From static rules to self-optimising payments: how AI is redefining orchestration

Ran Cohen, Co-Founder and CEO at BridgerPay, discusses how AI is redefining payment orchestration, shifting from static rules to self-optimisation.

 

Why isn’t traditional payment orchestration enough anymore, and how do you see it evolving with AI?

Traditional payment orchestration was built around static logic, routing transactions based on fixed rules or limited historical data. That worked when payment ecosystems were simpler. However, today’s environment is dynamic, and static setups can’t keep up with this complexity.

At BridgerPay, we’re evolving orchestration into a self-serve, data-driven, and AI-powered system. Instead of merchants defining rules manually, AI learns from transaction data across our entire Bridger community – billions of data points spanning geographies, industries, and PSPs to make smarter routing, retry, and optimisation decisions in real time. This creates a feedback loop where every merchant benefits from the collective intelligence of the network.

In other words, self-serve orchestration becomes self-optimising orchestration. Merchants can design and control their payment flows intuitively, while AI continuously tunes performance, increasing approval rates, lowering costs, and reducing false declines – all without manual intervention. By combining the flexibility of a no-code orchestration layer with the predictive power of AI trained on community-wide data, Bridger enables clients to optimise payments with insights and precision they’ve never had before.

We see this as a fundamental shift – not just automating payment routing but evolving it into a living, intelligent layer that adapts to business needs in real time. As ecosystems become more fragmented and user expectations rise, the ability to optimise dynamically across providers, currencies, and geographies becomes a necessity, rather than a nice-to-have.

What is BridgerPay’s approach to responsible AI use? 

Our approach to responsible AI is grounded in control, transparency, and data integrity. We believe AI should empower our clients – not replace their judgment or compromise their data. That’s why we’re building our own payments-specific language model (SLM), trained exclusively on BridgerPay’s proprietary transaction, orchestration, and performance data. Unlike general-purpose AI models that rely on open or external datasets, our model is fully controlled, hosted, and governed within BridgerPay’s infrastructure, ensuring complete data privacy and compliance across all jurisdictions.

This approach allows us to leverage the full power of AI while maintaining clear ownership and transparency over how data is used. Every insight generated by the Bridger SLM is explainable and traceable, designed to help merchants make better decisions rather than obscure them behind a ‘black box’.

We also believe in giving clients choice and control. AI should be assistive, not prescriptive. Our users can decide how much autonomy to give the system and when. In short, our AI is built for payments, by payments people, and for the benefit of our clients – responsibly. It’s AI you can trust, because it’s trained on your ecosystem, powered by BridgerPay, and controlled by no one but you.

How does BridgerPay use AI to support clients’ needs?

At Bridger, we’re using AI to extend our platform into a living ecosystem of intelligent experts – a family of specialised AI agents built directly into the product. Each expert has a defined role and purpose, designed to assist clients across every part of their payment journey. For example, one expert focuses on optimisation, analysing routing data and suggesting improvements to increase approval rates. Another focuses on risk and compliance, proactively detecting anomalies or potential fraud patterns. Others specialise in operations, PSP performance monitoring, reconciliation, and revenue recovery – each acting as a virtual team member with deep, domain-specific knowledge.

What makes this powerful is how these AI experts interact: they share data contextually through Bridger’s orchestration layer, creating a collaborative intelligence system. The result? Real-time insights that go beyond static dashboards – actionable recommendations, automated alerts, and even autonomous actions when permitted.

Our long-term vision is to make every merchant feel like they have a dedicated AI payments team inside Bridger – available 24/7, continuously learning, and fully tuned to their unique business logic and transaction patterns.

Where do you see AI taking payments and orchestration in the next few years?

AI is about to redefine what payments and orchestration mean. In the coming years, we’ll move from rule-based automation to fully autonomous optimisation – where payment systems not only execute transactions but think, learn, and adapt in real time.

Instead of merchants manually configuring routing rules or analysing dashboards, AI-driven orchestration will forecast the best path for every transaction, dynamically balance cost vs. approval probability, and even negotiate between PSPs and networks to achieve optimal performance. This evolution turns payments into a self-improving ecosystem, not just a processing infrastructure.

At Bridger, we see this as a shift toward self-serve intelligence – where even the smallest merchant has access to the kind of tools and insights once reserved for large enterprises. Our proprietary SLM will serve as the engine behind this, continuously learning from global data while preserving local context for each client.

Ultimately, payments will become invisible, adaptive, and always optimised. AI will bridge the gap between technology and strategy, helping merchants unlock new revenue, reduce operational drag, and stay ahead in a fast-moving digital economy.

 

This editorial piece was first published in The Paypers' Global Ecommerce Report 2026, which provides a complete overview of key trends and strategies to help businesses worldwide succeed. Download your free copy today to explore in-depth insights on global ecommerce trends, the latest innovations in payment solutions, and strategies to stay ahead in a competitive market.

 

About the author

Ran Cohen is the Co-Founder and CEO of BridgerPay, where he leads the vision for building the world’s first AI-powered payment operations platform. With over a decade in fintech, Ran brings a deep understanding of global payment infrastructure, risk, and optimisation. He’s passionate about turning complex payment ecosystems into intelligent, self-optimising networks that drive business growth.

 

 

About BridgerPay

BridgerPay is an AI-driven payment operations platform that helps businesses connect, manage, and optimise payments across 180+ countries and thousands of PSPs. With tools like Smart Routing, Bridger Retry™, tokenization, and AI-powered orchestration, BridgerPay enables merchants to boost approval rates, reduce costs, and scale globally. BridgerPay is PCI Level 1 certified and trusted by leading enterprises in ecommerce, travel, SaaS, and beyond.