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AI & Innovation Automation

1 minute read

Multi-agent, multi-modal AI: The Rise of Digital Colleagues

Look at a collection of job descriptions and it quickly seems as if organizations are all searching for a “jack of all trades.” That creature doesn’t exist, though that won’t come as news. Yet even in the development of popular AI models – ChatGPT, Copilot, Claude – it was long assumed that it might be possible to build a tool that can do everything: read, write, search, summarize, generate images, and perform calculations, to name just a few examples.

Users, too, tend to appreciate such an all-in-one solution. You can delegate work-related tasks to it, but you can just as easily use the model to design a poster for the local korfball club or even to act as a therapist for relationship issues. The fact that users just as readily enter sensitive company data as they do their own personal confessions is a topic for another blog. Apart from these security risks, however, such an all-encompassing model can actually never deliver optimal results.

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AI agents as the perfect team

This year, then, seems to be the year of multi-agent and multi-modal AI. These involve dozens or perhaps hundreds of smaller, specialized models that often communicate and work together autonomously. Basically, these agents work like a perfect team in an organization should. Without a team leader watching all the time, everyone takes his or her role in carrying out a task. Each team member also knows at the right moment to transfer tasks to a colleague when he or she has more knowledge and experience to do so.

Organizations are thus rapidly moving from using a few individual AI agents to a "swarm" of AI agents. In customer service, for example, one agent specializes in summarizing telephone calls, a second can search the manual database, a third filters the right information from the CRM system, a fourth knows how to extract order and payment information from an ERP system, and a fifth does a compliance check so that sensitive data is not inadvertently leaked. The information gathered can be explained to the customer by a chatbot.

Sheep with five legs

In this way, multi-agent systems can take over many tasks: logistics planning, QA reporting, supply chain optimization or tracking and visibility of healthcare records. Agents no longer consult only text- and number-based sources, but increasingly process and generate images, audio and sometimes video simultaneously. Thus, true multi-modal agents are emerging. Market analyst IDC expects an average organization to deploy some 100 to 200 AI agents as digital colleagues within its operations by 2028.

However, there are still many open questions surrounding the reliability and security of such multi-agent, multi-modal systems. Also looming is the danger of "AI proliferation": more and more AI agents become active in the organization, leading to a lack of oversight and governance. Therein lies a task for the enterprise architect to merge the agent systems into a manageable platform. Then the organization itself has actually created a digital "sheep with five legs.

kronkel

 

May 12, 2026

Thijs Doorenbosch

Elke organisatie barst van de kennis en is uniek door de eigen cultuur en interessante mensen. Dat geldt voor kennisinstellingen, gevestigde bedrijven, startups en scale-ups. Mijn ervaring is dat die mooie aspecten van de organisatie vaak vooral gezien worden binnen eigen teams of afdelingen en door een kleine groep klanten en andere betrokkenen. Maar hoe zorg je dat ook de wereld daarbuiten er enthousiast van wordt? Publicaties in de vorm van interviews, achtergrondartikelen of blogs scheppen vertrouwen in de organisatie bij externen en laten zien waar de expertise te vinden is. Intern creëren zulke publicaties een hechter ‘familiegevoel’ en trots op de eigen organisatie. Dit soort interessante verhalen vertellen aan een groter publiek – intern of extern – is al meer dan 30 jaar mijn passie.

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