MoonPay launched MoonPay Agents on February 24, 2026, enabling AI systems to execute cryptocurrency payments autonomously. The platform represents a shift from chatbots that answer questions to agents that complete transactions.
"Companies have AI that can answer questions, but not AI that can act," said Murali Swaminathan, highlighting the gap between current LLM capabilities and emerging autonomous systems. MoonPay Agents bridges this divide by giving AI models payment execution abilities.
Claude AI is helping identify targets and prioritize them for US strikes on Iran, MIT Technology Review reported. The deployment moves LLMs beyond information retrieval into military decision-making, where AI recommendations directly influence tactical operations.
Rad AI's technology transforms data chaos into actionable insights for healthcare providers, automating radiologist workflows rather than simply analyzing medical images. The system makes scheduling decisions and prioritizes cases without human intervention.
The shift from passive to agentic AI changes development priorities. Traditional LLMs optimize for accuracy and knowledge retrieval. Autonomous agents require decision-making frameworks, action execution capabilities, and safety constraints to prevent unintended consequences.
Payment processing, military targeting, and healthcare automation represent three distinct agent categories emerging in early 2026. Financial agents execute transactions, tactical agents recommend military actions, and workflow agents automate professional services.
Enterprise adoption requires new infrastructure. AI agents need API integrations to external systems, permission frameworks to limit action scope, and audit trails to track autonomous decisions. These requirements differ from chatbot deployments that only generate text responses.
Investment patterns are shifting toward agentic platforms. MoonPay Agents targets developers building AI applications that interact with financial systems, creating a new category beyond conversational AI tools.
The transition raises questions about liability and control. When an AI agent executes a payment or influences a military strike, accountability frameworks must determine responsibility for autonomous decisions. Current regulations treat AI as advisory tools, not decision-making entities.
Q1-Q2 2026 will test enterprise appetite for autonomous agents versus traditional LLMs. Early adoption in payments and military applications suggests high-stakes domains are moving fastest toward agentic AI, despite greater risks.