ebook: AI Cost and Value Management:
A two-lens operating model to control AI spend and prove business value

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Reading Time: 2 minutes
In brief:

In this ebook, SHI introduces a practical framework for AI cost and value management based on two complementary perspectives: a financial lens and an enterprise lens. Together, these lenses help organizations move beyond measuring activity and begin evaluating what matters most: whether AI investments are financially defensible, strategically aligned, trusted, governed, and delivering meaningful business value. Below we share an introduction. Download the pdf to read the full ebook.

AI cost and value management: Why the conversation is changing

For the past two years, many organizations have focused on getting AI into the hands of employees as quickly as possible. Pilots have become production workloads. Individual use cases have expanded into enterprise-wide initiatives. What started as experimentation is increasingly becoming operational reality.

As adoption grows, so does scrutiny.

Technology leaders are under pressure to understand not only what AI can do, but what it costs to run, support, secure, and govern at scale. Finance teams want greater visibility into spending. Business leaders want evidence that AI investments are contributing to productivity, efficiency, customer outcomes, or growth. Boards want confidence that today’s investments will deliver long-term value.

The challenge is that many organizations are still measuring only part of the picture.

Token consumption, model usage, and infrastructure costs provide useful operational insights, but they don’t explain whether an AI initiative is delivering meaningful business outcomes. At the same time, measuring value without understanding the full cost of delivery can create an incomplete view of performance.

This ebook explores how organizations can bring those two perspectives together.

Inside, you’ll learn how to evaluate AI through both a financial lens and an enterprise lens, helping you understand the true cost of AI, connect investments to business outcomes, and make better decisions about where to optimize, scale, redesign, or retire initiatives. Along the way, you’ll discover practical approaches for improving visibility, accountability, governance, and decision-making across your AI portfolio.

Whether you’re responsible for technology strategy, AI governance, finance, operations, or executive decision-making, this guide provides a framework for moving beyond AI activity metrics and focusing on what matters most: delivering measurable business value.

Read the ebook below to learn how leading organizations are approaching AI cost and value management in a rapidly evolving landscape. Click the download icon to get a pdf version, for sharing with colleagues.

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