What is AI Alignment?

AI alignment is the challenge of ensuring that artificial intelligence systems behave in ways that are consistent with human values and intentions. It encompasses both narrow alignment (making an AI follow specific instructions correctly) and broad alignment (ensuring AI systems don't cause unintended harm at scale).

Techniques for alignment include: Reinforcement Learning from Human Feedback (RLHF), Constitutional AI (training AI to follow explicit ethical principles), red-teaming (adversarial testing to find unsafe behaviors), and guardrails (runtime constraints that prevent harmful outputs).

For enterprise applications, alignment is a governance concern. An AI system that is technically capable but misaligned with business objectives, ethical guidelines, or regulatory requirements is a liability. Misaligned AI can generate inappropriate content, make biased decisions, or take harmful autonomous actions.

In 2026, alignment is a board-level concern. The EU AI Act requires organizations to demonstrate that high-risk AI systems are aligned with safety requirements. SEC guidance requires disclosure of material AI risks, including alignment failures.