AI Agents Are Starting to Handle Your Chores, With a Big Privacy Catch

A new class of artificial intelligence tools is moving beyond simple chatbots into something that works on tasks after you’ve stopped talking to it. OpenAI, Meta and Google have each released or expanded “AI agent” products in recent weeks, including OpenAI’s Dots and ChatGPT Work, Meta’s Muse and Google’s Gemini Spark.

Unlike a standard chatbot that answers a single question and waits for the next prompt, an agent can keep monitoring something, such as a flight price or an upcoming subscription renewal, and report back later or complete multi-step tasks on its own.

OpenAI’s Dots feature gives users a persistent cloud-based assistant that remembers ongoing work between sessions. It is rolling out to eligible ChatGPT Pro, Business Premium and Enterprise subscribers, and OpenAI says Dot usage will not count against plan allowances during this introductory period. ChatGPT Work, built directly into ChatGPT, is designed for longer research and multi-step jobs and is becoming available on paid plans including Plus, Pro, Business, Enterprise and Edu.

Meta’s Muse offers a free tier with usage limits and a paid option for heavier use. Google’s Gemini Spark is available to Google AI Pro and Ultra subscribers in supported regions and can run scheduled workflows using connected Google services.

What These Tools Can Actually Do

Practical uses being floated for these agents include tracking airfare or hotel prices until they drop below a target amount, scanning an inbox to flag messages that need a response while leaving drafts for the user to approve, and keeping tabs on bills, subscription renewals and paperwork deadlines so nothing slips through unnoticed.

Other suggested uses include building a weekly dinner plan and grocery list from a household’s food preferences, maintaining a running list of home maintenance tasks, following up on pending requests such as refunds or contractor estimates, and watching for openings in restaurant reservations, medical appointments or sold-out products.

In each case, the design intent is for the agent to do the repetitive watching or drafting work while a human retains final say over anything consequential — sending an email, booking a reservation, canceling a subscription or spending money.

The Access-and-Control Tradeoff

The tradeoff with these tools is straightforward: the more useful an agent becomes, the more access to personal accounts, calendars and inboxes it typically needs. That access comes with real exposure, since giving a tool read access to email or financial accounts creates more opportunity for something to go wrong, whether through a misfire by the AI itself or a security vulnerability in the service.

OpenAI allows users to prevent new ChatGPT conversations from being used to train its models, through settings that keep conversations in a user’s history without feeding them into the training process. OpenAI’s Temporary Chat feature keeps a conversation out of saved history, though OpenAI says it may retain those chats for up to 30 days for safety purposes. Connected app permissions can also be reviewed and revoked under account settings.

OpenAI says Dots can follow rules dictating which actions it may take on its own versus which require user input. Meta says Muse is designed to ask for approval before certain critical actions, including purchases and sending emails.

Where to Draw the Line

A recommended approach is to grant permissions incrementally: let an agent read and summarize information first, then allow it to prepare drafts, and only later consider giving it authority to take a limited action — with approval requirements left in place for anything involving money, legal matters or medical decisions.

Users are also advised never to enter passwords, PINs or two-factor authentication codes into an AI chat window, and to use a service’s official secure connection method instead when one is available.

The underlying distinction offered for deciding whether a task warrants an agent at all is whether the job truly ends once the AI responds. A one-time question, such as planning tonight’s dinner, doesn’t need an agent. A task with an unfinished tail — watching a price, waiting on a reply, checking for an opening — is where these tools are being positioned as genuinely useful, provided the person giving the instructions keeps control over what happens next.