---
id: "claim-people-issues-drive-failure"
type: "claim"
source_timestamps: ["§ Advice for Other Organizations"]
tags: ["digital-transformation", "root-cause"]
related: ["concept-pull-vs-push-adoption", "contrarian-tech-is-secondary", "question-matrix-adoption-gap"]
confidence: "high"
testable: false
sources: ["adoption"]
sourceVaultSlug: "hbr-seg-adoption"
originDay: 9
articleStem: "hbr-edu-41-french-spirits-employee-buy-in"
sourceUrl: "https://hbr.org/2025/12/how-a-french-spirits-company-created-employee-buy-in-for-ai"
sourceTitle: "How a French Spirits Company Created Employee Buy-In for AI"
---
# Digital Transformation Failures Stem from People Issues, Not Technology

The researchers assert that the vast majority of digital-transformation initiatives that fizzle out do so because of human resistance, skepticism, and poor change management — not the technical limitations or flaws of the software itself. This underpins the [[concept-pull-vs-push-adoption]] strategy and the contrarian insight [[contrarian-tech-is-secondary]].

**Confidence:** high. **Testable:** no (a framing/attribution claim rather than a falsifiable prediction).

**Enrichment assessment.** Directionally supported and aligned with expert consensus. HBS Working Knowledge stresses that success hinged on addressing resistance, training, and support rather than unique technology; the Think Insights synthesis states successful AI integration is 'fundamentally about people and culture, not just technology.' McKinsey's often-cited surveys report ~70% of transformations fail, largely due to employee resistance, unclear vision, and inadequate change management. **Nuance / counter-perspective:** 'vast majority' may be somewhat overstated — technical factors (data quality, integration complexity, legacy systems, regulatory compliance) are also documented failure causes, especially in healthcare and finance. People issues are major drivers but not the sole driver; the two are intertwined. See [[question-matrix-adoption-gap]] for a within-case example where tool characteristics (creative vs. analytical work) shaped adoption.