top Management Skills
2.2 The Upper Echelons
2.2.1 Upper Echelons Theory
2.2.2 Who is Who?
2.2.3 CIO versus CTO
2.3 CIO, CTO and AI Orientation
2.4 External Environment and IT intensity
3 Methods
3.1 Data and Sample Overview
3.2 Measures
3.2.1 Dependent Variable
3.2.2 Independent Variables
3.2.3 Moderator Variable
3.2.4 Controls
3.3 Empirical Approach
4 Results
4.1 Descriptive Statistics
4.2 Regression Results
4.3 Robustness Checks
4.3.1 Alternative Operationalizations of Explanatory Variables
4.3.2 Alternative Analytic Approach
4.3.3 Alternative AI Orientation
4.3.4 Endogeneity
5 Discussion
5.1 Summary and Interpretation of the Results
5.2 Theoretical Contributions
5.3 Managerial Implications
5.4 Limitations and Avenues for Future Research
6 Conclusion
Objectives & Core Themes
This master's thesis examines the influence of specific top management team (TMT) roles—specifically Chief Information Officers (CIOs) and Chief Technology Officers (CTOs)—on a firm's strategic orientation toward artificial intelligence (AI). By applying the Upper Echelons Theory, the research investigates whether the presence of these roles facilitates AI adoption, explores the moderating role of industry-wide IT intensity, and clarifies the functional distinctions between these two executive positions in U.S. S&P 500 companies.
- Strategic AI orientation and organizational alignment.
- Distinctive impacts of CIO and CTO roles within the TMT.
- Moderating effects of industry IT intensity on AI adoption.
- Application of text-mining techniques for firm-level strategic measurement.
- Upper Echelons Theory in the context of emerging technological innovations.
Excerpt from the Book
2.1.2 AI in the Corporate Environment
Brown et al. (2024) provided various examples of how companies are integrating (generative) AI into their organizations. Zalando, for instance, employes a chatbot based on OpenAI’s ChatGPT technology to enhance customer satisfaction on its e-commerce platform. DHL utilizes AI to ensure automated processes in its logistics operations, continuously monitoring them and accelerating defect detection. And Coca-Cola even created an AI-generated flavor (Y3000). This brief selection just demonstrates the immense potential that AI offers to companies across various industries and underscores its distinction from traditional IT (Li et al., 2021a). However, implementing AI entails inherent risks, significant costs, and substantial effort for all stakeholders, with no guaranteed outcomes (Haenlein & Kaplan, 2021; Mishra et al., 2022). To leverage the unique potentials of AI and prevent detrimental failures, companies must address several aspects to facilitate the optimal development and effective use of AI technology (Chatterjee, Rana, Dwivedi, & Baabdullah, 2021; Kinkel et al., 2022; Li et al., 2021a; Zeng et al., 2024).
Following Enholm et al. (2022, p. 1716), firms must first establish “enablers” and consider external factors (“inhibitors”) to enable AI’s effective development within the organization. These include technological and organizational factors, which will be covered in further detail below, as well as regulatory constraints and ethical questions (ibid.). Second, firms must decide on the application of AI. This decision typically involves a distinction between automation, which replaces human tasks with machines (substitutional role), and augmentation, where humans and machines collaborate to solve tasks (supportive role) (Davenport et al., 2020; Raisch & Krakowski, 2021). For years, businesses have employed AI solutions to automate routine tasks (“state of the art AI”) (Davenport et al., 2020, p. 27). Recent advancements in computing power, novel methods for machine learning, and exponential data growth now allow firms to leverage AI tools for management-related tasks (Brynjolfsson & Mcafee, 2017; Raisch & Krakowski, 2021). For instance, AI can provide managers with better insights and predictions, thereby supporting the decision-making (Brynjolfsson & Mcafee, 2017; Keding, 2021). However, the choice between automation and augmentation should not be viewed as a trade-off (Raisch & Krakowski, 2021).
Summary of Chapters
1 Introduction: Introduces the transformative potential of artificial intelligence and defines the research gap regarding the impact of specific TMT roles on a firm's AI orientation.
2 Theory and Hypothesis: Discusses the theoretical foundations based on Upper Echelons Theory and defines the roles of CIOs and CTOs, leading to the formulation of specific hypotheses.
3 Methods: Details the empirical research design, including data collection from S&P 500 earnings conference calls, text-mining procedures, and the GEE modeling approach.
4 Results: Presents the findings from the regression analyses and various robustness checks conducted to validate the empirical model.
5 Discussion: Interprets the empirical findings, compares them with prior literature, and provides managerial implications along with limitations.
6 Conclusion: Synthesizes the main conclusions of the research, highlighting the importance of the CTO role in driving AI orientation.
Keywords
AI Orientation, Chief Technology Officer, Chief Information Officer, Industry IT Intensity, Top Management Team, Upper Echelons Theory, Artificial Intelligence, Digital Strategy, Text Mining, Earnings Conference Calls, Strategic Management, Organizational Performance, Technology Management, Information Technology, Innovation.
Frequently Asked Questions
What is the core focus of this research?
This thesis explores how the presence of Chief Information Officers (CIOs) and Chief Technology Officers (CTOs) within the Top Management Team influences a company's strategic alignment toward artificial intelligence (AI orientation).
What are the central topics addressed?
The research covers the distinction between CIO and CTO roles, the application of Upper Echelons Theory, the impact of industrial IT intensity, and methods for measuring organizational AI orientation through text mining.
What is the primary research goal?
The primary goal is to determine whether CIO or CTO roles are more effective in fostering an AI-oriented corporate strategy and to identify the differences in impact between these two executive functions.
Which scientific methodology is applied?
The study uses a longitudinal panel data approach with 3,811 observations from S&P 500 firms (2012–2020). It employs computer-aided text analysis (CATA) to calculate AI scores and uses Generalized Estimating Equations (GEE) to test hypotheses.
What does the main body of the work cover?
The main part encompasses a review of AI in corporate environments, theoretical frameworks on TMT roles, the detailed measurement methodology for AI orientation, empirical results, and a critical discussion of the findings.
Which keywords best characterize this work?
Core keywords include AI Orientation, Chief Technology Officer, Chief Information Officer, Upper Echelons Theory, TMT, and Industry IT Intensity.
Why was the CTO found to have a stronger impact than the CIO?
The study suggests that CTOs, being typically more focused on R&D, innovation, and product development, align better with the exploratory and transformative nature of AI compared to CIOs, who are often focused on traditional administrative IT efficiency.
Did industry-wide IT intensity significantly moderate the AI orientation?
No, the empirical findings did not provide statistically significant evidence that industry-wide IT intensity moderates the relationship between TMT roles and firm-level AI orientation.
- Arbeit zitieren
- Maximilian Fröhlich (Autor:in), 2025, Only an IT Thing? Leading the AI Agenda: The Role of CIOs versus CTOs in Shaping AI Orientation, München, GRIN Verlag, https://www.grin.com/document/1691838
