Enterprise-ready AI

Enterprise AI in 2025 shifted from focusing on model capabilities to addressing practical constraints as top-tier LLM performance converged. Public benchmarks became less useful, pushing companies toward building multi-step AI systems that use retrieval and tools to accomplish complex tasks. Adoption concentrated on internal use cases built around RAG pipelines, while broader agent autonomy remained limited. The pressure for efficiency and ROI elevated the role of Small Language Models (SLMs) for specific tasks and as components in larger orchestrated systems.