---
id: "quote-human-hurdle"
type: "quote"
source_timestamps: ["¶34"]
tags: ["thesis-summary", "human-centric"]
related: ["claim-ai-spend-imbalance", "concept-make-or-break-layer"]
speaker: "Ashley Reichheld et al."
speakers: ["Ashley Reichheld", "Christina Brodzik", "Anne-Claire Roesch", "Greg Vert", "Ryan Youra"]
quote: "Because ultimately, AI's biggest hurdle isn't technical; it's human."
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."
---
# The Human Hurdle

> "Because ultimately, **AI's biggest hurdle isn't technical; it's human.**"
> — [[entity-ashley-reichheld]] et al.

**Why it matters:** the one-sentence thesis of the entire source. It reframes AI adoption from an engineering problem to a **trust, change-management, and skills** problem — the argument quantified by the 93%/7% spending imbalance in [[claim-ai-spend-imbalance]].

**Enrichment corroboration:** Deloitte's companion piece is titled almost identically — *"The real barrier to AI adoption isn't technology — it's trust."* Many industry surveys converge on organizational factors topping the list of AI-adoption obstacles. **Counter-perspective:** some analysts argue that in data-immature organizations, *technical readiness* is still the binding constraint, so read this as a strong but not absolute claim — trust is one necessary condition among several (data, architecture, governance, process redesign).