Work-Day AI: The Current Offerings

Platforms

Claude Cowork

Anthropic. Ready with caveats. Ready for a small team that works from files and email and is willing to keep approvals on. Watch usage limits on long jobs and pick the plan tier accordingly.

Cowork is a desktop app (Mac and Windows, with web and mobile access in beta) that takes a task and works across your folders, calendar, email, and the web until it is done, producing real files: spreadsheets with formulas, slide decks, formatted documents. It can run on your machine, where it only touches folders you have explicitly connected, or in Anthropic's cloud, where a session keeps going after you close the laptop. Scheduled tasks (hourly, daily, weekly) run in the cloud by default. Approvals come in three modes, from "ask me every time" to "just go," and an add-on browser lets it use websites that have no proper integration.

What to like

What to plan for

ChatGPT Work

OpenAI. Ready with caveats. Ready if you already live in ChatGPT and want the widest set of app connections. Set a credit cap on day one and keep approvals on until you understand the cost curve.

ChatGPT Work (launched July 2026, replacing the older "agent mode") is OpenAI's long-task agent. On web and mobile it runs in OpenAI's cloud; the Mac and Windows desktop app can also run locally with access to your files and desktop apps, plus a built-in browser. It plans first, lets you approve the plan, then executes, with approval cards before risky actions (sending messages, modifying files, purchases). The connector catalog is enormous (OpenAI says over 1,400), and there is a Small Business program bundling Dropbox, Shopify, Intuit, Slack, Atlassian, and Wix. Scheduled and event-triggered tasks (a new Gmail message, a Slack post) are supported.

What to like

What to plan for

Grok Bot

xAI. Wait. Interesting architecture, but the shared-machine design, opaque memory, and lack of business plans make it a research project for now, not a business tool.

Grok Bot gives you one or more named "bots" that live on a persistent Linux computer in xAI's cloud. Each bot can sign into your software, browse the web, run commands, and coordinate with your other bots in a group chat. Because the computer persists, logins, files, and memory carry over between sessions, and bots can run on schedules while your laptop is closed. It ships with roughly 220 opt-in plugins (Google Workspace, Slack, Microsoft 365, Salesforce, Notion, GitHub) and falls back to a real browser when no plugin exists.

What to like

What to plan for

Gemini for Workspace, Spark, and Workspace Studio

Google. Wait (agent), caveats (automations). If you already pay for Workspace, turn on Studio for simple, low-risk automations. Treat the full agent as not yet shipped for business use.

Google's offering comes in two layers that are easy to confuse. Workspace Studio is a no-code automation builder bundled into Business and Enterprise Workspace plans: describe a workflow in plain language ("when a client emails an invoice, summarize it and file it in this Drive folder") and Gemini builds the trigger-and-steps flow. Gemini Spark is the actual agent: a 24/7 assistant that runs multi-step tasks across Gmail, Drive, Docs, Sheets, and the web, using either your own Chrome or a cloud browser that keeps working when you are offline.

What to like

What to plan for

Microsoft 365 Copilot and Copilot Cowork

Microsoft. Ready with caveats. Ready for Microsoft 365 shops that have someone to administer it. If you have no IT person, the enable-and-govern step is the real cost.

Copilot is the assistant built into Word, Excel, Outlook, and Teams; Copilot Cowork (generally available since June 2026) is the agent layer on top. Give it a long task and it works in a cloud sandbox across your email, meetings, and files, showing a plan with checkpoints so you approve changes before they are applied. It inherits your existing Microsoft 365 permissions, audit logs, and sensitivity labels, which is the strongest governance story of the five. Scheduled prompts run from Teams and Outlook, and Microsoft lets you choose among several underlying models, including Claude and GPT.

What to like

What to plan for

What about running one yourself?

If you have heard of "local models" and wondered whether you could keep all of this in-house, the honest answer is: partly, and only if someone on your side enjoys the plumbing.

We run gpt-oss-20b, OpenAI's open-weight model released under the Apache 2.0 license, on a small Linux box in our office and on our own laptops. It needs about 16 GB of memory, costs nothing per call, and never sends a byte outside the building. We use it for the work where that matters: nightly health analysis and weekly summaries of our own systems, semantic search across months of operational history, and first-pass estimates on internal project cards. Nothing customer-facing, nothing that needs the reasoning depth of the frontier models, and nothing we would want to explain to a client if it had left our network.

What you give up is everything the five cards above package for you: the connectors, the approval gates, the scheduler, the audit trail. You assemble those, or someone does it for you.

Our verdict. Wait, unless privacy is the constraint that decides the question, or you already have the person. For a specific, well-bounded workflow that must stay in-house, a local model is a good answer, and it is one we set up for clients. If you think local inference might be right for part of your workflow, we can help with that.

What changed since August

Until recently, "using AI at work" meant typing into a chat window and copying the answer somewhere else. The current generation is different. You give it a task ("reconcile these two spreadsheets and write me a summary," "watch my inbox and draft replies to vendor questions"), it opens your files and apps, works through the steps, asks permission at the risky moments, and hands back a finished spreadsheet, document, or email draft. Every major vendor now sells a version of this, and they have converged on a similar shape: a sandboxed computer (on your machine or in the vendor's cloud), a catalog of app connectors, an approval prompt before anything irreversible, and a scheduler so tasks can run while you are away.

The differences that matter for a small business are not the model's IQ. They are where your data goes, how the bill behaves, how much can go wrong without you noticing, and whether the product is actually available on a business account today.

Five questions before you adopt any of them

  1. Where does the work happen, and is that acceptable for this data? Cloud execution is convenient and lets tasks run overnight, but it means client files, inbox contents, and logins are handled on someone else's computer. Decide per workflow, not per vendor.
  2. What is the bill going to look like in month three? Flat seats (Claude, Google) are easy to budget. Credit-metered agents (OpenAI, Microsoft) can be cheaper or much more expensive depending on how often people use them. Set caps before rollout.
  3. What happens when it reads something malicious? An agent that reads your email and browses the web can be tricked by text hidden in a web page or a message ("prompt injection"). Every vendor here acknowledges the risk; none claims to have solved it. Keep approvals on for anything that sends, deletes, or pays.
  4. Is it actually available on a business account? Two of the five most-hyped agents (Gemini Spark, Grok Bot) are not on business plans as of this snapshot. Check the plan, not the press release.
  5. Who administers it? Microsoft's and OpenAI's business tiers assume an admin who enables features, sets spend, and reviews audit logs. If that person is you, budget the time.

The readiness ratings above are Auth/Technic's judgments as of the snapshot date, made from the vendors' own documentation and independent reporting, not from vendor marketing.