AI Trends 2026: Agents, Federated Learning, Small Models

AI strategy for 2026 is shifting from “AGI soon” narratives to pragmatic deployments constrained by compute, risk, and adoption realities. Trinetix argues AGI remains unlikely in the near term due to resource/energy demands, unresolved issues like hallucinations, and unclear enterprise purpose. It highlights agentic AI as workflow-level augmentation that requires significant reskilling and AI literacy across business, agent, and human skills. It also points to federated learning to train models without centralizing sensitive data (notably in healthcare and fraud detection) and to small language models as faster, cheaper, domain-focused options. For tech leaders, the takeaway is to scope use cases tightly, pair agents with governance and training, and choose data/model architectures that fi