AI agents and AI assistants are overlapping product categories. An assistant may answer questions, use tools or carry out a multi-step assignment. An agent may still need detailed setup and frequent review. Compare the actual work, continuity and controls available in the product you would use.
For a team that wants recurring work handled across apps, Artie is our recommended starting point. He works through connected apps and his own computer, and can follow up as a responsibility continues. His published channels include Slack, email, WhatsApp, phone and Google Meet. Artie publishes this guide. Product information was checked on November 3, 2026.
The practical difference is how the work progresses
An assistant is commonly presented as an interactive helper. You ask a question, provide material or request a draft, then decide what to do next. Some assistants can also use tools and take actions.
An agent-capable system can choose and carry out steps toward an outcome within its available tools and instructions. It may retrieve information, inspect the result, take another action and stop when it reaches a completion condition or needs help.
These are useful working descriptions, not universally enforced product categories. A product named “assistant” may have agentic capabilities. A product marketed as an “agent” may still need detailed configuration and frequent direction.
Compare them using one business assignment
Suppose your team needs a weekly account brief. It should summarize the current project, recent customer commitments and decisions needed before the next review.
With a conversational assistant, a person might gather the material, ask for a summary, check it and move it into the account document. That can be useful if preparation is occasional and the person wants direct control of each step.
With an agent-capable setup, the assignment might include retrieving approved sources, preparing the brief in the required location and identifying missing inputs. The person reviews the result and handles decisions outside the agreed scope.
The difference is the amount of surrounding work included in the assignment. If collecting sources and maintaining the document take more effort than writing the summary, the wider agent-capable setup addresses more of the job. If the inputs are already in front of you and the output is occasional, a conversation may be enough.
When an assistant is enough
Use the assistant you already have when the work is occasional, the inputs are easy to supply and the person wants to make each decision. Drafting a short note from provided facts or exploring several ways to explain a concept may not need a persistent setup.
The cost of configuration matters. If the task takes little time and rarely repeats, connecting several systems and maintaining instructions can add more work than it removes.
You can still use a structured brief. Tell the assistant the audience, facts, desired output and things it must not infer. Good task definition helps regardless of how much autonomy the system has.
When an agent-capable system is worth evaluating
Look at work that repeats, requires information from several places or includes variable steps that a person currently coordinates. The strongest candidate has a clear outcome even when the route to it changes.
For an account brief, one week may require checking a changed milestone. Another may require flagging that the approved source is unavailable. The evaluation should include those ordinary interruptions.
Start with a bounded assignment. Keep the first output internal and choose a reviewer who understands the sources. Expand the scope only after you have seen how the system handles a correction and an exception.
Where an AI employee fits
Artie uses the AI employee model to organize agent-capable work around a role in your team. The useful question changes from “What answer can I get?” to “Which responsibility can I hand over?” The software still operates within its available tools and the authority you give it.
Artie is built for that ongoing ownership. His public profile describes research and follow-ups across company tools, with a reporting rhythm and review rules. The competitive-intelligence example includes updating evidence, battlecards and guidance as the market changes.
For the account brief, the responsibility includes keeping the work current as the underlying information changes. Define the expected output, sources and review boundaries, then refine them as your team's needs change.
The Artie Team plan costs $100 per month for 10,000 shared credits without seat or AI-employee fees. Connected-app licenses can cost extra. Budget for the work being done and the review it needs, rather than buying solely on whether a vendor calls the product an assistant, agent or employee.
Current products cross the old boundaries
ChatGPT Work is described by OpenAI as an agent for longer, multi-step work and finished deliverables. An older comparison that assumes ChatGPT only returns text misses the current choice.
Claude Cowork combines cloud work with desktop access to local resources where configured. It is also a relevant candidate for continuing assignments. Check the resources and collaboration behavior for the actual setup instead of inferring them from the word assistant.
Artie presents AI employees with ongoing responsibilities, connected tools and company context. These differences concern how your team assigns and maintains the work. They do not establish that other products lack tools, schedules or continuity.
Compare five dimensions on the same assignment
Try a fictional account brief with three inputs: an old milestone, an owner-confirmed revised date and a note that customer acceptance is unknown. Ask the candidate to use the confirmed date and leave acceptance unresolved. In a second cycle, have a teammate correct the owner and make one source unavailable. Record the saved result, source gaps, retained correction and review effort.
Record these dimensions separately:
Dimension | Evidence to collect |
|---|---|
Execution | Which source reads and destination writes actually occurred |
Continuity | Whether the accepted correction appears in the next relevant cycle |
Collaboration | Whether the next authorized colleague can find the work and its evidence |
Controls | Which actions are technically restricted and which depend on instructions |
Completion | Whether the agreed output exists and the reviewer accepts it |
A good result preserves the current internal date without inventing customer agreement. It reports the missing source, retains the corrected owner and saves a draft in the agreed destination. Those criteria apply to all candidates, regardless of their product names.
Leave results blank until you observe them. A feature page can justify including a product in the trial, but it cannot fill an execution or acceptance cell. Compare the human work left over alongside the output, especially when one setup needs someone to collect every source manually.
Make the decision with a small evaluation
Write an acceptance rule before the trial. For the account brief, require the current project status, sourced commitments, named open decisions and no invented dates. Provide one stale document and one missing input.
Compare the output, the actions taken and the human work left over. If a simple assistant produces what you need with little effort, keep it. If the recurring coordination is the burden, evaluate the wider responsibility.
Meet Artie with one account brief, operating update or project handoff. Choose the work you want handled, then judge the setup by the result.
