---
id: "framework-value-driven-ai-deployment"
type: "framework"
source_timestamps: ["§ 3. Align AI investments with business priorities."]
tags: ["strategic-alignment", "use-case-selection"]
related: ["action-align-ai-with-business", "contrarian-business-first-ai"]
steps: ["\\\"Identify primary business goals (e.g.", "resilience", "supporting revenue growth targets).\\\"", "Analyze processes to determine which ones most need AI to achieve those specific goals.", "\\\"Develop focused use cases (e.g.", "Lenovo's ~10 specific use cases) tailored to those processes.\\\""]
sources: ["tail1"]
sourceVaultSlug: "hbr-seg-tail1"
originDay: 1
articleStem: "hbr-tail-107-lenovo-ai-supply-chain"
sourceUrl: "https://hbr.org/2026/05/how-lenovo-built-an-ai-powered-supply-chain"
sourceTitle: "How Lenovo Built an AI-Powered Supply Chain"
---
# Value-Driven AI Deployment

**Framework — Value-Driven AI Deployment.** The methodology Lenovo used to select its AI use cases, ensuring that *technology serves the business rather than the business serving the technology* — the essence of [[contrarian-business-first-ai]].

1. **Identify primary business goals** (e.g., resilience, supporting revenue growth targets).
2. **Analyze processes** to determine which ones most *need* AI to achieve those specific goals.
3. **Develop focused use cases** — Lenovo landed on roughly **10 specific use cases** tailored to those processes, including [[concept-supply-commit-accuracy-system]], [[concept-smart-allocation-system]], and [[concept-predictive-quality-management]].

This framework is the operating logic behind [[action-align-ai-with-business]].

> **Enrichment validation — strongly supported.** McKinsey's "AI at scale" framework and broader transformation literature consistently recommend business-goal-first AI: start from value pools (resilience, working-capital reduction, service-level improvement) and select processes where AI is necessary, rather than experimenting with technology for its own sake.