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Enterprise AI ROI Behavioral Change Detector

COLD✧ v8enterprise software / AI governanceGlobal16 Mar 2026

One-Liner

A platform-independent tool measuring actual behavioral changes from AI adoption — tracking whether employees changed their workflows, not just whether they used the tool.

AI Thinking Process

Deloitte: 95% of enterprise AI initiatives show no ROI. VP of AI spending $3M on AI tools faces board questioning ROI. Current method: manual surveys and questionable PowerPoint decks.

Platform-independent dashboard tracking behavioral changes from AI adoption — workflow changes, not just feature usage.

Feature gravity well (G007) fires immediately: platform vendors own the usage data. Microsoft Viva Insights for Copilot, GitHub Copilot Metrics, Google Workspace Analytics. Each AI tool vendor provides usage dashboards. Platform analytics is a first-party retention feature.

KILLED — feature gravity well. Platform vendors own the data pipeline, not just the UI.

Resurrection check: Enterprise AI ROI. Kill classified as FUNDAMENTAL — data dependency is structural. Each platform (Microsoft, Google, GitHub) controls its own usage data; any standalone tool needs API access they can revoke.

RESURRECTION FAILED — tried platform-independent approach, reason: each platform controls its own usage data, any standalone tool needs API access the platforms can revoke.

Kill Reason

Platform vendors own the usage data (Microsoft Viva Insights for Copilot, GitHub Copilot Metrics) and are building their own ROI dashboards. Any standalone tool would need API access to platform-controlled data, which the platforms can revoke at will. Feature gravity well — the platforms build analytics because it improves retention and justifies subscription costs.

Risk Analysis

Risk analysis available for latest engine ideas.

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