---
id: "claim-ai-spend-imbalance"
type: "claim"
source_timestamps: ["\\\"§ 3. Design AI with Workers", "Not Just for Them\\\""]
tags: ["budget-allocation", "change-management", "roi"]
related: ["contrarian-ai-cost-cutting", "quote-human-hurdle"]
confidence: "high"
testable: true
provenance: "Deloitte research statistic"
sources: ["adoption"]
sourceVaultSlug: "hbr-seg-adoption"
originDay: 9
articleStem: "hbr-edu-40-workers-dont-trust-ai"
sourceUrl: "https://hbr.org/2025/11/workers-dont-trust-ai-heres-how-companies-can-change-that"
sourceTitle: "Workers Don’t Trust AI. Here’s How Companies Can Change That."
---
# 93% of AI Spend Ignores Human Factors

**Claim:** Enterprise AI expenditure is massively imbalanced: companies devote **93% of spending to data, technology, and infrastructure** and only **7% to people-related issues** — redesigning work, training, change management, and reimagining roles and career paths. This underinvestment in the human element directly contributes to the failure of AI scaling efforts (see [[contrarian-ai-cost-cutting]]; this is the numeric backbone of the thesis in [[quote-human-hurdle]]).

**Confidence: HIGH** (as reported), with a provenance caveat.

**Enrichment validation:** *Plausible and likely accurate for Deloitte's dataset,* but the precise **93/7 split is not widely corroborated outside this HBR/Deloitte context.** Treat it as a **Deloitte research statistic**, not a universal industry benchmark. The *qualitative* point — chronic underinvestment in human/organizational factors relative to technology — is a recurring theme across Deloitte and broader sociotechnical-systems literature.