{
  "schema": "vedokrok.public-item.v1",
  "release_id": "MHC-RPUB-20260920-75ad787a",
  "url": "/knowledge/automate-the-part-you-can-change-without-waiting-for-everyone-else",
  "id": "MHC-D-RESEARCH-0381",
  "version": "0.1.0",
  "title": "Automate the part you can change without waiting for everyone else",
  "summary": "A local tool can change your drafting today. It cannot unilaterally cancel everyone else's meetings.",
  "kind": "heuristic",
  "body": "Separate work changes you can make independently from those that require new team norms, approvals or shared workflows. Start AI experiments where one worker can change the process and measure the result. Treat coordination-dependent benefits as a separate organizational change problem rather than assuming tool access will create them.",
  "limits": [
    "Local optimization can shift work to others; measure downstream burden before declaring the independent change a net gain."
  ],
  "topics": [
    "union-ai-assisted-thinking-work"
  ],
  "intents": [],
  "source_ids": [
    "RS-035E1521DB1A895E"
  ],
  "evidence": [
    {
      "claim": "A randomized field experiment with 6,000 workers found that AI access reduced time spent on email and appeared to speed document work, while meeting time did not significantly change.",
      "source_id": "RS-035E1521DB1A895E",
      "role": "supports",
      "note": "The intervention and work environment were specific; organization-wide coordination effects should not be inferred from individual task savings.",
      "locator": "Abstract results"
    },
    {
      "claim": "The 6,000-worker field experiment concluded that AI initially changed behaviors workers could modify independently more than behaviors requiring coordination with others.",
      "source_id": "RS-035E1521DB1A895E",
      "role": "supports",
      "note": "This describes the studied deployment period and should not be treated as a permanent law of AI adoption.",
      "locator": "Abstract interpretation"
    }
  ],
  "use_when": [
    "AI adoption is stuck because the desired benefit depends on organization-wide coordination."
  ],
  "avoid_when": [
    "Local optimization can shift work to others; measure downstream burden before declaring the independent change a net gain."
  ],
  "example": "Use AI to reduce email drafting time now; do not count fewer meetings as an expected benefit unless meeting norms and decision processes also change.",
  "check": "The experiment's expected benefit matches the level of coordination the intervention can actually influence.",
  "sources": [
    {
      "id": "RS-035E1521DB1A895E",
      "title": "Shifting Work Patterns with Generative AI",
      "url": "https://www.microsoft.com/en-us/research/publication/shifting-work-patterns-with-generative-ai/"
    }
  ],
  "relations": [
    {
      "from": "MHC-D-RESEARCH-0381",
      "to": "MHC-D-RESEARCH-0382",
      "type": "useful_with",
      "url": "/knowledge/measure-ai-speed-and-quality-as-separate-outcomes"
    }
  ],
  "collections": [
    {
      "id": "RC-433FB61AA7D7AF43",
      "title": "Use AI where it helps, and keep the thinking that still matters",
      "url": "/collections/use-ai-where-it-helps-and-keep-the-thinking-that-still-matters"
    }
  ]
}