The right AI tool depends on the job you want to finish. Start with an assistant for a task you supervise, a workflow for repeatable steps across apps, or a local model when you need to control where inference runs. Add an agent's freedom to choose actions only when the task needs it.
At a glance
- Start with one output you can check.
- Compare total cost, access and maintenance.
- Use existing software when it already solves the task.
Which route fits your task?
| Your situation | Start here | First thing to check |
|---|---|---|
| You need help writing, analysing or planning, and can supply the inputs yourself. | An AI assistant | Can you check the answer against the original material? |
| The same information moves between the same apps every week. | A defined automation workflow | What happens when a field is missing or an app stops responding? |
| The next step genuinely changes according to what the system finds. | An agent with limited tools and permissions | Which actions must wait for your approval? |
| You want inference on equipment you control. | A local model and suitable software | Do any connected tools, searches or plugins still send data elsewhere? |
New to the distinction? Read what an AI agent is before choosing a platform.
Choose by the work you want to do
Draft a client report
Bring together approved figures, calculate changes in a spreadsheet, and ask AI to draft a short explanation. A person checks the sources and approves the report. Start with our client reporting workflow and its fictional example.
Connect the apps you already use
Write down the trigger, the apps involved and the final output before comparing platforms. Our Make versus n8n guide explains how to compare usage costs and the responsibility for maintaining your setup.
Use AI on your own computer
Check your available memory, the models you need and whether local performance is acceptable. Read running AI on a Mac and Ollama versus LM Studio versus Jan.
Two examples of a sensible first choice
A two-person agency writing ten monthly updates: start with a spreadsheet and an approved AI assistant. Keep the source figures and output together. Automate the handoff only after a few runs show that the report is useful and checking it takes less time than writing it.
A business moving hundreds of enquiries between apps: map the trigger, required fields and review queue first. A fixed workflow may be enough to classify and route requests. Add an AI step for a defined judgement, such as suggesting a response, while the account owner retains approval.
Ask these five questions before subscribing
- What output counts as success? Describe one deliverable, such as a checked draft report, rather than "automate marketing".
- What does it need to read or change? Separate access to source data from permission to send, delete or publish.
- Who will maintain it? Include the time needed to repair connections, review changes and handle exceptions.
- What will a normal month cost? Include platform usage, model usage, hosting where relevant, and human review.
- Can your current software already do enough? An existing reporting dashboard, spreadsheet or scheduled export may solve the problem.
Do you need an AI agent at all?
Not for every task. If a formula, a checklist or a fixed sequence of actions produces a reliable result, start there. An agent becomes useful when choosing the next action requires judgement, but that flexibility also creates more behaviour to test.
What should you try first?
Choose a task with a clear source of truth, a small amount of non-sensitive test data and an output you can review before anyone relies on it. Browse practical workflows or download the free reporting starter kit.
For more detail, see AI agent costs in the UK, AI agents and UK GDPR and the full tools archive.