Getting in Contract with Large Language Models—An Agency Theory Perspective on Large Language Model Alignment
Authors’ abstract
Getting in Contract with Large Language Models – An Agency Theory Perspective on Large Language Model Alignment Research Paper Sascha Kaltenpoth1 and Oliver Müller1 Paderborn University, Department of Business Administration and Economics, Paderborn, Germany Abstract. Adopting Large language models (LLMs) in organizations potentially revolutionizes our lives and work. However, they can generate off-topic, dis- criminating, or harmful content. This AI alignment problem often stems from misspecifications during the LLM adoption, unnoticed by the principal due to the LLM’s black-box nature. While various research disciplines investigated AI align- ment, they neither address the information asymmetries between organizational adopters and black-box LLM agents nor consider organizational AI adoption pro- cesses. Therefore, we proposeLLM ATLAS(LLMAgencyTheory-LedAlignment Strategy) a conceptual framework grounded in agency (contract) theory, to mitigate alignment problems during organizational LLM adoption. We conduct a conceptual literature analysis using theorganizational LLM adoption phasesand the agency theoryas concepts. Our approach results in providing an extended literature analysis process specific to AI alignment methods during organizational LLM adoption and providing a first LLM alignment problem-solution space. Keywords:Large Language Models, Organizational LLM Adoption, LLM Align- ment, Agency Theory
Paper
- Authors
- S. Kaltenpoth, O. Müller
- Publication date
- 2026
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