Prompt: AI agents are running into the limits of access

AI agents are beginning to do more than help people complete individual tasks. They are increasingly being built to act on their behalf, working across applications, pursuing broader goals and interacting with other companies' systems.

The shift has become harder to miss over the past few weeks. Meta's Muse can carry out tasks on users' behalf across websites and connected services. Meta has since expanded Muse to small businesses, letting it connect with tools including Shopify, QuickBooks and Slack and take on broader goals across the software owners use to run their businesses.

OpenAI followed with Dots, always-on agents designed to pursue goals in the background across connected applications. Microsoft has introduced its own digital teammate for enterprise teams. And this week, Google joined the trend with a Gemini workplace agent that can use business context to conduct work across applications.

Taken together, the launches point to a larger change in how people may interact with software. Instead of moving between applications themselves and using AI for help along the way, users may increasingly give an agent an objective and let it navigate those systems for them.

But Meta is already discovering one complication with that model: The systems an agent needs to use don't necessarily have to let it in.

Amazon has blocked Muse from making purchases on its site, saying Meta didn't arrange access in advance and raising concerns about how the agent identified itself and handled customer information. Shopify has taken the opposite approach, partnering with Meta to support Muse purchases through Shop Pay. The dispute exposes a challenge that could become more important as agents take on more work. Their usefulness depends not only on what they can do, but also on whether the websites, applications and businesses they need to interact with are willing to accept them.

That kind of delegation requires more than increasingly capable models.

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