The question is no longer whether your agency uses AI, but which agents it rolls out. The most important ones cover the recurring work from briefing checks and brand safety to costing.
The trick isn't the latest AI model; it's that the agents run on your agency's knowledge, are shared across the team and know which client is which.
We'll show you eight agents and how to start tomorrow. 🤞
What is an AI agent?
An AI agent is more than a chat model. It has a fixed job, knows its own context and skills, is connected to the right tools and carries out concrete steps of work.
In short: a chat model answers, an agent works (for you).
With a normal chat, you prompt from scratch every time. The knowledge of what a good result looks like sits in your head and it's gone the moment someone else takes over the task.
An agent flips that around. You define it once: the task, the context, the skills, the connected tools and a fixed output format. After that it runs repeatably, on demand or automatically, and delivers the same quality every time.
What advantages do AI agents have over a simple LLM subscription?
An LLM subscription gives everyone the same general-purpose model. An agent is built specifically for your workflows, knows your agency context, is connected to the relevant tools and — above all — can be shared across the team.
A chat subscription for everyone is a good start, but it stays generic: everyone prompts on their own, the wheel gets reinvented over and over, and no one makes sure client data stays cleanly separated. An agent picks up exactly where a general-purpose model stops.
At a glance — agent instead of subscription:
- Built for your workflow — tailored to concrete agency cases instead of generic answers.
- Knows the agency context — clients, projects, guidelines, personas, capacities.
- Connected to your tools — so it does real work instead of just producing text.
- Shareable across the team — build it once, everyone works at the same quality.
Which tasks can AI agents take on in an agency?
In brief: Anything that eats up a lot of time, is repetitive and has a clear result — deliberately not your creative core work. That's exactly where an agent takes the legwork off your plate without replacing the idea.
The rule of thumb for a good agent candidate: the task recurs often, relies heavily on sifting through data and context, and has a clearly defined output format. When that's true, an agent saves noticeable time — and you put it into the jobs that are actually fun.
Typical examples: checking incoming briefings, checking assets against brand guidelines, costing proposals, pulling together references for your website, or researching the competitive landscape for a pitch.
and now for the main event…
Which AI agents does every agency need in 2026?
In brief: Eight agents cover the recurring agency work — sorted along the path of a project: competitor, case and costing (new business), briefing, persona and strategy support (project start), plus brand safety and planning (delivery). We developed these together with awork users from real agency cases.
The 8 agents along the agency workflow:
- Competitor agent: researches the competitive landscape and comparable campaigns for the pitch.
- Case agent: pulls relevant references for your website and pitches from completed projects.
- Costing agent: calculates the proposal from the briefing based on your rate cards and capacities.
- Briefing-check agent: turns any client input into a checked, complete briefing.
- Persona agent: evaluates ideas and drafts from the perspective of the client persona.
- Strategy-support agent: moderates and supports your own strategy process methodically.
- Brand-safety agent: checks assets against brand, voice and design before they go to the client.
- Planning agent: thinks through the whole resource plan whenever a deadline shifts.
Three of them are worth a closer look, because every agency can roll them out straight away:
Briefing-check agent
A client sends a briefing — as a Word doc, a chaotic email, a voice note, it doesn't matter. The agent checks it automatically: What are the requirements? What goal should be achieved? Do we have the skills and the capacity for the timeline — and did the client even give one? It scans the content, flags the critical points, creates your re-briefing and drafts the email for any open questions.
Brand-safety agent
Keeping every colour code, every piece of wording and every edge case in your head is a lot to ask — and clients aren't amused when something slips through. The brand-safety agent checks your assets against tone of voice and design guidelines before they go to the client. You start it manually or wire it automatically into your project flow, as soon as a task moves into review. The best part: it can run across all your clients, each with its own stored context, and only accesses the guidelines it's actually meant to check.
Persona agent
Your personas live centrally in awork Docs. Just throw the agent a campaign idea for a client — or even a finished hook line for a social asset. It gives you feedback from the perspective of the predefined audience. Where you used to have to work out manually which criteria mattered for which ICP, the agent takes that over — and you put your time into strong assets that don't talk past the target audience. If a persona changes, you update it once; from then on the agent uses the new version.
How do you get started with AI agents?
In brief: With a shared base the whole team works from and where all your context lives. Without that base, every agent is a lone wolf — with it, the agent taps into your agency knowledge centrally.
An agent is only as good as the context it runs on. Sure, you can drop documents into the project folders of LLM models — but in the day-to-day of an agency that rarely gets maintained regularly, and out-of-date context leads to useless results.
So it's better to keep everything in one place: in awork. That's where your entire project management lives, along with team capacities and the info on your clients and projects. The agents then tap into your individual agency knowledge centrally — and that's also how they know which client is which.
[.b-testimonial]Context is ultimately the core building block and the key prerequisite for a successful AI rollout.[.b-testimonial]
How to start, concretely:
- Build the base — maintain projects, clients, guidelines and capacities centrally in awork.
- Pick a recurring workflow — the briefing check is the ideal entry point.
- Start the agent and share it — begin small, roll out across the team, improve together.
Which AI agents are other agencies using?
In brief: Almost every agency uses AI, but only 16% are truly AI-ready — most prompt and chat, while rolled-out agents are rare. We develop our agents together with awork users; the briefing-check agent in particular is a highlight that gets a lot of use.
Because we build these agents together with our awork users, we know the real pain from the day-to-day of an agency — and we quickly see which agents genuinely catch on in everyday work. The briefing-check agent is one of those: it's the first one many agencies put to use, because it hits a pain that every agency knows.
That the step pays off is also borne out by the numbers: around 28% of agencies that have rolled out AI increase their margin; only 13% see it drop. The difference doesn't come from more prompting, but from a few shared agents running on shared context.
Conclusion
2026 won't be decided by the smartest model, but by the structure behind it. An agent isn't a chat model: it's built for your workflow, knows your context, is connected to your tools and is shared across the team. That's exactly what gives you back time for the jobs that are actually fun — and three agents you can roll out today: briefing check, brand safety and persona.
Recap:
- An agent works, a chat model answers — the advantage lies in context, tools and shareability.
- Good candidates: tasks that eat up a lot of time, are repetitive and have a clear result.
- Getting started works through a shared base — in awork sits the context the agents run on.
👉 Want to see agents in action?
[.b-button-primary]Here's your way to the demo[.b-button-primary]
FAQ
Do AI agents replace jobs in the agency?
The data is reassuring: around a third of agencies plan AI-related headcount cuts, but 20% are hiring, and for almost half nothing changes (ifo Institute, awork AI rollout webinar). The agents take on the legwork, not the creative core work.
How do agents stay GDPR-compliant?
By only using models hosted in the EU in a GDPR-compliant way, with data not used for training purposes. In awork, many models run on the same EU infrastructure as awork itself; you also choose yourself which models are approved.
When will the AI agents be available in awork?
The agent features will be available shortly; the first templates and an agent library for direct import are part of that. But you can already see them in action in a demo.
