Service
AI Workflows
Automate the repetitive analysis, keep a human on the decisions
A lot of marketing work is the same steps over and over: pull the numbers, tidy them up, spot what changed, write it into a report. I build AI workflows that do that groundwork for you, then hand it back so you can check it and decide what to do. Less time copying data between tabs, more time on the calls that actually move the account.
What an AI workflow actually is
An AI workflow is a set path a task follows, with AI doing the reading, sorting and drafting inside it. Think of it like hiring a very fast assistant who never gets bored of the boring bits. You tell it where the data lives, what a finished report looks like, and what to watch for. It handles the rest and shows you the result.
It is not a chatbot you have to prompt from scratch each time. The steps are set up once, tested, and then run on demand or on a schedule. You get a consistent output every time, not a different answer depending on how the question was phrased.
- Pull live figures straight from Google Ads, Meta, GA4 and other platforms
- Draft the report in your format and voice, ready for a human to check
- Run on a schedule or on demand, with the same steps every time
Automated reporting
Reporting is the most obvious win. The data already exists in each platform. The slow part is collecting it, lining up the date ranges, working out the comparisons, and writing it into something a client can read.
A reporting workflow connects to the platforms directly, pulls the current period and the one before it, and drafts a clean summary with the headline metrics up top and the detail underneath. You read it, sanity-check it against what you know about the account, and send it. What used to be a half-day of copy-paste becomes a review job.
- Live platform data instead of stale exports
- Month-on-month and year-on-year comparisons worked out automatically
- Consistent structure across every client, every month
Campaign analysis and flagging problems
The harder value is in analysis. AI is good at scanning a lot of numbers and pointing at the ones that look off: a spike in cost per lead, a campaign that has quietly stopped converting, spend drifting to a search term that never buys.
A workflow can check the whole account against its normal range and surface only the things worth a look. You are not reading every line yourself. You are looking at a short list of flags with the context attached, then deciding whether each one is a real problem or just noise.
- Anomaly flagging: cost, conversion and spend shifts outside the usual range
- Search term and audience review to catch budget going to the wrong place
- Plain-language notes on what changed and where to look first
Summarising and sorting at scale
Some jobs are just too big to do by hand. Reading hundreds of search terms, grouping ad copy by theme, sorting feedback or reviews into topics, tagging which queries show buying intent. AI handles this kind of sorting quickly and consistently.
The point is scale. A person can categorise fifty things well and five thousand things badly, because attention runs out. A workflow keeps the same standard across the whole list, then gives you the summary rather than the raw pile.
Where a human still makes the call
AI does the gathering, sorting and drafting. It does not decide to pause a campaign, shift a budget or send a client the report. Those stay with a person, and that is on purpose.
AI can be confident and wrong. It can miss context it was never told about, or read a one-off event as a trend. So every workflow I build ends with a human check before anything goes out or changes in an account. You get the speed of automation and keep the judgement where it belongs.
- AI drafts and flags. A person approves before it ships or changes anything
- Nothing is paused, adjusted or sent without a human saying yes
- The workflow shows its working, so you can trace any number back to its source
By the numbers
Illustrative examples to show the shape of the work. Not client data.
Time on monthly reporting
Where the AI workflow helps
The detail
| Task | Done by hand | With an AI workflow |
|---|---|---|
| Collecting the data | Log in to each platform, export, tidy | Pulled live from every platform at once |
| Working out comparisons | Line up date ranges by hand | Prior period and last year done automatically |
| Writing the report | Type it up from scratch each time | Drafted in your format, ready to check |
| Spotting problems | Scan every line yourself | Only the flags that fall outside normal |
| The decision | You make it | You still make it |
| Job | Good fit for a workflow? | Why |
|---|---|---|
| Monthly reporting | Yes | Clear inputs, set format, repeats every month |
| Anomaly flagging | Yes | Pattern-spotting across lots of numbers |
| Sorting search terms or feedback | Yes | High volume, consistent rules |
| Budget and bid changes | Human decision | Needs judgement and account context |
| Sending client-facing work | Human check first | A wrong number sent is hard to unsend |
| Strategy and creative direction | Stays with people | AI supports the thinking, it does not own it |
Common questions
Does an AI workflow replace the marketer?
No. It takes the repetitive groundwork off your plate: pulling data, drafting reports, flagging what looks off. The decisions, the strategy and the client relationship stay with a person. The point is to free up time for the work only a human can do, not to remove the human.
Is my data safe?
Data handling is set up to fit how your business already works, using approved connectors and access you control. I keep client data isolated, and I will always talk through where data goes and how it is stored before building anything. If a tool or setup does not meet your standard, we do not use it.
How accurate is it?
The data pulls are as accurate as the platforms they come from, because the numbers are read directly rather than retyped. The AI-written parts, the summaries and the flags, are drafts. That is why every workflow ends with a human check. AI can be confidently wrong, so nothing goes out unreviewed.
Do I need to be technical to use this?
No. The technical setup is my job. Once it is running, using it is usually as simple as opening the finished draft, reading it, and approving it. I build the workflow around how you already work, not the other way around.
What if the AI gets something wrong?
That is exactly why the human check exists. The workflow shows its working, so you can trace any figure back to its source and catch anything that looks off. Nothing is sent to a client or changed in an account on the AI's say-so alone.
How long does it take to set one up?
It depends on the job. A reporting workflow for a handful of accounts is quicker to stand up than something that spans many platforms and clients. I start with the task that is eating the most time, get that working and tested, then build out from there once you can see it earning its keep.
Talk it through
Tell me which task is eating your week, and I will show you what an AI workflow could take off your plate.
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