Whose Alignment? Comparing LLM Process Alignment Across Diverse Organizational Decision Contexts
arXiv:2605.25256v2 Announce Type: replace Abstract: Steerable pluralism requires a model to faithfully represent one specified perspective. Organizations are a natural setting for this demand, since they deploy LLMs to make decisions that must reflect their own policy. Yet, most existing work fixes that perspective at the level of individuals or demographic groups. We rely on a decision-policy capturing method to measure process alignment in organizational settings, assessing whether an LLM faithfully reproduces the organization's decision policy rather than merely reaching the same conclusion
The proliferation of LLMs in enterprise settings is forcing a re-evaluation of how these models can be aligned with specific organizational policies rather than individual preferences.
Ensuring LLMs adhere to organizational policies is critical for maintaining corporate governance, compliance, and strategic alignment, especially as AI adoption scales.
The focus of LLM alignment is shifting from individual or demographic perspectives towards organizational decision policies, enabling more reliable and controlled AI deployment in businesses.
- · Organizations implementing LLMs
- · AI governance and compliance platforms
- · Enterprise AI developers
- · Consulting firms specializing in AI policy
- · LLM developers ignoring organizational process alignment
- · Organizations with ill-defined internal policies
- · Generic AI solutions without customization capabilities
Companies will increasingly demand LLMs capable of 'process alignment' to their specific operational guidelines.
New AI tooling will emerge to support the 'decision-policy capturing' necessary for organizational alignment.
The legal and ethical frameworks for AI will begin to incorporate requirements for demonstrable organizational alignment and policy adherence.
This signal links to a primary source. Continuum Brief monitors and indexes it as part of the live intelligence stream — we do not republish source content.
Read at arXiv cs.AI