Enabling the AI Company of the Future

Camunda is a Business Reporter client.

Agentic AI is reshaping how businesses operate – from decision-making to customer experience to internal operations. But while enthusiasm is high, results remain uneven. Gartner predicts that more than 40 per cent of agentic AI projects will be scrapped by 2027. Even the most promising initiatives stall when early success fails to scale.

What’s often missing isn’t more AI. It’s the architecture to coordinate how agents fit into business processes, facilitating end-to-end context for the AI to yield better, more consistent results, while also monitoring, reporting and providing visibility of the process – including the agent. Process orchestration is that architecture.

Process orchestration provides the connective tissue between people, systems (including AI agents) and devices – ensuring that decisions, actions and outcomes flow seamlessly across end-to-end business processes. As agents become more embedded in daily operations, the need for this co-ordination grows more urgent.

Why process orchestration matters

As AI agents gain traction, their ability to act independently opens new possibilities. But that autonomy also introduces risks. Without oversight, agents can deviate from business objectives, misinterpret intent or create unpredictable outcomes. These issues compound in regulated environments where transparency and auditability are non-negotiable.

Process orchestration ensures agent actions are aligned, traceable and compliant. It manages context across steps, coordinates handoffs and provides the infrastructure needed to scale from prototype to production.

It also solves one of the biggest challenges facing enterprise AI: execution. According to the 2025 State of Process Orchestration and Automation report, 85 per cent of IT leaders say they struggle to scale and operationalize AI effectively. Too often, AI remains siloed – tied to individual tools or teams, without integration into core business processes. Process orchestration connects these efforts, ensuring AI outputs drive meaningful business results.

It’s all about governing how work gets done across different (AI) systems, people and devices – leading to compounding value and a faster pace of innovation.

 Choosing the right process orchestration approach

There’s a wide spectrum of human and machine work in the modern enterprise. Some automated business processes require strict compliance and adherence to preset conditions. Others benefit from adaptability and reasoning. Most land somewhere in between, where organizations use dynamic elements such as AI agents with deterministic (or predefined) elements of a business process.

Deterministic process orchestration is the most traditional approach to process automation and orchestration. Processes are modelled in advance with predefined logic, conditions and decision models. Deterministic orchestration offers a high degree of predictability and control. It’s auditable by design and works well in environments where rules are fixed, compliance is required and outcomes must be repeatable.

Dynamic process orchestration leverages large language models (LLMs) to dynamically determine which tasks should be executed, the sequence of task execution, the routing of workflow paths and the handling of edge cases and exceptions. While this approach allows for more flexible and adaptive processes that can respond to complex scenarios, process orchestration is rarely, if ever, fully dynamic.

Agentic process orchestration is a hybrid approach to process orchestration that incorporates both deterministic and dynamic elements. It offers the structural reliability of deterministic workflows and the adaptive decision-making of AI agents. In this model, agents operate within a structured process but retain enough autonomy to make decisions, manage subprocesses or adapt based on real-time context.

Building durable systems for change

Rather than hardcoding decisions or relying on disconnected tools, leading organizations are building fully orchestrated business processes designed to evolve. This includes integrating AI at appropriate points, layering in human oversight where needed and capturing process design in standard formats such as Business Process Model and Notation (BPMN) and Decision Model and Notation (DMN).

Agentic orchestration makes this possible. It supports innovation while preserving stability and compliance. It helps companies move faster without losing control. And it allows teams to focus on outcomes instead of managing exceptions.

To build the AI company of the future, process orchestration must become a strategic capability. It’s essential for adopting AI innovations while reducing risk – and turning AI from isolated effort into enterprise-wide value.

by Jakob Freund, CEO, Camunda

Header image credit: iStock- 2167882376