---
id: "framework-3m-ai-rollout"
type: "framework"
source_timestamps: ["§ Create intelligent failure protocols"]
source_url: "https://hbr.org/2026/02/how-to-foster-psychological-safety-when-ai-erodes-trust-on-your-team"
source_title: "How to Foster Psychological Safety When AI Erodes Trust on Your Team"
tags: ["rollout-strategy", "pilot-programs", "feedback-loops"]
related: ["entity-3m", "concept-intelligent-ai-failures"]
speakers: ["Jayshree Seth"]
steps: ["Test tools initially with a micro-group of 1 to 3 technical experts tasked specifically with finding and reporting every issue.", "\\\"Share the identified problems widely across the organization", "alongside the exact changes instituted to fix them.\\\"", "\\\"Expand to a larger pilot group consisting of volunteers", "emphasizing a learning mode rather than a deployment mode.\\\"", "\\\"Execute regional and global rollouts", "utilizing the established checkpoints to continuously catch and learn from failures.\\\""]
sources: ["adoption"]
sourceVaultSlug: "hbr-seg-adoption"
originDay: 9
articleStem: "hbr-cl-79-psychological-safety-ai-trust"
sourceUrl: "https://hbr.org/2026/02/how-to-foster-psychological-safety-when-ai-erodes-trust-on-your-team"
sourceTitle: "How to Foster Psychological Safety When AI Erodes Trust on Your Team"
---
# 3M's Phased AI Failure-to-Improvement Loop

The concrete case study that operationalizes pillar 3 of the [[framework-ai-integration-principles|Psychological Safety Principles framework]]. At [[entity-3m]], [[entity-jayshree-seth|Jayshree Seth]]'s team used a **specific, phased rollout strategy** for generative-AI tools in R&D, designed to build **multiple checkpoints for catching and learning from failures** — a highly visible *failure-to-improvement loop* that signaled a learning mindset to the whole organization.

**The four phases:**
1. **Micro-group probe (1–3 technical experts)** — tasked *specifically* with finding and reporting *every* issue.
2. **Broadcast problems + fixes** — share the identified problems widely, *alongside the exact changes* instituted to fix them (this is what makes the loop visible and safe).
3. **Volunteer pilot** — expand to a larger group of volunteers, emphasizing **learning mode, not deployment mode.**
4. **Regional & global rollout** — scale out, using the established checkpoints to keep catching and learning from failures.

The design intent is to manufacture [[concept-intelligent-ai-failures]] at low risk and make their resolution public, so questioning AI becomes normal. 3M paired this with [[action-demystify-pattern-matching|demystifying AI as "pattern matching," not "thinking"]].

**Enrichment:** The looping failure-to-improvement structure is consistent with broader digital-transformation practice (pilots → feedback loops → staged rollout) and with Seth Mattison's low-stakes-first testing recommendation. Primary source for the specific 3M case is the HBR article itself.