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This chapter focuses on maximizing the return on investment (ROI) of ServiceNow’s AI capabilities and avoiding common value traps. It provides IT managers with a structured approach to defining, measuring, and realizing ROI, covering financial, operational, and strategic outcomes. Through practical frameworks, real-world case studies, and actionable strategies, it explains how to track KPIs, improve data quality, drive adoption, and align AI initiatives with business goals. Additionally, it highlights common pitfalls, such as misaligned expectations, poor change management, and inadequate data governance, and offers proven techniques to overcome them. By the end of this chapter, IT leaders will be equipped to transform AI-driven ITSM into a sustainable source of measurable value.

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Maximizing ROI with ServiceNow AI Capabilities and Avoiding Value Traps

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  • 发表日期：

    2025年

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  • Saaniya Chugh

摘要

This chapter focuses on maximizing the return on investment (ROI) of ServiceNow’s AI capabilities and avoiding common value traps. It provides IT managers with a structured approach to defining, measuring, and realizing ROI, covering financial, operational, and strategic outcomes. Through practical frameworks, real-world case studies, and actionable strategies, it explains how to track KPIs, improve data quality, drive adoption, and align AI initiatives with business goals. Additionally, it highlights common pitfalls, such as misaligned expectations, poor change management, and inadequate data governance, and offers proven techniques to overcome them. By the end of this chapter, IT leaders will be equipped to transform AI-driven ITSM into a sustainable source of measurable value.