This week saw important progress in multi-agent AI systems where groups of AI helpers work together like teams. The Digital Twin Consortium introduced a new capabilities framework shaped like a periodic table. It sorts AI agents into five maturity levels: from basic rule-followers (Level 1) to conversational helpers (Level 2), workflow managers (Level 3), independent problem-solvers (Level 4), and finally teams that create new ideas together (Level 5). This helps businesses compare different AI agents fairly.

Major tech companies revealed new platforms for building these systems. Microsoft launched Deep Research in Azure AI Foundry for enterprise use and introduced 11 specialized security agents that automatically protect businesses from cyber threats. IBM created a unified platform to manage AI teams safely, while Virtual developed the Agentic Commerce Protocol – a communication system that lets different AI agents make transactions with each other, similar to how banks exchange money.

Customer experience saw big changes with autonomous AI agents that act without waiting for commands. These systems now watch customer interactions, learn patterns, and fix issues before they become problems. For example, they might reroute a frustrated customer during a chat or suggest new services proactively. Cisco research indicates that by 2028, over two-thirds of customer experiences will be shaped by this technology.

Business strategy got smarter with multi-agent simulation platforms. Companies like Capital One now use teams of AI agents representing customers, regulators, and competitors to test plans. Columbia University found this approach simulates human behavior 75% more accurately than single-AI methods. These simulations help leaders spot blind spots – like when Amazon surprised retailers by buying Whole Foods – and build confidence in decisions.

Specialized agents are spreading across industries. Startups are leading this change: Harvey AI builds legal workflow agents, Innovaccer creates healthcare assistants, and Shield AI develops military systems. Jotform offers ready-made customer service agents for law firms, while Zapier connects nearly 8,000 apps so agents can work across business tools. In electronics design, companies demonstrated multi-agent systems that handle complex chip creation workflows.

New management skills are emerging as AI teams grow. Workers must learn to prompt agents effectively, set clear goals, and monitor digital workers. Delinea emphasized that autonomous AI requires new security rules: classifying AI identities, setting task boundaries, and continuous behavior monitoring. Nvidia CEO Jensen Huang envisions companies employing millions of AI agents, with humans and AIs collaborating in communication tools like Slack.

Research advanced with new testing standards like the Agentic Benchmark Checklist for evaluating AI teams. Studies also showed memory-enabled agents preserving cultural heritage by recognizing risk patterns over time. However, integrating these systems with older technology remains challenging due to privacy risks and technical hurdles.

Looking ahead, low-code tools from Google and others will make agent-building accessible. Microsoft's Copilot agents (Researcher, Analyst) and Google's Workspace gems will transform office work. As Wang Guanchun of Laiye noted, future leadership will be measured by how many digital workers a manager can effectively guide.