## Big AI Companies Are Giving Teams of Smart Helpers to Businesses

Multi-agent systems are the new big thing in AI. Companies like Anthropic and OpenAI are building AI agents that don't work alone—they work as teams to solve big problems together. Think of it like having multiple helpful assistants that can divide up work and finish projects much faster than before.

Anthropicjust released Claude Opus 4.6 with multi-agent teams, which is like giving marketing teams a whole crew of AI helpers that can talk to each other and work on the same project. These agents can help with research, write documents, make presentations, and plan campaigns. The company says these agent teams are really good at quality work, fast speed, and keeping things safe for businesses. This is not just about making things faster—it's about doing bigger, more complicated jobs that one AI alone could never handle.

## Companies Are Building Tools So Everyone Can Use AI Agents

Making AI agents easy to use is the next big battle. Anthropic is adding new features to something called Cowork that let teams customize their own AI agents for different jobs. Marketing teams can set up agents to write copy. Legal teams can set up agents to read contracts. Customer support teams can have agents that answer customer questions. The cool part is that teams don't need to know computer code to do this.

Meanwhile, OpenAI launched Frontier, a new service that helps big companies build their own AI agents and connect them to the programs they already use. This is OpenAI's answer to compete with Anthropic for business customers who want AI agents built specially for their needs. Both companies know that businesses don't just want a smart AI—they want AI that fits into their actual work.

## Making AI Agents Even Smarter With Real Business Information

Connecting AI agents to company data makes them way more useful. Snowflake and OpenAI made a huge deal—a $200 million partnership—to make OpenAI's AI agents work right inside Snowflake's data system. This means AI agents can look at all a company's real information and make better decisions based on actual facts. For marketing, this means AI agents can personalize messages to customers using real data about who they are and what they like.

When AI agents have access to governed data (information that's been checked and organized), they can do way more. They can analyze customer behavior, suggest personalization ideas, and help with reporting. This partnership shows how AI agents are moving from experiments to real business infrastructure.

## Marketing Teams Are Already Using AI Agents in New Ways

Reddit is testing AI agent search, and it's already helping advertisers make more money. When people search on Reddit, they get answers from the community, and AI is making those answers better and easier to understand. For advertisers, this opens up new places to show their ads inside conversations and search results. Reddit's advertising business jumped by 70% in the last quarter, partly because of AI tools that help ads work better and people buy from them.

The big picture is that multi-agent systems are taking over different parts of marketing. Agents can now handle research, writing, designing, planning campaigns, and even measuring if ads are working. But here's the real challenge: most companies say they're using AI but can't prove it's making them more money. Only about 4 in 10 marketers can confidently show that their AI is giving real results.

## The Hard Part: Making This Actually Work in Real Businesses

The tough part isn't building smart AI—it's getting companies to actually use it. OpenAI is hiring lots of people like deployment managers and solutions architects to help big companies move from trying out AI in tests to actually using it in real work. Many AI projects fail because the technology is too complicated to connect with existing systems, data is messy, or teams don't know how to change their work to use AI properly.

To make AI agents work, businesses need to redesign how teams do their jobs, how they check that work is being done right, and how they measure success. Companies are learning that governance matters as much as the technology itself. The winners will be the companies that figure out how to build AI agents into their actual work processes, not just use them as side projects.