---
id: "concept-digital-playgrounds"
type: "concept"
source_timestamps: ["§ 4. Encourage Experimentation"]
tags: ["experimentation", "no-code", "innovation-culture"]
related: ["contrarian-metric-penalties", "entity-colgate-palmolive", "action-build-no-code-playgrounds", "prereq-frontline-metrics", "framework-five-approaches-ai-trust"]
definition: "Secure, low-risk enterprise environments that allow non-technical employees to experiment with, build, and share AI tools without fear of metric-based penalization."
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."
---
# Digital Playgrounds

**Digital Playgrounds** are secure, low-risk enterprise environments where employees — *especially those without formal programming skills* — can safely test new AI tools, learn by doing, and share successful workflows **without fear of penalization**. They are the fourth of the [[framework-five-approaches-ai-trust]] and are, in effect, an attempt to engineer localized *psychological safety* (à la Amy Edmondson) around AI experimentation.

The problem they solve: traditional frontline metrics (time-clock violations, late scans, missed check-ins) are designed to *catch errors and enforce consistency*, which actively discourages the trial-and-error that AI adoption requires (see [[contrarian-metric-penalties]] and the prerequisite context in [[prereq-frontline-metrics]]). Digital playgrounds counter this by **rethinking incentives to reward curiosity**.

The flagship example is [[entity-colgate-palmolive]]'s **AI Hub**, a no-code platform on which employees built between **3,000 and 5,000 custom AI assistants by mid-2025**. Grassroots innovations emerge here — such as a **Greek factory manager building a local-language troubleshooting assistant from German manuals**, and an HR goals coach — and the most valuable can be **scaled enterprise-wide based on user feedback loops**. The operational recipe is captured in [[action-build-no-code-playgrounds]].

Counter-consideration: without governance, this experimentation can produce "AI sprawl" — fragmented workflows, duplicated effort, and local hacks that don't scale — so playgrounds should be paired with consolidation and architecture discipline.


## Related across articles
- [[prereq-psychological-safety-d79]]
- [[action-introduce-innovation-grants]]
- [[action-peer-activators]]