The five applications
| Application | What it yields |
|---|---|
| Content | Faster first drafts and ideas |
| Research | Market and competition mapped faster |
| Automation | Repetitive work out of your hands |
| Analysis | Interpret data faster |
| Visibility | Get listed in AI search and answer engines |
Start small
Choose a specific, time-consuming task and automate it with Get AI automations. Measure the effect before you expand. You can build up the broader use of AI for companies in your company step by step.
Common mistake
The biggest pitfall is using AI to produce mediocre content in bulk. That just weakens your visibility: Google and AI reward quality, not volume. Use AI to create good content faster, not to create more bad content.
AI and your visibility
The application with the most direct link to customers is discoverability: make sure your brand shows up in AI responses via Generative Engine Optimization (GEO). That builds on your regular what is SEO and a strong content strategy.
Which task do you automate first?
The one that recurs often, whose output you can verify and whose input is recognisable. That is a sharper test than which task takes the most time, because a slow task with unpredictable output mainly produces rework when you add AI.
| Question | Good sign | Bad sign |
|---|---|---|
| How often does the task recur? | Weekly or more | A few times a year |
| How recognisable is the input? | Always the same shape | Different every time |
| Can you verify the output? | At a glance | Only after a long review |
| What does a mistake cost? | You correct it before publishing | It goes straight to a client |
Score well on all four and the task is suitable. Score badly on the last row and a human belongs in the loop before anything goes out.
What do you measure to know whether it works?
Time per completed task, not the number of pieces produced. Judging AI on volume measures exactly the wrong thing: more output under the same quality control only means more mediocrity gets through.
- How much time the task took before and after, including the review afterwards.
- How much output went through unchanged, and how much had to be rewritten.
- How many errors were only found after publication.
- Whether the result still sounds like your business.