Multi-agent AI: What It Is and Why Creativity Should Care
The Dawn of a New Era for Creative Work: How Multi-Agent AI Systems Are Revolutionizing Advertising
Discover how multi-agent AI systems are transforming advertising creation: how they work, use cases, advantages, and limitations.
Why Multi-Agent AI Systems Herald a New Era for Creative Work
Gartner predicts that by 2028, 33% of enterprise software applications will incorporate agentic AI. This evolution isn't just a technical shift; it's also opening up new possibilities for creative professions by changing how they design and produce content. For agencies, studios, and marketers, multi-agent AI systems are like a new virtual team of artificial intelligences, capable of analyzing, planning, deciding, and acting together to streamline workflows and free up time for human creativity.
Multi-Agent AI: A Technology Inspired by Collective Systems
What Is a Multi-Agent System ?
A multi-agent AI system is a collection of specialized artificial intelligences that cooperate with each other to analyze a situation, plan actions, execute tasks, and monitor results in order to achieve a common goal.
How Does a Multi-Agent System Work ?
A multi-agent system operates much like an organized team. It all starts with perception: each agent collects the information it needs, whether it's audience data, project history, or technical constraints. Next comes planning, where the agents communicate to find the best strategy. This can be seen, for example, in Amazon's logistics warehouses, where hundreds of robots coordinate their routes to optimize storage and order fulfillment.
Once the strategy is defined, the agents move to the execution phase: each one performs its mission, whether it's producing a report, generating a recommendation, or triggering an action. Finally, a "controller" agent provides supervision: it checks the consistency of the results and adjusts if necessary. In short, a multi-agent system can be seen as a decentralized orchestration where multiple intelligences work in parallel, each in its own role, but always in coordination toward the same objective.
Use Cases in Creative Work
In a creative context, a multi-agent system can already intervene at key stages of a project. For instance, one agent can help organize a brief by categorizing essential information. Another can track the progress of deliverables and flag potential delays. A third can assist with managing approvals or monitoring different versions. These interventions don't replace human supervision, but they reduce time wasted on manual coordination and improve the overall process flow. Creative teams can then focus more on their value-added tasks: ideation and creation.
Augmented Creation and Workflow
According to Business Insider (March 2025), several major companies like ServiceNow, Salesforce, SAP, and Intuit are already experimenting with AI agents capable of automating complex processes within their workflows, from customer support to data management. While these cases primarily concern the wider business world, they pave the way for similar uses in the creative field.
Platforms like Jasper already demonstrate the feasibility of this approach. By leveraging Webflow CMS, Jasper automatically generates personalized landing pages for ABM campaigns and automates repetitive tasks such as writing emails, social media posts, or blog drafts (Webflow, Jasper.ai).
When applied to the creative sector, this logic of orchestration by AI agents could simplify the management of complex projects. Take the example of a multi-format creation: a main video, a series of visuals for different digital platforms, and a printed version. One agent could distribute tasks among specialized modules, another could automatically adapt certain elements to the required formats, and a "controller" agent could verify consistency with the brand's visual identity. These interventions don't replace aesthetic or strategic choices, but they lighten the technical workload. The result: more time to refine the creative idea and less time lost on operational management.
Advantages for Creatives
- Time Savings: Automation of repetitive tasks (versioning, reporting, archiving).
- Fluidity: Better coordination on complex projects.
- Rich Insights: Multi-source analysis (audience, trends, performance).
- Augmented Creativity: More room for human ideation and innovation.
“Multi-agent systems are efficiency catalysts, not human substitutes.” — Cognizant, 2024
Limitations and Points of Caution
- Data Dependence: If the data is biased, the agents will be too.
- Technical Complexity: Implementation requires a robust architecture.
- Essential Human Supervision: Final creative decisions must remain human-led.
As they stand, multi-agents are powerful for organizing and optimizing, but not for inventing a campaign idea from scratch.
Conclusion: Toward Intelligent Co-Creation
Multi-agent AI systems represent a natural evolution of AI in business. For creatives, they are not a threat but an opportunity to work with specialized "virtual collaborators" that streamline logistics and amplify the impact of ideas. In 2025, agencies that know how to integrate them will see a new era of intelligent co-creation emerge: the human retains creative leadership, while multi-agent AI optimizes implementation.
FAQ – Multi-Agent AI and Creative Work
How does a multi-agent AI system work?
It brings together several specialized agents that analyze, plan, act, and monitor each other to achieve a common goal.
Are there already concrete examples of multi-agents?
Yes. They are used in logistics (Amazon robots), cybersecurity (IBM), and in platforms that automate certain content workflows.
What advantages do they offer to creatives?
They reduce the time spent on coordination and repetitive tasks, provide precise insights, and allow more room for ideation.
What are the current limitations for creative work?
The results are highly dependent on the provided data or briefs, human supervision remains essential, and the technology is still young.
Can multi-agent systems already be used in a creative agency?
Yes, but mainly through experimental tools or those integrated into large platforms. Their adoption is still in the pilot phase.
How do multi-agents differ from classic AI tools for creatives?
Unlike tools that perform a single task (generating text, editing an image), multi-agents coordinate multiple stages of a project. They act as a virtual team that streamlines the workflow without replacing human creativity.
