The agency world is changing faster than ever before.
AI is present at every industry conference, in every newsletter, in every client conversation. And rightly so: the technology is transforming how agencies work, how they plan, and how they deliver projects.
What this means in concrete terms is something we experience daily in conversations with you. The level of implementation ranges from first prompt experiments to agencies that have built entire AI engineering teams and completely rethought their business model from the ground up. The full spectrum exists – and everyone is asking themselves the same thing: Are we on the right track?
Our thesis: The agencies of the future will consist of people with creative ideas who develop strategies, orchestrate projects, and deliver results. And of AI and agents that support them – in creation, production, strategy development, and planning. That is precisely the foundation we want to build. And you already have a head start: because the basis for this already lies in awork.
Why AI without project data fails in agencies
[.toc-name]AI fails without data[.toc-name]
AI needs context – real, up-to-date data about projects, teams, and processes. Without this context, AI remains a useful experiment. With it, it becomes a genuine part of your value chain.
This context already lives in awork: projects, processes, skills, capacities, calculations – and via awork Connect, often your client voices as well. Everything in one place, GDPR-compliant on EU servers. This is the foundation on which AI can truly work meaningfully – and the decisive difference from a tool stack that you have to populate with context manually.
awork AI, Agents and MCP: the 3 AI building blocks at a glance
[.toc-name]3 AI building blocks[.toc-name]
awork AI – AI chat directly in awork
You already know awork AI: ask in natural language, get a data-driven answer straight away. No need to explain context, no prompt engineering – the AI knows where you are in awork and accesses your project data directly.
We are actively working to further expand the quality and use cases: more precise answers, more actions, more processes that awork AI can handle independently.
[.b-button-primary]More on awork AI[.b-button-primary]
awork Agents – AI agents for the entire agency (Coming soon)
This is the area we are currently working on most intensively – together with the first agencies from our community. awork Agents are AI agents that independently take over agency processes and roll them out consistently across the entire team.
The difference from awork AI: agents act, they don't merely respond. An agent can automatically check availability for a new project enquiry, analyse similar projects from the past, suggest an initial project plan, and notify the right people – without anyone having to manually trigger each step.
Together with pilot partners from agencies with 20 to several hundred employees, we are developing awork Agents for perfectly tailored workflows.
awork MCP – your agency data in every LLM
The other side of the coin: not bringing AI into awork, but bringing awork data into the AI tools you already use. With the awork MCP Server, you can access your project data directly in Claude, GPT, or other LLMs – without opening awork. Capacity analysis, client reporting, summarising project status: directly from your awork data, without manual exports, without copy-pasting.The awork MCP Server is already available – and we are continuously investing in expanding the integration further.
[.b-button-primary]More on the awork MCP Server[.b-button-primary]
AI Readiness: why it is the strongest hgappiness lever in agencies
[.toc-name]AI Readiness[.toc-name]
According to the Agency Happiness Report 2026, agency employees who perceive their structures as AI-ready have a happiness score of 7.3 – nearly twice as high as those in agencies without this perception (score: 4.0).
AI readiness is therefore the strongest happiness lever in the entire report – stronger than salary, stronger than leadership.
[.b-testimonial]AI readiness isn't about licences and tools – it's about whether the agency demonstrates that it is actively shaping change. Clear processes, defined roles, a strategic embedding of AI into the value chain: all of this signals future viability and strengthens work happiness.[.b-testimonial]
We are actively investing in the AI functionalities of awork – with awork AI, awork Agents, and the MCP Server. And we want to walk this path together with you. Not because we have all the answers, but because we want to find out together what the agency model looks like in the age of AI.
Curious about what the industry thinks about AI, work happiness, and the future of the agency?
[.b-button-primary]Read the Agency Happiness Report 2026[.b-button-primary]
FAQs
What is awork AI and how does it differ from other AI models?
awork AI knows your project data – capacities, time tracking, ongoing projects – and responds directly from this context. ChatGPT and other generic LLMs do not have this agency context.
What are awork Agents?
awork Agents are AI agents that independently take over agency processes – for example, automatically checking availability for new project enquiries, analysing similar projects, and suggesting initial plans.
What is an MCP Server and what do I need the awork MCP Server for?
MCP (Model Context Protocol) allows external data to be integrated into AI tools such as Claude or ChatGPT. With the awork MCP Server, you can access your project data directly in the LLM tool of your choice – without any manual export.
Is my agency data GDPR-compliant with awork AI?
Yes. All data is stored on EU servers and is not used to train AI models. Admins can also deactivate AI features.
Why is AI readiness so important according to the Agency Happiness Report 2026?
Employees in AI-ready agencies achieve a happiness score of 7.3 – nearly twice as high as in agencies without this perception (4.0). This makes AI readiness the strongest happiness lever in the report, stronger than salary or leadership.
