ARTICLE
12 December 2025

Evaluating AI Through The Outcome Index (OI): Turning Clarity Into Measurable Impact

Despite unprecedented investments in artificial intelligence, enterprise adoption remains limited. A recent MIT study found that less than 5% of AI deployments achieve sustained usage or measurable productivity gains.
United States Technology
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Despite unprecedented investments in artificial intelligence, enterprise adoption remains limited. A recent MIT study found that less than 5% of AI deployments achieve sustained usage or measurable productivity gains. The reasons are consistent across industries: integration challenges, ambiguous ROI measurement, and user experience barriers.1

At Alvarez & Marsal, we've developed a battle-tested framework that enables enterprises to evaluate, compare, and optimize their AI initiatives in a structured, evidence-based way: the Outcome Index (OI). This approach helps organizations balance innovation with governance, ensuring that AI programs deliver real value, aligned to business priorities, risk appetite, and organizational maturity.

The Outcome Index is an evaluative model that measures the effectiveness of AI programs across three dimensions of Clarity:

  1. Clarity in Goals
  2. Clarity in Data
  3. Clarity in Governance

The AI revolution will not be won by the most advanced models, but by the most disciplined operators. True success in AI lies in clarity - clarity of purpose, of data, and of accountability.

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Footnote

1 The GenAI Divide: State of AI in Business 2025, July 2025

Originally published 5 December 2025

The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.

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