The AI SCORE is a self-assessment instrument developed in Vienna, psychometrically designed and GDPR-compliant, for capturing individual AI competence. The instrument is published by the digitalworld Academy OG (Michael Kainz). According to the publisher's self-presentation, it understands itself as a scientifically oriented assessment proposal in the German-speaking world; an independent external validation is not documented.[1]
The assessment takes approximately fifteen minutes and captures the cognitive positioning of participants in relation to artificial intelligence along five competence dimensions: AMP, WIN, LEV, ERS and TGV (see Section 2). The result is assigned to one of seven archetypes, which map the spectrum from the mere adoption of generated content to strategic steering of AI-supported processes (see Section 3).
Within the conceptual environment of the Noocene, the AI SCORE functions as an operative positioning aid: it translates the abstract description of the epoch into an individually accessible self-report about one's own position within the cultural-cognitive epoch of networked intelligence.
1 Concept
The AI SCORE rests on the assumption that AI competence can be described not through factual knowledge but through the way in which a person thinks and works with artificial intelligence. Correspondingly, the instrument does not capture bodies of knowledge but cognitive-operative patterns in the handling of AI systems, in particular of language models.[1]
The psychometric design follows established standards of empirical social research; the five dimensions were formed such that they encompass both operative skills (prompting, workflow integration) and reflexive competences (logic checking, ethical placement, conceptual understanding).
2 The five competence dimensions
The AI SCORE structures its assessment in five distinguishable dimensions, each individually evaluable.
2.1 AMP — AI Mastery & Prompting
The AMP dimension captures precision in the instruction of language models. It ranges from basic prompt formulation to complex system architectures and multi-step prompt chains. AMP-strong persons give language models clear, context-rich and controllable instructions.
2.2 WIN — Workflow Integration & Navigation
The WIN dimension evaluates the ability to integrate AI systems into existing workflows and to design new workflows with their help. It comprises the choice of suitable tools, the interlinking of different AI applications and the steering of productive routines.
2.3 LEV — Logic & Evaluation
The LEV dimension tests the ability to recognise errors, hallucinations and logical inconsistencies in AI outputs, to question them critically and to check them against sources. LEV is the most important dimension of reflexive AI competence.
2.4 ERS — Ethics, Rights & Security
The ERS dimension examines the understanding of ethical, legal and security-related implications of AI deployment — from GDPR compliance through copyright to the risks of algorithmic bias and manipulation. In doing so, ERS also covers the topic field of the EU AI Act.
2.5 TGV — Technical Grasp & Vision
The TGV dimension evaluates the conceptual understanding of how language models and related AI systems function in principle — from the underlying transformer architecture through training procedures to the placement of foreseeable lines of development. TGV combines technical understanding with strategic vision.
3 The seven archetypes
On the basis of the profile across the five dimensions, the AI SCORE assigns the result to one of seven archetypes, which map the competence spectrum from the mere adoption of generated content to strategic steering:
| Archetype | Characterisation |
|---|---|
| Copy-Paster | Adopts AI outputs largely uncritically; low depth of reflection and steering. |
| AI-Refuser | Largely rejects the use of AI systems on principled or pragmatic grounds. |
| Efficiency Hunter | Seeks primarily immediate productivity gains, with limited interest in methodological depth. |
| Sceptic | Deploys AI purposefully but consistently questions outputs and effects; high LEV and ERS scores. |
| Experimenter | Tries out new tools and applications with a pronounced learning curve and willingness to take risks. |
| Prompt Architect | Masters the structured instruction of language models at a high level; high AMP and WIN scores. |
| AI Strategist | Unites operative skill with conceptual and ethical reflection; uses AI as a strategic instrument of the organisation and of one's own activity. |
4 Relation to the digitalworld Academy
The AI SCORE is published by the digitalworld Academy OG and is anchored in particular in the context of the AI-Management diploma programme offered there. The instrument serves at once as an entry diagnosis and as a measure of learning progress: participants complete the AI SCORE before and after the course, so that the change in the individual competence profile can be documented.[2]
The assessment is designated as a formal component of the Academy's diploma award.
5 Relation to the Noocene
In the conceptual environment of the first publication of the term The Noocene on 17 March 2026 at The Digioneer, the AI SCORE was introduced as an operative positioning aid: it offers individuals the possibility of practically determining their own position within the epoch of cognitively networked world-production described by the Noocene.
In terms of content the five dimensions of the AI SCORE connect to the characteristics of the Noocene: the combination of AMP/WIN (operative AI use), LEV (reflexive checking), ERS (ethical-legal placement) and TGV (conceptual depth) mirrors the qualitative constitution of the epoch described in Section 4 of the main article — not the tool but the mode of world-relation stands at the centre.
6 See also
- The Noocene (concept)
- Integrative intelligence (cognitive disposition behind cross-domain AI competence)
- The Digioneer (online magazine)
- Michael Kainz (publisher)
- Prompt engineering
- EU AI Act
- Hallucination (artificial intelligence)
7 External links
- AI SCORE — official self-assessment page
- AI-Management diploma programme of the digitalworld Academy
- digitalworld Academy
8 References
- Self-presentation of the AI SCORE at ki-management.vercel.app/ai-score, accessed 28 May 2026.
- Programme description of the AI-Management diploma programme at ki-management.vercel.app, accessed 28 May 2026.