Create Generative AI Value at Scale

2026-06-02 · Source: MIT Sloan Management Review · Field: Business & Management — Corporate Strategy & Leadership, Operations & Process Management, Artificial Intelligence & Machine Learning · Depth: Intermediate, short

Summary

Companies are achieving scaled value from generative AI by implementing a new internal organizational structure called the "AI spine." This cross-functional framework facilitates rapid development of innovative GenAI use cases, fostering idea and expertise sharing across business units. The AI spine helps organizations overcome the challenge of translating billions of dollars invested in general-purpose LLMs for personal productivity into strategic, scalable applications with measurable ROI. Research, based on interviews with 87 practitioners in 23 large organizations, identifies three key practices for success: expanding use cases across processes, treating each use case as a work in progress, and quickly abandoning those that fail to deliver value. This approach moves beyond traditional hub-and-spoke models, providing a flexible core for managing a dynamic GenAI portfolio.

Key takeaway

For Directors of AI/ML aiming to scale generative AI beyond individual productivity, your current organizational structure likely impedes strategic GenAI adoption. Consider implementing an "AI spine" model to foster cross-functional collaboration and disciplined governance. This structure enables you to expand use cases across processes, continuously improve solutions, and quickly abandon low-value projects, ensuring your GenAI investments yield measurable, enterprise-wide value.

Key insights

The "AI spine" is a cross-functional organizational model enabling scalable, strategic generative AI value creation.

Principles

• Expand GenAI use cases across processes.
• Continuously improve GenAI use cases.
• Abandon GenAI use cases lacking measurable value.

Method

The AI spine provides a flexible core structure for implementing, evolving, and abandoning LLM use cases at scale, keeping the GenAI portfolio focused and current.

In practice

• Prioritize process-wide GenAI applications.
• Establish continuous improvement loops for GenAI.
• Implement rapid value assessment for GenAI projects.

Topics

• Generative AI
• AI Strategy
• Organizational Design
• Business Process Innovation
• Large Language Models
• Value Creation

Best for: CTO, Executive, Director of AI/ML, VP of Engineering/Data, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by MIT Sloan Management Review.