From RAG to agentic AI: When models stop answering and start acting

Retrieval-augmented generation (RAG) gave AI a memory. Agents give it a job description. This captures where enterprise AI is today—the first wave focused on helping models say the right thing, but the next wave is about helping systems do the right thing.Generative AI (gen AI) has moved quickly from experimentation with large language models (LLMs) to a race to operationalize AI at enterprise scale. For many organizations, RAG was the first practical step, grounding model outputs in enterprise data and making gen AI usable in real business contexts. But enterprises don’t run on answers, the