Moving beyond a single-task view

With UK organisations under mounting pressure to boost productivity and automate end-to-end workflows, specialised multi-agent systems are ideally suited to the challenge. By rethinking and redesigning processes around these multi-agent systems, organisations become increasingly adaptable and agile, transforming long, manual cycles into minutes or seconds. 

Take the issue of complex supply chains – common to many enterprises. Stages of this process can rely on decades-old, highly manual action: long cycles, siloed teams, endless handoffs. They are also subject to innumerable variables, from material resource, to weather, to technical failures causing delays.

Agentic AI systems can completely transform a supply chain end-to-end. Multiple AI agents can operate together, each contributing specialised expertise, communicating with each other, and collaborating like a real team across disciplines and locations. The system can collectively re-route shipments, flag and manage risks, and adjust buyer expectations – all in seconds.

When highly specialised agents are coordinated across teams and embedded alongside humans, measurable impact scales quickly.

Orchestrating the multi-agent advantage

Multi-agent systems can reshape the very core of how enterprises design their operations and deliver value. But getting multiple agents to work together, and alongside humans, takes careful orchestration. There is an art to joining tasks together and adapting processes for an agentic-empowered workforce.

 It’s vital to have carefully designed programmes in place, with clear roles, robust guardrails, and reliable coordination mechanisms. To integrate AI effectively into existing workflows, new tools and frameworks are emerging to create and manage specialised AI agents across departments, enabling them to plan, collaborate, and hand off work safely.

This coordinated approach marks an evolution in how we think about enterprise architecture. Instead of relying on fragmented, bolted-on systems and manual orchestration, organisations can now embed intelligence directly into their workflows.  A deep understanding of the business, its weaknesses, and greatest opportunities for driving efficiency is essential – there is no copy and paste approach.

Fuelled by this shift in enterprise thinking, 2026 is set to be the year of integrated multi-agent operations. Yet delivering tangible ROI and measurable productivity gains across the enterprise hinges on addressing a critical gap: building the trusted, AI-ready foundations needed for widespread adoption.

Trust in multi-agent transformation

Enabling multi-agent orchestration requires more than technology: organisations must establish the right enablers, from workforce models and governance frameworks to strong data infrastructure.

This means prioritising platforms that enable multiple AI agents to coordinate safely within robust security frameworks capable of protecting and monitoring distributed systems. Because even despite the visible benefits of moving past single-task AI assistants, trust remains the critical barrier to multi-agent adoption.

In 2024, 43% of executives expressed confidence in fully autonomous AI agents for enterprise applications. In 2025, that figure has dropped to just 22%, and 60% do not fully trust AI agents to manage tasks and processes autonomously. When scaling to multiple agents working in concert, this trust deficit becomes even more pronounced.

Enterprises are shifting to a new operating model, whereby AI agents propose and execute, while humans supervise and govern. In this new paradigm, oversight becomes a design principle, and transparency in multi-agent decision-making becomes a strategic imperative.

When multiple agents coordinate across departments like finance, supply chain, HR, customer service, visibility into how they collaborate and make decisions is essential. Employees and management alike need to understand how agents hand off work, resolve conflicts, and execute processes together. They must ensure they have the expertise in the data, system integration, and engineering on hand. Only when this human-AI chemistry is mastered, and when people can confidently supervise and guide the agents’ actions, can the trust question be fully addressed.

Generating waves of value

Organisations that prioritise trusted orchestration as the foundation for multi-agent operations will unlock the competitive advantage these systems deliver: measurable productivity gains, reduced costs, and the ability to move from manual cycles to autonomous operations in minutes or seconds.

Once these foundations are in place, multi-agent orchestration can generate continuous waves of value unmatched by the isolated AI deployments we’ve seen up to now. The next decade won’t be defined by incremental digital upgrades, but by a profound shift toward autonomous, adaptive, and self-optimising systems that form the fabric of modern business. 

Steven Webb is the UK chief technology & innovation officer at Capgemini.