---
id: "framework-ai-strategic-diagnostic"
type: "framework"
source_timestamps: ["§ A Diagnostic for Leaders"]
tags: ["leadership-assessment", "strategic-planning"]
related: ["concept-growth-blindspot", "concept-absorptive-capacity", "concept-organic-vs-inorganic-growth", "action-audit-efficiency-bias", "action-invest-in-absorptive-capacity", "question-competitive-compression"]
steps: ["Are you focusing too much on cost savings? (Audit the AI roadmap for an efficiency bias that limits P&L impact.)", "Are you focusing too little on growth? (Establish an explicit AI-for-growth agenda with dedicated resources and metrics.)", "Are you treating all growth the same? (Prioritize organic growth over M&A integration to drive multiple expansion.)", "\\\"Are you staying ahead of the competition? (Continuously invest in new AI growth levers", "as early gains like ad optimization will compress as competitors imitate.)\\\"", "\\\"Are you factoring in investor conviction? (Build a deliberate evidence base of field results", "not just pilots", "to convince investors to price in a higher multiple.)\\\"", "\\\"Are you expanding your absorptive capacity? (Remove internal bottlenecks—resistant personnel", "legacy workflows", "slow governance—that prevent AI utilization.)\\\""]
sources: ["spine"]
sourceVaultSlug: "hbr-seg-spine"
originDay: 1
articleStem: "hbr-tier1-04-ai-for-growth"
sourceUrl: "https://hbr.org/2026/06/companies-are-using-ai-for-efficiency-they-should-use-it-to-grow"
sourceTitle: "Companies Are Using AI for Efficiency. They Should Use It to Grow."
---
# AI Strategic Value Diagnostic

The **AI Strategic Value Diagnostic** is a six-question test for senior leaders to check whether their AI roadmap is optimized for durable value creation rather than marginal efficiency. It forces a shift from asking *whether* to adopt AI to *where and how* AI creates multiple-expanding growth. It operationalizes the whole thesis — [[concept-growth-blindspot]], [[concept-absorptive-capacity-d4]], and [[concept-organic-vs-inorganic-growth]].

**The six questions:**
1. **Are you focusing too much on cost savings?** Audit the AI roadmap for an efficiency bias that limits P&L impact. → [[action-audit-efficiency-bias]]
2. **Are you focusing too little on growth?** Establish an explicit AI-for-growth agenda with dedicated resources and metrics.
3. **Are you treating all growth the same?** Prioritize organic growth over M&A integration to drive multiple expansion. → [[concept-organic-vs-inorganic-growth]]
4. **Are you staying ahead of the competition?** Keep investing in new AI growth levers, because early gains (e.g., ad optimization) compress as competitors imitate. → [[question-competitive-compression]]
5. **Are you factoring in investor conviction?** Build a deliberate evidence base of *field* results (not just pilots) to convince investors to price in a higher multiple.
6. **Are you expanding your absorptive capacity?** Remove internal bottlenecks — resistant personnel, legacy workflows, slow governance. → [[action-invest-in-absorptive-capacity]], [[concept-absorptive-capacity-d4]]

**Enrichment.** The diagnostic maps cleanly onto McKinsey's maturity ladder (move from productivity-only levels 1–2 to offering-embedded levels 3–4) and reinforces that question 6's constraint is the classic Cohen & Levinthal absorptive-capacity problem.


## Related across articles
- [[framework-ai-investment-diagnostic]]
- [[framework-gen-ai-advantage-assessment]]