What is agentic AI, and when is it worth using?

Give it an outcome, not just a question

“Which emails need a reply?” asks for an answer. “Review this week’s messages, make a reply list and draft the three most urgent replies” asks for several steps toward a result.

Agentic AI means AI can choose steps, use available tools and adjust as it works. An AI agent is the system doing that work. It might search, read files, edit a document or use a connected app. A chatbot can contain agent features too; the labels are not a clean dividing line.

A fixed automation follows a set recipe. An agent has more freedom to decide what to do next. That can help when the work changes, but it also makes results less predictable.

What would I use it for?

Task	Work you could delegate	Result to review
Back from holiday	Find relevant mail, identify open requests and draft responses	A catch-up list and reply drafts
Research a purchase	Find options against your requirements and compare source information	A shortlist with links and trade-offs
Prepare a team update	Read approved notes and assemble the current status	A draft update with unresolved questions
Maintain a website	Edit content or code, run checks and prepare a release	Changed files and a reviewable result

These are task designs. The app still needs the appropriate tools and permission. A general Copilot chat can help plan these jobs; direct inbox actions require the relevant Outlook experience. Our holiday email example explains that distinction.

Pros and cons

The upside: less copying information between steps, a deliverable you can inspect, and the ability to adjust the plan when new information appears. It is especially useful when you can describe a result clearly but the steps take a while.

The downside: a wrong assumption can carry into later steps. Tools can fail, access can be missing, and retries can take time or consume usage. Checking the result is still work. For a quick rewrite, an ordinary chat may be easier than setting up an agent.

What does it cost?

Cost	What to look for
App access	Your existing plan may include some agent work; other features need a subscription.
Usage	Credits or included allowance can be consumed by a long task and its retries. API billing is separate from consumer subscriptions.
Connected services	Hosting, paid data or another app may have its own charge.
Your time	Connecting accounts, explaining the job and reviewing output are part of the cost.

A concrete price reference: OpenAI lists Plus at US$20/month, with Work and Codex sharing usage, and Pro from US$100/month as checked on 25 October 2026. That is a subscription example, not a per-task agent price or an assurance of every feature. A custom agent has no universal monthly price: it depends on its model, tools and how often it runs.

For a first go, use an app you already have and a small task. If a tool offers a spend limit, set one before an open-ended job. “Research these three options once and stop at a draft” is easier to budget than “keep finding better options.”

An example brief you can adapt

“Use these approved meeting notes to make a one-page team update. Include decisions, owners, dates and anything still unresolved. Check each item against the notes. Save a draft for me; don’t send it. If a needed detail is missing, ask me. Stop when the draft is ready.”

Here the result is clear, the source is limited, and there is a useful point to hand it back. This brief is an example, not a recorded run.

Start with one responsibility

Try one bounded job, inspect what happened, then decide what else to hand over. If you want help choosing an OpenAI experience, see ChatGPT, Work, Codex and Dot. For a task you can try with ordinary chat, organize your meeting notes.