---
id: "question-future-state-ai"
type: "open-question"
source_timestamps: ["¶52 (Daniela Seabrook)"]
tags: ["strategy", "uncertainty"]
related: ["action-chunk-learning-journey", "quote-disrupt-ourselves", "entity-daniela-seabrook"]
speakers: ["Daniela Seabrook"]
resolutionPath: "Will be resolved iteratively as organizations chunk their learning journeys and discover the practical limits and capabilities of agentic AI in real-world workflows."
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"
---
# What Does the Future State (Point B) Actually Look Like?

Organizations are declaring they want to **'ride the wave to the AI future,'** but leaders admit they **do not actually know what that future state (Point B or Point C) looks like.** The exact structural makeup of a fully AI-integrated enterprise remains **theoretical.** Surfaced by [[entity-daniela-seabrook|Daniela Seabrook]].

**Resolution path:** Will be resolved **iteratively** as organizations chunk their learning journeys (see [[action-chunk-learning-journey]]) and discover the practical limits and capabilities of agentic AI in real-world workflows. This uncertainty is precisely why rigid multi-year training plans are discouraged, and why [[quote-disrupt-ourselves]] frames continuous self-disruption as survival.