Abstract

The use of AI in enterprise systems, known as enterprise AI, has grown significantly recently. However, many organisations struggle to operationalise AI, resulting in cost overruns and challenges in demonstrating ROI. Furthermore, the inappropriate application of AI to tasks for which it is ill-suited can have unintended consequences, potentially undermining or diminishing value. The root cause is AI’s unique characteristics (e.g., opacity and autonomy) that make its value creation process distinct from traditional IT systems. In this paper, we analyse five successful case studies from various industries and sizes to develop a process model of how organisations can create and capture value from enterprise AI. We identify two types of AI use: internal use (e.g., improving operational efficiency) and external use (e.g., enhancing customer experience). This distinction helps contextualise the triggers. Moreover, our study identifies six episodes, both at the project and enterprise levels, as processes leading to value capture.

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