Navigating the organizational AI journey: The AI transformation framework

Jonny Holmström and Johan Magnusson

Business Horizons, 2026, vol. 69, issue 1, 89-100

Abstract: This article introduces the AI transformation framework, a structured approach organizations can use to navigate the complexities of AI integration. AI transformations are reshaping industries, but organizations often struggle to realize value from their initiatives. The framework presents three dimensions critical to successful AI transformation: automation, augmentation, and data richness. Automation involves delegating routine tasks to AI systems, augmentation enhances human decision-making through AI, and data richness ensures AI systems are effective and accurate. By visualizing these dimensions as a cube, the framework helps organizations strategically position their efforts to maximize AI’s benefits. The AI transformation framework unfolds in three steps—path framing, path narrating, and path stretching—each addressing critical questions related to “what,” “when,” and “how” AI impacts the organization. Path framing helps executives define AI strategy, path narrating provides a temporal structure for implementation, and path stretching focuses on scaling AI efforts. The article offers practical recommendations for managing AI transformation, and by breaking down the AI transformation journey into manageable stages, organizations can better align their initiatives with their strategic goals.

Keywords: Artificial intelligence (AI); AI transformation; Automation; Data richness; Path framing; Integrated intelligence (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eee:bushor:v:69:y:2026:i:1:p:89-100

DOI: 10.1016/j.bushor.2025.01.002

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