The technology sector's push to integrate artificial intelligence into enterprise operations has given rise to a significant trend: using AI to orchestrate workflows rather than simply automate isolated tasks. This evolution, building on the agentic AI hype, marks what Forrester describes as "a clear shift from task-level automation to process orchestration for enterprise scale." In its April 2026 report, The adaptive process orchestration software landscape, Q2 2026, the analyst firm notes that the market is maturing around agentic and AI-first approaches. The emphasis is now on blending adaptive AI behavior with deterministic workflows, not entirely replacing existing structures.
The new paradigm: Orchestration over automation
For years, businesses have used robotic process automation (RPA) and workflow engines to streamline repetitive tasks. However, these tools operated in silos, lacking the intelligence to adapt to changing conditions. The emergence of large language models and generative AI has opened the door to more dynamic systems – agents that can reason, plan, and take actions. Yet deploying such agents in complex enterprise environments requires careful orchestration. Forrester's research highlights that software providers are consolidating automation tools into orchestration backbones that combine process intelligence, modeling, execution, monitoring, and data foundations. Governance, auditability, and hybrid execution models supporting event-driven automation and human-in-the-loop are critical.
Camunda, a key player covered in the Forrester report, held its annual conference in Amsterdam from 19-21 May 2026, drawing 1,100 attendees eager to learn about agentic AI for business process reengineering. CEO Jakob Freund opened the event by stressing the need for safe customer data agents that require high levels of human approval and deterministic behavior. He called this "the power of agentic orchestration," enabling organizations to use agentic AI safely. Freund referenced Forrester's observation that every process in an organization is legacy, designed at a time when AI did not exist. AI, he argued, completely redefines how organizations operate.
ProcessOS: A new operating system for agentic workflows
During the keynote, Camunda CTO Daniel Meyer introduced ProcessOS, described as "an agentic operating system" that reengineers business processes and continuously optimizes them for the AI era. He demonstrated how Camunda internally used ProcessOS to redesign its quote-to-cash process. "It is one of our most critical business processes, and there were quite a few inefficiencies, manual handoffs, spreadsheets," Meyer said. After reengineering with ProcessOS, Camunda not only improved cycle time and efficiency but also reduced error rates. CFO Clemens Morgenroth quantified the impact: the reengineered process is freeing 6,000 person hours, based on the fact that quote-to-cash previously took five hours per deal.
Barclays: Agentic AI for customer onboarding
Barclays is among the enterprises exploring business process reinvention using Camunda's platform. Lily Wang, CIO for wholesale client onboarding and group financial crime at Barclays, explained that "ProcessOS tackles the real reason AI adoption stalls in large enterprises. We can't build tomorrow's process using only what we know today. Transformation stalls." In a presentation, Gautam Verma, head of financial crime core platforms and client due diligence technology, detailed how the bank uses deterministic and agentic orchestration to streamline customer due diligence. "The complexity of the customer due diligence process can get very involved and can take months to do," Verma said. "There's a lot of sequential handles between people and teams that do different functions on this journey, and the evidence gathering can be manual in many cases."
Barclays developed three agents: one for data collection from multiple sources, a data intelligence agent that assesses policies and procedures for effective due diligence, and a third agent to handle the policy procedures themselves. The orchestration layer across this workflow is deterministic. "We've got multiple systems at play during this whole journey – multiple handoffs for internal systems and internal teams – and we needed to orchestrate it completely end-to-end to achieve the goals that were set for us," Verma added. The aim is not just to streamline but to "fundamentally reimagine how we move around the customer onboarding process."
The role of deterministic orchestration in agentic systems
A key theme emerging from the conference is that agentic AI cannot operate in a completely unstructured manner. Enterprises require guardrails to ensure compliance, security, and reliability. Deterministic orchestration provides those guardrails by defining the sequence of steps, approval points, and fallback procedures. For example, in financial services, any AI agent handling customer data must adhere to strict regulatory requirements. By combining deterministic workflows with AI-driven decision-making, organizations achieve both flexibility and control. This hybrid approach is exactly what Forrester's report advocates: blending adaptive AI behavior with deterministic structures rather than replacing them entirely.
The market for adaptive process orchestration software is expanding rapidly. Vendors are positioning their platforms as the central nervous system of the enterprise, connecting AI models, legacy systems, data lakes, and human workers. Camunda's ProcessOS is one example, but others like Pega, Appian, and ServiceNow are also investing heavily in agentic capabilities. The competitive landscape is shifting from simple automation to intelligent orchestration that can learn and evolve over time.
Challenges and considerations for adoption
Despite the promise, adopting agentic orchestration is not without challenges. Organizations must first map their existing processes to identify where AI can add value without introducing undue risk. Data quality and integration remain significant hurdles; AI agents are only as good as the data they access. Furthermore, change management is critical – employees must trust AI agents to make decisions and be willing to adapt to new workflows. The success of initiatives like Barclays' customer onboarding relies on close collaboration between business stakeholders, IT, and compliance teams.
Another consideration is cost. While agentic AI can reduce manual effort, the infrastructure required – including GPU clusters, large language model deployments, and orchestration platforms – can be expensive. However, the long-term benefits in terms of efficiency, reduced error rates, and improved customer experiences often justify the investment. As CFO Morgenroth noted, freeing 6,000 person hours from a single process can dramatically lower operational costs.
Looking ahead, analysts predict that agentic orchestration will become the default mode for enterprise software. The shift from task automation to process orchestration represents a fundamental change in how businesses operate, moving from rigid, predefined workflows to adaptive, AI-driven processes that can respond to real-time events. Companies that fail to reinvent their business processes risk being left behind in an increasingly competitive landscape.
In summary, the reinvention of business processes through agentic AI orchestration is not a luxury but a necessity. As Freund put it, "AI completely redefines how organizations operate." The tools are now available to reengineer processes from the ground up, combining the best of deterministic control and AI-driven adaptability. Early adopters like Camunda and Barclays are already reaping the benefits, and the rest of the enterprise world is taking notice.
Source: ComputerWeekly.com News