---
id: "claim-individual-gains-insufficient"
type: "claim"
source_url: "https://hbr.org/2024/12/how-to-create-value-systematically-with-gen-ai"
source_title: "How to Create Value Systematically with Gen AI"
source_timestamps: ["§ Individual Improvements"]
tags: ["productivity", "roi", "enterprise-strategy"]
related: ["concept-so-so-technologies", "concept-value-creation-pyramid"]
confidence: "high"
enrichment_confidence: "medium-high"
testable: true
sources: ["spine"]
sourceVaultSlug: "hbr-seg-spine"
originDay: 1
articleStem: "hbr-nm-98-create-value-systematically-genai"
sourceUrl: "https://hbr.org/2024/12/how-to-create-value-systematically-with-gen-ai"
sourceTitle: "How to Create Value Systematically with Gen AI"
---
# Individual AI productivity gains do not impact enterprise competitiveness

**Claim.** While Gen AI delivers significant one-time productivity improvements for isolated tasks — customer-service agents resolving issues **34% faster**, software engineers delivering **26% more code**, data scientists completing tasks **10% faster** — these gains represent minimal impact when applied across an entire enterprise. Organizations relying solely on these individual improvements will not increase overall competitiveness and may **lag behind** peers adopting higher-level AI strategies (levels 2–4 of the [[concept-value-creation-pyramid]]). This is the mechanism behind [[concept-so-so-technologies]] and the contrarian framing [[contrarian-productivity-gains-are-insufficient]].

**Confidence:** high (extraction) / medium-high (enrichment). Testable: yes.

**Enrichment / validation.** The *factual premise* — that individual gains are large — is strongly supported by RCTs: customer-support agents using GenAI at a large US software firm resolved **14% more issues per hour** and were **35% faster** to first response (lower-skilled workers benefited most); a BCG experiment found consultants using GPT-4 completed creative product-innovation tasks **25% faster** with higher quality; coding-assistant studies report **20–40%** shorter completion times for well-specified tasks. These align directionally with the article's 26–34% figures.

The *strategic conclusion* — that such gains rarely shift enterprise competitiveness — is consistent with Acemoglu & Restrepo's "so-so technologies" and with PwC-style frameworks arguing value requires linking AI to end-to-end value chains and business-model change. However, this is a **normative/strategic interpretation**, not a directly measured law. Counter-evidence: for firms with large labor cost bases, even 5–10% aggregate efficiency can materially shift margins.


## Related across articles
- [[claim-individual-productivity-roi]]
- [[concept-so-so-technologies]]
- [[concept-efficiency-ceiling]]