AI Safety & Alignment

AI safety and alignment encompasses the research, tools, and companies working to ensure AI systems are reliable, trustworthy, and aligned with human values and intentions. The field has moved from academic research to a funded commercial category as the deployment of powerful AI systems creates real-world safety risks including hallucination, bias, misuse, and loss of human control. Companies in this space build evaluation frameworks that test AI systems for safety properties, guardrail systems that constrain AI behavior within safe boundaries, red-teaming tools that identify vulnerabilities, and monitoring systems that detect when deployed AI deviates from intended behavior. The sector gained urgency with the rapid deployment of LLMs in high-stakes domains (healthcare, legal, financial), where AI errors can cause genuine harm. Anthropic, OpenAI, and Google DeepMind all have significant internal safety research teams, while startups like Patronus AI, HaizeAI, and Robust Intelligence (acquired by Palo Alto Networks) build commercial safety tooling. The EU AI Act's classification of high-risk AI systems creates mandatory demand for safety testing and documentation.