Paper Number
ICIS2025-1360
Paper Type
Complete
Abstract
Even though the transformative potential of Artificial Intelligence (AI) for business operations and strategy is widely acknowledged, our understanding of which types of AI create value for companies remains limited. This study examines the relationship between different types of AI and their value over time. Using natural language processing and multivariate regression analysis on a comprehensive dataset of 461,207 AI patents, we demonstrate that value effects vary across the different types of AI and change over time. AI patents categorized as mechanical showed positive value associations in early years that reversed after 2019, whereas intuitive AI patents exhibited positive value associations throughout the observation period, with increasing effect magnitudes after 2019. This research contributes to existing literature by offering a nuanced view of AIs’ impact and practical implications for strategic AI usage and innovation in organizations.
Recommended Citation
Santos Gabriel, Victoria Sofia; Müller, Lukas; and Drechsler, Katharina, "Is AI Worth the Hype? The Divergent Link between AI Types and Value" (2025). ICIS 2025 Proceedings. 4.
https://aisel.aisnet.org/icis2025/digitstrategy/digitstrategy/4
Is AI Worth the Hype? The Divergent Link between AI Types and Value
Even though the transformative potential of Artificial Intelligence (AI) for business operations and strategy is widely acknowledged, our understanding of which types of AI create value for companies remains limited. This study examines the relationship between different types of AI and their value over time. Using natural language processing and multivariate regression analysis on a comprehensive dataset of 461,207 AI patents, we demonstrate that value effects vary across the different types of AI and change over time. AI patents categorized as mechanical showed positive value associations in early years that reversed after 2019, whereas intuitive AI patents exhibited positive value associations throughout the observation period, with increasing effect magnitudes after 2019. This research contributes to existing literature by offering a nuanced view of AIs’ impact and practical implications for strategic AI usage and innovation in organizations.
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