---
id: "concept-growth-blindspot"
type: "concept"
source_timestamps: ["¶4", "§ A Diagnostic for Leaders"]
tags: ["strategic-error", "ai-adoption", "executive-mindset"]
related: ["concept-efficiency-ceiling", "claim-ai-value-doubling", "action-audit-efficiency-bias", "quote-efficiency-reflex", "contrarian-efficiency-is-a-trap"]
definition: "The strategic gap between executives' belief that AI can massively multiply firm value and their contradictory behavior of investing in AI almost exclusively for cost-cutting efficiency."
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."
---
# The Growth Blindspot

The **growth blindspot** is the massive cognitive and strategic gap between what executives *believe* AI can achieve and how they *actually* deploy it inside their organizations. In a roundtable of senior financial-services executives, participants universally agreed that effective AI utilization could raise a firm's value by an average of **135% (a 2.35× multiplier) over three years** — see [[claim-ai-value-doubling]]. Yet when the same executives were asked where their organizations were actually directing AI investment, the overwhelming consensus was *efficiency* — and several admitted they had **never even considered AI as a tool for revenue growth**.

That contradiction — belief in transformative value paired with cost-cutting behavior — is the blindspot, and it leaves immense durable firm value on the table. It is the entry point for the entire thesis: it pairs with the [[concept-efficiency-ceiling]] (why cost-cutting caps out) and is corrected by the diagnostic's first move, [[action-audit-efficiency-bias]]. The authors frame the reflex bluntly in [[quote-efficiency-reflex]], and treat it as the vault's central contrarian claim, [[contrarian-efficiency-is-a-trap]].

**Enrichment.** McKinsey's AI-maturity research is directionally consistent: markets do **not** materially reward firms that use AI only for productivity (maturity levels 1–2); valuation multiple expansion shows up only when AI is embedded in offerings and business models (levels 3–4). The specific 135% roundtable figure is the authors' own field estimate, not a market-wide benchmark.