Replacing repetitive delivery tasks for agencies.

Every agency I've worked with has the same pattern: the work that fees are billed against is interesting, scoped, and well-priced. The work that fills the rest of the week is a long tail of admin, status reports for clients who barely read them, brief processing, competitor monitoring, repetitive content production, internal reporting for the partners. None of it bills. All of it is non-optional.

It's the work that quietly grows as accounts grow. A new £8k/month retainer adds two hours of standing admin a week. Three new accounts is half a day. You can't hire your way out of it, the cost lands directly on margin, but you also can't stop doing it.

This is the work AI implementation is best at: documented, repeatable, structured outputs that humans can review faster than they can author from scratch.

1. Weekly client reporting, data pulled from your project tool, GA/Plausible, ad platforms and any CRM, narrative drafted in your house voice, partner reviews and ships. Lives in the workflow automation lane.

2. Brief processing, turning client emails, calls and Loom recordings into structured project briefs the delivery team can actually work from. Standard structure every time. Lives in the AI agents lane.

3. Competitor research, automated pipelines that pull competitor messaging, content drops, pricing changes and ad creative on a schedule. Useful for client decks, useful for your own positioning. Lives in the data extraction lane.

4. Content production, turning a single brief into the asset family (long-form, social variants, newsletter, image-prompt for the designer). AI drafts, account lead approves.

The audit ranks these against your specific accounts. Reporting usually wins on first-build ROI.

Every system I build for an agency keeps the account lead approving anything that goes to a client. AI handles the assembly, the drafting, the data pulling, the parts of the job that should never be a senior's time. What ships to the client is still your work; what feeds into it stops being.

Each workflow integrates with the project tool you already use, Notion, ClickUp, Asana, Linear, Monday, Airtable. Data comes from your existing reporting (GA4, Plausible, ad platforms, CRMs), drafts land in the project tool or directly in the account lead's inbox for approval. No new platform to teach the team.

Versioning is first-class. Every draft the AI produces is logged. When a client questions a number or a phrasing, you can trace it.

A 14-person digital agency with 12 monthly retainer clients. Before: Fridays consumed by status report assembly across the team, roughly 6 senior hours weekly. After: reports drafted automatically Thursday night from the project tool plus analytics, account leads spending 15 minutes each Friday morning reviewing and personalising before ship. Build time: 4 weeks. Stack: Claude API, ClickUp API, GA4 API, Node.js.

Another: a brief-processing pipeline for an SEO agency. Before: 2 hours of senior strategist time per new project translating client emails and discovery calls into a brief the delivery team could use. After: 20 minutes, Claude drafts from the transcript and email chain, strategist sharpens the angles. Build time: 3 weeks.

Numbers vary by agency shape and stack. The pattern repeats: senior time off the admin and back onto the strategy.

A good fit if:

• You have 5+ monthly retainer clients (the volume justifies the build).

• Your team is spending visible chunks of senior time on assembly work, reports, briefs, recurring content.

• You already use one of the standard project tools (Notion, ClickUp, Asana, Linear, Airtable).

• You're comfortable with AI drafting outputs that account leads review before they ship to clients.

Probably not yet if:

• You're a solo freelancer, the volume usually doesn't justify the build cost.

• Your work is 90% creative judgement (creative direction, brand identity from scratch). The AI lift is smaller.

• You're looking for AI to do client-facing work end-to-end without senior review. That's not what this is.

This page covers the agency angle. The broader practice is AI implementation — the audit, scoping, build and measure process I follow across every engagement, regardless of sector.

Worth reading: The 3 Workflows Every Agency Should Automate First.