Most of the payment service providers are already actively using payment orchestration, or at least considering using this technology to enhance flexibility, routing intelligence, and global reach for merchants. What happens when AI agents come into play, and how agentic orchestration differs from payment orchestration? Let’s find out.
As more and more technology leaders develop their own agentic AI tools for multiple purposes, we cannot help but wonder how they will come in handy for the payments sector. To estimate that utility, let’s start with defining core terms.
AI Agents Explained
A recent survey has shown that 86% of Southeast Asian firms are set to adopt AI agents within a year, with half of them having already deployed the technology. What are those agents exactly?
AI agents are artificial intelligence tools able to handle the most complex tasks without human intervention. These software programs are designed to autonomously adapt to changing environments, improve their performance, and make informed choices without constant human input and supervision.
How do they differ from, let’s say, common GPT-like chatbots? AI agents are not solely focused on conversational or generative tasks. While AI agents can embed chatbots like ChatGPT into their system, they encompass broader capabilities.
Main Characteristics of AI Agents
Some of the most significant features that characterize AI agents are:
- autonomy,
- environment perception,
- reactivity,
- reasoning,
- learning capabilities,
- independent intra-agent communication,
- goal-oriented behavior,
- real-time adaptivity to changing environments,
- suitability for complex workflows and dynamic environments beyond text conversations.
AI Agents May Cooperate in Agentic Orchestration Systems
Agentic orchestration is a system that coordinates activities of multiple autonomous AI agents, robotic process automation (RPA) bots, and even humans across complex workflows.
While each separate AI agent may be dedicated to a specific task, agentic orchestration helps them communicate and collaborate towards more complicated multi-step tasks, and optimize processes dynamically, often across multiple enterprise systems.
Just as human employees with different experience levels and skill sets together form a multifunctional organization that serves the same mission, diverse AI agents in an agentic orchestration ecosystem unite to handle a complex workflow.
Within an agentic orchestration system, the coordination of separate autonomous agents is managed by a specialized coordination layer or orchestration engine rather than a single dedicated agent. This orchestration layer manages all the interactions and task delegation between various agents with different capabilities.
How Agentic Orchestration Layer Works
In agentic orchestration frameworks, the coordination layer or engine divides high-level shared goals into sub-tasks, then routes these tasks dynamically to the appropriate agents.
This decision is based on the capabilities of available agents and their workload. Such information is stored in an agent registry that maintains metadata on all participating agents. It facilitates optimal task assignment.
Besides that, there’s a communication protocol that enables asynchronous, real-time communication and data sharing between agents. The communication methods may include APIs, message queues, event-driven systems, or shared memory.
How Agentic Orchestration Overlaps With Payment Orchestration
Payment orchestration is a software system that optimizes payment processing across multiple payment service providers (PSPs), gateways, and payment methods, unifying their management in a single centralized hub.
Payment orchestration service leverages data analytics and machine learning to intelligently route transactions to the best provider, manage failures, improve approval rates, consolidate reporting, and simplify integrations for merchants.
If Payment Orchestration Platform Is Powered by AI, Does It Make It Agentic?
At present, payment orchestration is driven by AI but still tends to rely on predefined logic and centralized routing rules. At the same time, the evolution of payment orchestration frameworks and the emergence of agentic AI solutions designed for public use suggest that payment orchestration might eventually move toward agentic payments intelligence as well.
Incorporation of agentic orchestration principles like autonomous reasoning, AI-driven routing decisions, and real-time adaptive workflows in payment systems is already taking place across payment processing software solutions. With their wider implementation, payment processing can seamlessly coordinate with other operational segments as well.
So, how can payment orchestration become more intelligent and autonomous through agentic orchestration capabilities?
To find that out, PaySpace Magazine Global reached out to Andrew Riabchuk, founder of Akurateco:
“The ability of agentic AI systems to make certain operational decisions independently is very valuable for payment orchestration systems. Some of these AI tools are already used in payment orchestration, and they’ll be implemented even more actively as the agentic technology rapidly develops.
Agentic orchestration is the most useful for intelligent payment routing, where decisions can be made taking into account vast arrays of information rather than a few predefined rules. Payment orchestration with multiple AI agents (e.g. risk&fraud agent, customer preference agent, success probability agent, each contributing specialized intelligence) allows the system to dynamically evaluate far more variables in real time, as the orchestration agent balances all these trade-offs to maximize success rate, compliance, cost efficiency, and customer experience.
Another possible implementation area is optimization of the payment structure, as agentic AI can optimize which fees the customer actually ends up paying, by making dynamic fee choices for merchants who apply surcharges or absorb fees in real time based on certain factors like customer profile or product margins, and minimizing conversion fees for cross-border transactions. AI tools can also suggest lower fee choices to the customer at checkout in real time. That could increase the conversion rate and boost customer satisfaction.
In general, payment orchestration has a lot of areas where agentic AI can significantly boost efficiency, like cascading that distributes declined transactions between multiple payment channels so that the payment can be completed; management of failover systems, which support the payment software’s ability to switch automatically and seamlessly to a reliable backup system; and all other operational aspects, which can improve the payment approval rate.
Another major segment of payment orchestration that might be disrupted by agentic AI capabilities is A/B testing. Orchestrated AI agents could seamlessly and quickly compare acceptance rates, chargeback rates, and other crucial features of a few available payment processing variants to measure which one is most successful based on your key metrics and efficiently distribute traffic among those channels in a test mode.
Last but not least, agentic orchestration capabilities can serve payment companies while dealing with anti-fraud measures, including related planning and scoring systems, user verification, and compliance.
As for the prospective emerging technologies, we see network tokens actively used today to boost transaction security. Today, token vaults are mostly static repositories, often poorly synchronized, and lacking automated, real-time token lifecycle management. Thus, token vault storage could also be enhanced by agentic AI tools, creating active, adaptive, and intelligent infrastructure optimized for security, speed, and approval success.”
Agentic Orchestration Use Cases
Agentic orchestration systems are most useful in settings that require complex decision-making and currently involve a lot of manual effort. These can include, but are not limited to:
- financial trade reconciliation;
- industrial inspections and infrastructure maintenance;
- customer support automation;
- cybersecurity;
- insurance claim management;
- retail demand forecasting;
- risk management;
- intelligent payment routing;
- reconciliation and settlement;
- handling transaction failures;
- integration with agentic AI commerce.
Top Platforms Providing Agentic Orchestration Services
Although the technology is in its nascent stage, you can find a few service providers actively developing agentic orchestration solutions.
UiPath Maetsro orchestration engine enables autonomous, contextual agent tasks across business systems. It unites enterprise-grade orchestration with auditability and governance.
Camunda workflow and business process orchestration engine embeds AI agents into BPMN (Business Process Model and Notation) workflows. It offers observability, governance, and human-in-the-loop oversight.
Microsoft Copilot Studio is piloting multi-agent orchestration systems that let Copilots handle multi-step tasks, delegate responsibilities between specialized agents, and integrate seamlessly with enterprise tools.
Many other providers are exploring agentic orchestration infrastructure as well, with some of them already available in demo mode. As the technology becomes more common, it promises to pave the way towards a smarter, more resilient payments infrastructure.
