One of 4 dimensions that determine AI vulnerability archetype assignment
The Creation vs. Curation dimension captures the most fundamental distinction in how knowledge workers generate value. At one pole, value comes from producing new artifacts: writing reports, building analyses, generating designs, composing code, or drafting documents. At the other pole, value comes from evaluating, selecting, and improving what already exists or what others have produced. Most knowledge work involves both activities, but the balance between them varies enormously across roles and has profound implications for AI vulnerability.
This dimension matters for AI vulnerability because generative AI systems are fundamentally creation tools. Large language models produce text, code, analyses, and summaries at speeds and volumes that no human can match. The cost of creation is dropping toward zero for many output types. When creation becomes cheap, the bottleneck in organizational value chains shifts to curation: deciding which outputs are worth pursuing, which need refinement, and which should be discarded entirely. Roles that are heavily weighted toward creation face the most direct displacement pressure.
The relationship between AI capability and this dimension is asymmetric. AI can accelerate creation dramatically, producing adequate first drafts of most standard knowledge-work outputs. But curation requires contextual judgment that current AI systems handle poorly: understanding organizational priorities, assessing audience needs, recognizing when technically correct output is strategically misleading, and knowing when an adequate draft needs to be excellent versus when adequate is sufficient. These judgment calls depend on tacit knowledge, political awareness, and relational context that resist automation.
The scoring mechanism combines three tradeoff pairs that probe the creation-curation balance in different contexts with two scenario responses that test how the person thinks about quality and AI-driven role change. The tradeoff pairs capture the current state of work, while the scenario responses reveal the person's orientation toward creation or curation when confronted with hypothetical situations. Divergence between tradeoff and scenario scores can indicate a person whose cognitive orientation differs from their current role, which is diagnostically significant.
Scoring toward Creation indicates that the majority of daily work involves producing deliverables: documents, analyses, designs, code, or other structured outputs. Value is measured by the volume and quality of what gets generated. AI excels at first-draft creation from documented knowledge, placing creation-heavy roles at higher displacement risk.
Scoring toward Curation indicates that the majority of daily work involves reviewing, selecting, evaluating, and improving what others produce. Value is measured by the quality of judgment applied to inputs rather than the volume of outputs generated. Curatorial roles become more valuable as AI increases the supply of raw outputs that need evaluation.
A moderate position on this dimension indicates a balanced mix of creation and curation in daily work. The person both produces original outputs and evaluates or refines existing ones. This balance provides partial protection against AI displacement because the curatorial component resists automation, while the creation component benefits from AI acceleration.
This dimension is measured through three tradeoff pairs (T1, T2, T3) that directly probe the creation-curation balance, plus two scenario sub-questions (S1b, S2a) that contribute at half weight each.
Archetypes distribute across this dimension in three distinct clusters, with creation-leaning archetypes concentrated among The Exposed, curation-leaning archetypes concentrated among The Durable, and balanced archetypes spanning The Transitioning category.
Archetypes at this end are defined by work that centers on generating outputs from documented knowledge. AI can replicate this production pattern at scale, placing these roles at elevated displacement risk. The creation orientation is the single strongest predictor of high vulnerability scores in the study.
The Accelerated Producer The Template Specialist The Volume Player The Efficiency Amplifier The Confident Automator The Acceleration Navigator The Confident ExplorerArchetypes in the middle range are actively transitioning between creation and curation. Their work involves both producing outputs and evaluating or refining them, and the balance is shifting in real time as AI absorbs more of the production tasks. This transitional position creates both opportunity and measurement challenges.
The Judgment Concentrator The Institutional Memory The Knowledge Translator The Selective Curator The Catalyst The Dual NavigatorArchetypes at this end are defined by evaluating, selecting, and improving work rather than generating it. As AI increases the supply of raw outputs, the demand for curatorial judgment grows. These roles become more valuable in an AI-rich environment, not less.
The Context Bridge The Orchestrator The Sense-Maker The Relationship Architect The Cautious StrongholdThe Creation vs. Curation dimension interacts with the other three dimensions to produce distinctive vulnerability patterns. No single dimension determines archetype assignment in isolation; it is the combination of dimensional positions that defines the profile.
Creation combined with Routine produces the highest vulnerability scores in the study. Roles that generate predictable outputs from documented knowledge following established patterns represent the core of what AI automates. Curation combined with Novel produces the lowest vulnerability scores, representing roles that evaluate unique situations using contextual judgment. The interaction between these two dimensions accounts for more variance in the Vulnerability Index than any single dimension alone.
Creation paired with Individual work amplifies vulnerability because the production occurs in isolation, making it easier to substitute with AI. Creation paired with Coordination is somewhat protected because the social context around the creation resists automation. Curation paired with Coordination represents the most durable configuration on these two dimensions, as cross-boundary evaluation inherently requires human relational skills.
Creation from Explicit knowledge is the combination that AI handles best: generating outputs from documented, codified information is precisely what large language models do. Creation from Tacit knowledge is somewhat more protected because the knowledge source resists extraction. Curation using Tacit judgment represents the strongest protection on these two dimensions, as evaluating quality requires experiential wisdom that no current system can replicate.
Understanding where a role falls on the Creation vs. Curation spectrum is the most actionable insight from the AI Vulnerability assessment. For those who score heavily toward Creation, the path forward involves deliberately building curatorial capabilities: learning to evaluate rather than just produce, to select rather than just generate, and to apply judgment rather than just execute. This shift does not require abandoning creation entirely. It requires ensuring that creation is not the only source of value.
For organizations, this dimension reveals where workforce vulnerability concentrates. Teams composed entirely of creation-heavy roles face systemic displacement risk, while teams with strong curatorial capacity are better positioned to integrate AI productively. The strategic response is to invest in developing curatorial skills across the organization, creating a workforce that can evaluate and direct AI outputs rather than competing with them on production speed.
The AI Vulnerability Study takes approximately 6 minutes. It produces a personalized archetype based on all 4 dimensions.
Take the AssessmentThe AI Vulnerability Study measures 4 dimensions. Each contributes to the archetype assignment.