---
id: "action-dial-back-mandates"
type: "action-item"
source_timestamps: ["§ Relieving the Pressure: How Leaders Can Reduce Workslop"]
tags: ["policy", "leadership"]
related: ["claim-blanket-mandates-fail", "concept-performative-ai-use", "framework-system-level-response", "counter-mandates-context-dependent"]
speakers: ["Kate Niederhoffer", "Alexi Robichaux", "Jeffrey T. Hancock"]
action: "Replace vague directives to 'use AI' with specific, role-based expectations for quality output."
outcome: "Reduces performative AI use and the subsequent generation of workslop."
sources: ["adoption"]
sourceVaultSlug: "hbr-seg-adoption"
originDay: 9
articleStem: "hbr-edu-38-ai-workslop"
sourceUrl: "https://hbr.org/2026/01/why-people-create-ai-workslop-and-how-to-stop-it"
sourceTitle: "Why People Create AI “Workslop”—and How to Stop It"
---
# Dial Back Blanket AI Mandates

**Action:** Replace vague directives to 'use AI' with specific, role-based expectations for quality output.

Leaders must stop issuing blanket mandates like 'use AI everywhere every day.' Instead, they should replace them with specific, context-aware guidelines that define what quality AI output looks like for specific roles and missions. This targets [[claim-blanket-mandates-fail]] and short-circuits [[concept-performative-ai-use]]. It implements the **Practice** layer of [[framework-system-level-response]].

**Expected outcome:** Reduces performative AI use and the subsequent generation of [[concept-workslop-d38]].

**Nuance:** [[counter-mandates-context-dependent]] warns that the harm of mandates is context-dependent — pair specificity with room to experiment rather than eliminating adoption pushes entirely.


## Related across articles
- [[claim-mandates-backfire]]
- [[contrarian-mandates-fail]]