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Evaluating Intra-firm LLM Alignment Strategies in Business Contexts

2025/05/24 by Noah Broestl, Broestl, Noah, Benjamin P. Lange +7
Business, Management and Accounting · Computer Science · #Business Law and Ethics #Computers and Society (cs.CY) #Dispute Resolution and Class Actions #FOS: Computer and information sciences #Law, AI, and Intellectual Property

paper · pdf · doi:10.48550/arxiv.2505.18779

openalex publication_date 2025/05/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Instruction-tuned Large Language Models (LLMs) are increasingly deployed as AI Assistants in firms for support in cognitive tasks. These AI assistants carry embedded perspectives which influence factors across the firm including decision-making, collaboration, and organizational culture. This paper argues that firms must align the perspectives of these AI Assistants intentionally with their objectives and values, framing alignment as a strategic and ethical imperative crucial for maintaining control over firm culture and intra-firm moral norms. The paper highlights how AI perspectives arise from biases in training data and the fine-tuning objectives of developers, and discusses their impact and ethical significance, foregrounding ethical concerns like automation bias and reduced critical thinking. Drawing on normative business ethics, particularly non-reductionist views of professional relationships, three distinct alignment strategies are proposed: supportive (reinforcing the firm's mission), adversarial (stress-testing ideas), and diverse (broadening moral horizons by incorporating multiple stakeholder views). The ethical trade-offs of each strategy and their implications for manager-employee and employee-employee relationships are analyzed, alongside the potential to shape the culture and moral fabric of the firm.

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