Artificial Intelligence has moved beyond experimentation. For many businesses in 2026, AI is no longer a pilot project or a productivity add-on. It is becoming core operational infrastructure. The shift from testing AI to relying on it introduces new risks and responsibilities, particularly around data quality, trust, and governance. The companies that succeed in this transition will not be the ones that adopt AI the fastest, but the ones that prepare their systems, data, and capital strategy to support it sustainably. From AI Experiments to Mission Critical Systems Early AI adoption focused on surface-level use cases such as chatbots, content generation, and basic analytics. Today, businesses are moving toward Agentic AI systems , AI that can execute multi-step workflows, make decisions, and act autonomously across departments. Examples include • Automated inventory forecasting tied directly to purchasing • AI-driven credit decisions and risk scoring • End-to-end customer serv...