---
id: "action-chunk-learning-journey"
type: "action-item"
source_timestamps: ["¶53 (Daniela Seabrook)"]
tags: ["training-strategy", "agile"]
related: ["claim-role-specific-upskilling", "question-future-state-ai", "entity-daniela-seabrook"]
speakers: ["Daniela Seabrook"]
action: "Design AI upskilling in short, immediately applicable sprints rather than rigid 18-month roadmaps."
outcome: "Prevents training programs from becoming obsolete before completion and encourages continuous adaptation."
sources: ["reskilling"]
sourceVaultSlug: "hbr-seg-reskilling"
originDay: 10
articleStem: "hbr-edu-43-leading-human-ai-organization"
sourceUrl: "https://hbr.org/2026/05/leading-the-human-ai-organization"
sourceTitle: "Leading the Human-AI Organization"
---
# Chunk the AI Learning Journey

**Action:** Design AI upskilling in **short, immediately applicable sprints** rather than rigid 18-month roadmaps.

Because the **'Point B'** of AI integration is constantly moving (see [[question-future-state-ai]]), do **not** attempt to build rigid **12-to-18-month training plans.** Instead, break the learning journey into **smaller, immediate steps**, apply the knowledge instantly, and iterate based on what is discovered. Recommended by [[entity-daniela-seabrook|Daniela Seabrook]]; pairs with [[claim-role-specific-upskilling]].

**Expected outcome:** Prevents training programs from becoming obsolete before completion and encourages continuous adaptation.