Agentic orchestration
Designed to take advantage of the emergence of agentic AI and agentic automation, agentic orchestration allows enterprises to coordinate, control, and optimize the work of a multitude of AI agents, robotic process automation (RPA) robots, and people across end-to-end agentic workflows and systems. This powerful, unified approach yields seamless collaboration between people, agents, and robots while maintaining trust, governance, and oversight across operations.
- What is agentic orchestration?
- What is the real power of agentic orchestration?
- What’s the difference between agentic orchestration and process orchestration?
- What are the capabilities and characteristics of agentic orchestration?
- What are the benefits of agentic orchestration?
- What are potential use cases for agentic orchestration?
- What challenges must agentic orchestration address in order to succeed?
- What does the future of agentic orchestration have in store?
What is agentic orchestration?
Agentic orchestration is a set of capabilities and technologies that allows enterprises to design, implement, operate, monitor, and optimize long-running agentic processes while managing them effectively at scale. While it includes traditional workflow orchestration capabilities like process modeling, business rules, design, and execution, it goes far beyond them by also incorporating process intelligence, AI-driven automation tools, agentic automation, and rules-based automation.
With agentic automation, enterprises can now:
Automate core, complex, and costly processes end-to-end by designing, executing, and managing cohesive long-running workflows that integrate different automated tasks and operations
Design and execute agent-driven processes that involve many different systems, apps, and technologies.
Orchestrate a hybrid workforce of people, AI agents, and RPA robots within well-defined processes that include clear guardrails and compliance with internal policies—minimizing human error and ensuring permissions are respected.
Leverage 360-degree, continuous AI-powered discovery to monitor and optimize processes over time.
Let’s dive into how agentic orchestration delivers these transformative agentic AI capabilities and what capabilities and technologies are required.
What is the real power of agentic orchestration?
Agentic orchestration is an advancement on traditional process orchestration. It’s a secure ecosystem of technologies and capabilities that allow AI agents, automation, machine learning, RPA robots, and people to work productively together in executing complex processes end-to-end. This approach creates a dynamic ecosystem that enables an organized sequence and cadence of activities, real-time collaboration and human-in-the-loop interventions, proactive problem-solving, smarter decision making, and streamlined execution.
At its core, agentic orchestration combines AI agents, UI and API automation, and human intervention to keep workflows running smoothly.
But the real power of agentic orchestration lies in its ability to unite cutting-edge technologies like generative AI (GenAI) and RPA to optimize workflows. GenAI brings natural language processing and decision making capabilities, while RPA bots handle high-volume, repetitive tasks. In supply chain management, this might mean AI agents forecasting demand while RPA bots adjust inventory systems in real time, minimizing disruptions and maximizing efficiency.
Ultimately, agentic orchestration transforms complexity into clarity, creating a cohesive system where every component works together to achieve overarching goals.
What’s the difference between agentic orchestration and process orchestration?
Put simply: process orchestration is about aligning people and automation across a workflow. Agentic orchestration goes beyond process orchestration to make sure AI agents can be part of that equation—with the right visibility, rules, and oversight to ensure they drive value without introducing risk.
Process orchestration is a technology focused on streamlining how work gets done across people, systems, and automation technologies. It is typically used to coordinate RPA automation, manual work, and business rules across different enterprise systems and business areas to make processes work faster, smoother, and more efficiently.
Agentic orchestration has all the capabilities of process orchestration, but it also introduces new technologies specifically designed to allow users to develop, govern, operate, and control agentic processes that involve AI agents, people, and robots. Agentic orchestration technology also introduces new governance layers, escalation logic, and safeguards to ensure that AI agents—which can autonomously make decisions, interact across systems, and adapt to changing conditions—can operate safely and effectively within defined boundaries. And it includes enhanced discovery, design, monitoring, and optimization capabilities that allow users to incorporate AI agents into complex, end-to-end processes and monitor and improve agents’ performance.
The technology includes expanded abilities to:
Model and design with industry-standard BPMN constructs
Implement integrated processes involving AI agents, RPA automation, human-in-the-loop interactions, API events, and advanced decisioning
Operate processes with a high level of control and performance measurement into specific instances as they progress through a process
Monitor execution of processes over time with analytics integrated into BPMN modules
Optimize using performance data as well as simulation and bottleneck detection tools
What are the capabilities and characteristics of agentic orchestration?
Agentic orchestration goes beyond siloed task execution, creating a comprehensive system where AI, automation, and human expertise work in sync to tackle even the most complex tasks. Here’s how it operates:
Collaborative systems
AI agents and orchestration platforms form the backbone of agentic orchestration. These specialized agents, whether focused on customer analytics or logistics, share insights and adapt to real-time changes, driving better decision making and operational agility across the board.
Process orchestration tools
Instead of relying on a single centralized engine, agentic orchestration uses integrated process intelligence to coordinate AI agents, RPA bots, and human contributors. It includes the ability to create, import, and edit business process modeling and notation (BPMN) 2.0 models to clarify and optimize IT processes’ efficiency. It also incorporates industry-standard decision model and notation (DMN) to add business rule tasks and manage decisions within processes.
Seamless integration
RPA and APIs act as the connective tissue between legacy systems and modern technologies. This integration allows data to flow effortlessly across platforms, ensuring every component works in harmony without silos or interruptions. In some cases, container orchestration with Kubernetes or integration with Microsoft services can further streamline cross-platform workflows.
Intelligent automation
Generative AI and large language models (LLMs) enhance the system’s ability to understand natural language and deliver smarter, faster solutions. Their full value comes from driving continuous improvement, optimizing business processes, and enabling organizations to respond quickly to change.
What are the benefits of agentic orchestration?
Agentic orchestration helps enterprises use all forms of AI—including AI agents—alongside RPA robots in a more efficient, coordinated way. It expands what’s possible to automate and enables smoother, end-to-end automation across critical business processes. It transforms how businesses manage complex workflows, takes full advantage of new agentic-driven possibilities, and ultimately drives better business outcomes. Here’s what the strongest and most robust orchestration solutions enable:
Orchestrating work across diverse systems and technologies
End-to-end processes are typically very complex and highly variable. They require seamless integration across multiple systems and workflows, along with flexible collaboration between robots, people, and AI agents. Agentic orchestration is the capability that dynamically connects the dots between all these constituents, data, software, and systems, forming cohesive workflows that facilitate scalability across entire processes. Orchestration technologies allow users to design and model complex, end-to-end workflows across these multiple systems and ecosystems to achieve business outcomes.
Orchestrating work across agents, robots, and people
Agentic orchestration effectively distributes work among AI agents, RPA robots, and people to work in sync efficiently and productively. Agents are deployed to work on complex and dynamic end-to-end processes that require adaptability, while predictable, structured tasks are handed off to robots. Meanwhile, human intervention can be included as necessary for review and confirmation of agent activities (human in the loop). This division of labor optimizes productivity and frees employees to focus on more strategic, impactful work. Agentic orchestration allows your people to focus on activities that drive growth. It allows IT teams, for instance, to focus on higher-value IT service initiatives.
Delivering agentic AI transformation
Agentic orchestration technologies allow users to deploy a diverse set of AI agents—possibly from a range of different providers—within a consistent framework. Users can orchestrate agentic actions in a well-defined process.
Executing and managing at scale in real time
Complex, highly variable processes don’t fit a prescribed path or run according to a pre-defined plan. Rather, one event often triggers other events, subprocesses, or tasks. Orchestration technologies therefore include event-sourced execution engines that can analyze and respond to situations in real time. These engines give enterprises the capability to run processes and instance management at scale. Moreover, these engines include the ability to fix, restart, modify, and manage versions.
Relatedly, agentic orchestration helps foster business resilience. It dynamically reroutes individual tasks, adapts to unexpected changes, and ensures critical operations continue running smoothly. This reliability safeguards customer trust and ensures service levels remain high, even during challenging times.
Providing process intelligence
The best orchestration technologies include capabilities to monitor and learn from real-time data. AI-powered discovery tools provide a real-time, 360-degree view of workflows, making it easier to pinpoint inefficiencies and bottlenecks and uncover opportunities for improvement. Continuous monitoring empowers organizations to anticipate roadblocks and address them proactively, keeping business operations running smoothly. What’s more, by continuously monitoring performance and using learning loops to address mistakes, organizations can proactively improve how AI agents operate—supporting systems that adapt and self-correct over time.
Providing built-in trust and governance
Orchestration technologies permit users to define business rules and guardrails with standard, easy-to-use frameworks (e.g., BPMN notation and DMN rules). They will include a trust layer as well as unified admin to improve compliance with enterprise policies and to make agents’ activities visible and controllable.
What are potential use cases for agentic orchestration?
By making it possible to leverage agents, robots, and people in automating core enterprise processes end-to-end, agentic orchestration makes a range of new high-ROI use cases possible. For example:
Cross-industry applications
Purchase-to-pay: Automates procurement from order placement to payment, cutting cycle times and boosting transparency.
Order-to-cash: Speeds up the entire journey from order receipt to payment, improving cash flow and customer satisfaction.
Accounts payable/receivable: Optimizes payment workflows to enhance financial accuracy and manage liquidity effectively.
Banking and financial services
Fraud detection and prevention: Automates workflows for real-time transaction monitoring and fraud alerts, enhancing security and reducing financial risk.
Regulatory compliance: Compliance workflows such as know your customer (KYC) and anti-money laundering (AML) are streamlined to ensure audits go smoothly and that all regulations are met.
Loan processing: The entire loan approval process—from document checks to final authorization—becomes more efficient, cutting down on manual tasks and shortening turnaround times.
Customer 360 view: Data is integrated across multiple departments to create a single, comprehensive view of each customer, enabling a more personalized banking experience.
Mortgage processing: Mortgage applications, underwriting, and disbursements are automated, speeding up approvals and reducing bottlenecks in the process.
Dispute resolution: Automating claim and chargeback tracking and responses simplifies the resolution process, making it faster and more transparent for both banks and customers.
Energy
Grid management: Automates load balancing and real-time grid monitoring to optimize energy distribution and prevent outages.
Asset lifecycle management: Inspection, maintenance, and upgrade processes are streamlined to keep critical infrastructure reliable and running efficiently.
Customer onboarding: Simplifies the steps for new customer connections, disconnections, and billing, resulting in faster service and greater accuracy.
Utilities
Meter-to-cash: Automates meter reading, bill generation, and payment collection to improve accuracy and reduce processing time.
Regulatory compliance: Ensures precise reporting and audits for both environmental and operational standards, helping reduce regulatory risks.
Workforce management: Optimizes how field technicians are scheduled and deployed, leading to greater efficiency and quicker service response times.
Telecom
Network operations: Automates fault detection, resolution, and performance monitoring so networks remain reliable and downtime is kept to a minimum.
Customer onboarding: Speeds up SIM activation, device setup, and service enablement, giving customers a smooth start from day one.
Billing and revenue management: Refines processes for billing adjustments, payments, and refunds, boosting accuracy and overall customer satisfaction.
Manufacturing
Order-to-cash: Automates order processing, invoicing, and collections to accelerate revenue cycles and reduce manual processes.
Supplier and inventory management: Optimizes supplier onboarding and inventory replenishment workflows to enhance supply chain efficiency.
Production scheduling: Automates scheduling adjustments in response to supply chain disruptions or demand fluctuations, ensuring optimal production flow.
What challenges must agentic orchestration address in order to succeed?
Agentic orchestration delivers remarkable value, but the technology and the design approach need to ensure that it can navigate a number of challenges. Here’s a breakdown of some of the biggest issues that agentic orchestration approaches must be capable of addressing:
Bridging legacy systems with modern workflows
Many organizations rely on legacy systems not designed to handle advanced technologies like generative AI. This makes it challenging for companies to maintain real-time data flow and seamless interoperability.
Take supply chain operations as an example: connecting legacy enterprise resource planning (ERP) systems to agentic workflows often requires custom APIs to ensure data flows seamlessly. The trick to addressing the issue of interoperability to ensure that the agentic orchestration capability has access to proven methods of handling legacy systems, such as RPA.
Data governance and privacy
Agentic orchestration thrives on data, but it must be able to manage the data that it uses and keep it safe and secure. This is especially important in highly regulated industries like healthcare or finance, where mishandling data can lead to expensive compliance violations and erode public trust.
Having access to robust data governance frameworks and tools is therefore critical. This includes encryption, role-based access controls, and regular audits. Incorporating explainable AI (XAI) can also enhance transparency, helping stakeholders understand how decisions are made and ensuring compliance with privacy regulations. It’s also important to put “fences” around both agents and robots—for example, limiting the data that an agent can have access to and/or use in modeling. Or, by using robots—who can be constrained to focus on gathering a very specific set of data and provisioned with end-point security—to do data extraction and processing in sensitive areas.
Mitigating LLMs’ issues such as bias and inaccuracy
Agentic AI systems are built around large language models (LLMs). While LLMs are what allow agents to understand and take action, they can also introduce bias, hallucinations, variations in answers to the same question posed at different times, and inaccurate answers and decisions.
To minimize these issues, agentic orchestration technologies should make it easy to bring people into critical decision making. Additionally, agentic orchestration should allow for consistent monitoring and checking of agents’ decisions against deterministic models. Whatever people or monitoring systems find—and the corrective actions they take—should be fed back into agents via learning loops.
Balancing costs and infrastructure investments
Deploying agentic orchestration can require upfront investment in automation platforms, infrastructure, and employee training. One way that agentic orchestration systems can mitigate these costs is to make it easier to identify high-impact use cases and map out the automation approaches and orchestration requirements. These early wins can fund broader initiatives.
That’s why agentic orchestration technologies should include robust AI-powered process, task, and communication mining, analysis, and mapping capabilities.
Strong security and resilience
The more interconnected a system becomes, the greater the risk of cyberattacks or operational disruptions. Compromised AI agents or bots could lead to data breaches or workflow manipulation, making security an essential focus. Therefore, agentic orchestration technologies should include strong cybersecurity protocols, such as encryption, multi-factor authentication, and continuous monitoring.
What does the future of agentic orchestration have in store?
Agentic orchestration is poised to redefine how businesses function, allowing AI systems to seamlessly collaborate while dynamically responding to changing conditions. With ongoing advancements in AI models, large language models, and agentic orchestration platforms, the possibilities are immense—elevating customer experiences, solving intricate real-world problems, and driving innovation into new territories.
Organizations that embrace agentic workflows will gain far more than operational efficiency. They’ll unlock smarter decision making, greater adaptability, and a significant competitive edge in an increasingly AI-powered world. As this technology matures, agentic orchestration will transition from being a cutting-edge tool to an essential pillar of enterprise strategy, reshaping how businesses approach automation, problem-solving, and growth.