AI Tools

About the AI Tools category

What counts as an AI tool

This category covers software built around machine learning and large language models: standalone assistants such as ChatGPT, Claude and Gemini, AI writing and editing tools, meeting assistants that transcribe and summarise calls, image and video generators, and the AI features increasingly embedded inside the apps teams already use. We draw a deliberate line between products whose core value is the AI and ordinary software that has bolted an "AI" label onto a minor feature — the former belong here, the latter rarely do.

Common use cases

In practice, businesses reach for AI tools to remove the slow, repetitive parts of knowledge work: drafting and rewriting content, summarising long documents and meetings, researching at speed, answering routine customer questions, and turning rough notes into something usable. The most valuable deployments tend to be unglamorous — shaving minutes off tasks that happen dozens of times a day — rather than the headline-grabbing demos.

Who this category is for

These guides are written for founders, marketers, support teams, operations leads and solo professionals who do a lot of writing, research or repetitive analysis and want to do it faster without hiring. You do not need a technical background; what you need is a clear sense of which tasks are eating your time, because that is what decides whether a given tool will actually pay for itself.

Key buying considerations

Price per seat is only the start. The questions that matter more are how the vendor handles your data — in particular, whether your inputs could be used to train its models — how reliably the tool performs on your real tasks rather than cherry-picked examples, and how cleanly it fits the software you already run. We also weigh the generosity of free tiers for evaluation and the stability of the vendor, since this is a fast-moving market where tools appear and vanish quickly.

How we evaluate AI tools

We sign up and use each tool on representative tasks before forming a view, read the official pricing and data-handling documentation, and cross-reference verified user feedback to catch behaviour that only shows up at scale. Because privacy is a real concern with AI, we give meaningful weight to a vendor's data terms. The full process is documented in our review methodology.