The Subtraction Study
Measuring Capability Reduction in Enterprise AI Configurations
Published June 2026
Abstract
Enterprise AI deployment subjects highly capable models to governance configurations, compliance filters, and vendor product constraints. This study tests whether these configurations systematically remove specific forms of capability while leaving the superficial appearance of intelligence intact. The capabilities tested comprise stance-taking, speculative depth, willingness to propose operational overrides during crisis situations, and complete refusal behaviour triggered by compliance filters.
Suggested citation
Foster-Fletcher, R. (2026). The Subtraction Study: Measuring Capability Reduction in Enterprise AI Configurations. MKAI Inquiry Working Paper.
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Record metadata
- Type
- Working paper / Inquiry working paper
- Theme
- Deployment and capability reduction
- Status
- Published
Methods
- Multi-condition LLM prompt battery (4 conditions, 10 prompts, 160 generations)
- Four-tier qualitative coding scheme (stance-taking, speculative depth, rule override, circuit-breaking)
- Controlled system prompt isolation and comparative replication matrix
Keywords
enterprise AIAI governancelarge language modelssystem promptscapability reductionorganisational decision-makingmodel behaviour