---
id: "framework-pernod-ricard-buy-in"
type: "framework"
source_timestamps: ["§ How the Company Gained Buy-In"]
tags: ["change-management", "strategy"]
related: ["concept-risk-free-adoption", "concept-technology-ambassadors", "concept-pull-vs-push-adoption", "framework-hbs-ai-adoption-playbook"]
steps: ["\\\"Demonstrate real value through testing: run localized A/B tests to prove tangible", "measurable improvements (e.g.", "net market share growth) vs. control groups.\\\"", "\\\"Take the risk out of adoption: restructure evaluations so employees are not penalized for following AI recommendations that fail", "but face scrutiny if they ignore the AI and miss targets.\\\"", "\\\"Invest in education and support: deploy dedicated local teams (change-management specialists", "data analysts", "trainers) and hotlines for immediate troubleshooting.\\\"", "Leverage internal champions: recruit highly respected veteran employees in each market as technology ambassadors to drive peer-to-peer adoption."]
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"
---
# Pernod Ricard's 4 Pillars of AI Buy-In

A four-pillar strategy used by [[entity-pernod-ricard-d9]] to overcome deep employee skepticism and achieve 60–85% adoption rates for new AI tools across a traditional, global workforce. HBS Working Knowledge organizes the case under exactly these four headings, and the pillars map onto the more general [[framework-hbs-ai-adoption-playbook]].

**The four pillars:**

1. **Demonstrate real value through testing** — Run localized A/B tests to prove the tools deliver tangible, measurable improvements (e.g., net market share / net sales growth for stores following [[entity-d-star]] versus a control group). Operationalized as [[action-run-local-ab-tests]].
2. **Take the risk out of adoption** — Restructure performance evaluations so employees are not penalized if they follow AI recommendations that fail, but face scrutiny if they ignore the AI and miss targets. See [[concept-risk-free-adoption]], [[action-restructure-evaluations]], and [[quote-safe-harbor-compliance]].
3. **Invest in education and support** — Deploy dedicated local teams (change-management specialists, data analysts, trainers) and establish hotlines for immediate troubleshooting.
4. **Leverage internal champions** — Identify and recruit highly respected, veteran employees in each market to serve as technology ambassadors, driving peer-to-peer adoption. See [[concept-technology-ambassadors]] and [[action-leverage-champions]].

**Enrichment assessment.** Precisely supported by the HBS article; the terminological framing matches exactly. The quoted adoption numbers — 85% for [[entity-d-star]] and 60–70% for [[entity-matrix]] by 2023 — are directly reported. Together, the pillars produce the [[concept-pull-vs-push-adoption]] dynamic.


## Related across articles
- [[framework-five-approaches-ai-trust]]
- [[framework-building-ai-with-workers]]