AI agents are becoming more powerful and helpful, but companies face a big problem: they don't trust them yet. This weekly update explains what experts and business leaders learned about building trust with AI agents.

Understanding AI Agents and Why They're Different AI agents are a new type of artificial intelligence that works differently from tools like ChatGPT. When you ask ChatGPT a question, it predicts what words should come next based on what it learned. AI agents do something much more complex. They look at everything happening around them and make choices based on what they see. Think of it like self-driving cars that talk to each other on the road—each car is thinking and deciding what to do based on what other cars are doing. These AI agents could help doctors work faster in hospitals, help banks find bad activity, and work in places that might be dangerous for people.

The Big Trust Problem On December 22, 2025, business leaders met to talk about how to build trust in AI agents at work. They discovered something important: trust is the biggest problem stopping companies from using AI agents. Companies are worried that AI agents might make mistakes that lose money, hurt customers, or break laws. Right now, AI agents struggle with understanding the full situation around them, the same way humans understand context. They also don't always know when they should ask a human for help instead of making a decision alone.

Research from Stanford and Harvard universities found something troubling: most AI agents look amazing when companies show them to customers in demos. The agents work perfectly, make smart decisions, and accomplish their tasks. But something strange happens when real people start using these agents at actual jobs. The agents fall apart. They make mistakes they never made in the demo. This is a big problem because companies spent money building these systems, and now they don't work.

What Companies Need to Do Experts say companies need to answer three important questions about their AI agents. First, what is the agent trying to do? Is it working on behalf of a human who is watching it? Is it working with other AI agents? Or is it someone bad trying to cause trouble? Second, what is the agent allowed to do? Companies need to set clear rules about what jobs their AI agents can do and when they must ask a human first. Third, how much power does it have? An AI agent working in a hospital has different power than one organizing emails.

Companies like Experian are helping solve this problem. Experian keeps people safe from fraud and protects their identities, and now they're helping companies protect themselves from AI agents that might cause problems. This is called governance, which means having rules and watching to make sure everything is safe.

Standards Are Starting to Help The good news is that the AI industry is trying to fix the trust problem. In December 2025, companies agreed to use a standard way for AI agents to talk to tools and do their jobs. This standard is called the Model Context Protocol, or MCP. Over 10,000 companies are already using it, and 97 million people download it every month. When everyone uses the same standard, AI agents work better together, and it's easier to watch what they're doing.

Scientists are working on this too. A researcher named Alqahtani received an important award from the U.S. National Science Foundation to figure out how to make multi-agent AI systems that keep working even when something goes wrong. If one agent breaks or gets hacked, the other agents should still work correctly. This is like having backup helpers when one helper takes a break.

What's Coming Next As AI agents become more common in 2026, businesses are learning hard lessons. They're learning that AI agents cannot be trusted to work alone in jobs where mistakes could be serious, like hospitals, banks, law firms, or government offices. AI agents need humans watching them and making the final decisions. The companies that will win in the future are the ones that figure out how to build AI agents that people can trust. They need to be honest about what their AI agents can and cannot do. They need to write clear rules. And they need to always keep humans in charge of the biggest decisions.