For too long, businesses have failed to move beyond thinking about AI as a product; an assistant that sits at the side, helping users complete tasks and providing incremental improvements in productivity.
This narrow definition has limited its impact, limiting minor pilots to isolated use cases and preventing organizations from seeing the full operational potential of AI.
But that's changing. More and more business leaders are waking up to a new reality: AI is no longer an enabling technology. It is quickly becoming the operating fabric of modern businesses. We are seeing a decisive shift from single-task activities to autonomous, adaptive and self-optimizing systems based on multi-agent systems.
It's not hard to see why. When autonomous agents can understand intent, coordinate complex work, and optimize themselves over time, value virtually generates itself.
Accordingly, AI agents projected to generate $450 billion in economic value by 2028.. And yet, despite the obvious promise, our recent research shows that only 2% of organizations have deployed agents at full scale.
Going beyond a single task view
As UK organizations experience a growing need to improve productivity and automate end-to-end workflows, purpose-built multi-agent systems are ideally suited to meet this need. By rethinking and redesigning processes around these multi-agent systems, organizations become increasingly adaptable and flexible, turning long manual cycles into minutes or seconds.
Take, for example, the problem of complex supply chains that plague many businesses. The steps in this process may rely on decades-old manual processes: long cycles, disparate teams, endless handoffs. They are also subject to countless variables, from material resources to weather conditions and technical failures that cause delays.
AI agent systems have the potential to completely transform the entire supply chain. Multiple AI agents can work together, each bringing their own specialized expertise, communicating with each other, and collaborating as a true team across disciplines and locations. The system can collectively redirect supplies, flag and manage risks, and adjust customer expectations—all in seconds.
When highly specialized agents coordinate across teams and work alongside people, measurable impact scales quickly.
Multi-Agent Advantage Management
Multi-agent systems have the potential to change the very way businesses plan their operations and create value. But getting multiple agents to work together and with people, requires careful orchestration. There is an art to combining tasks and tailoring processes for empowered employees.
It is essential to have carefully designed programs with clear roles, strong barriers and strong coordination mechanisms. To effectively integrate AI into existing workflows, new tools and platforms are emerging to create and manage specialized AI agents across departments, allowing them to securely plan, collaborate, and delegate work.
This coordinated approach marks an evolution in the way we think about enterprise architecture. Instead of relying on fragmented, embedded systems and manual orchestration, organizations can now embed analytics directly into their workflows. A deep understanding of the business, its weaknesses and greatest opportunities for improvement is essential – no copy and paste approach here.
With this shift in enterprise thinking, 2026 will be the year of integrated, multi-agent operations. However, delivering tangible ROI and measurable productivity gains across the enterprise depends on closing a critical gap: building the robust, production-ready AI foundation needed for widespread adoption.
Trust in multi-agent transformation
Enabling multi-agent orchestration requires more than just technology: organizations must build the right enablers, from workforce models and management systems to a powerful data infrastructure.
This means prioritizing platforms that allow multiple AI agents to securely coordinate their actions within robust security frameworks that can protect and control distributed systems. Because even with the perceived benefits of moving away from single-task AI assistants, trust remains a critical barrier to the adoption of multiple agents.
In 2024 43% of executives expressed confidence in fully autonomous AI agents for enterprise applications.. In 2025, this figure will drop to just 22%, and 60% do not fully trust AI agents to autonomously manage tasks and processes. When scaling multiple agents working together, this trust deficit becomes even more pronounced.
Enterprises are moving to a new operating model in which AI agents propose and perform functions, while humans supervise and manage. In this new paradigm, oversight becomes a design principle and transparency in multi-agent decision making becomes a strategic imperative.
When multiple agents coordinate the work of departments such as finance, supply chain, HR, customer service, transparency in how they collaborate and make decisions is important. Both employees and management must understand how agents delegate work, resolve conflicts, and complete processes together. They must ensure that they have expertise in data, systems integration, and design. Only when the chemistry of humans and artificial intelligence is mastered and when people can confidently control and direct the actions of agents can the issue of trust be fully resolved.
Generating Waves of Value
Organizations that prioritize trust orchestration as the foundation of multi-agent operations will discover the competitive advantage that these systems provide: measurable productivity gains, cost savings, 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 have seen so far. The next decade will be defined not by incremental digital upgrades, but by a profound shift towards the autonomous, adaptive and self-optimizing systems that form the fabric of modern business.
Stephen Webb is UK Director of Technology and Innovation at Capgemini.
