[Paypers] Agentic AI, orchestration, and the future of payments: Damir Čaušević on Money Motion 2026

What role does Monri Payment play in organising Money Motion, and how does the event connect to Monri’s broader vision for payments? 

Together with the other co-founders, we started Money Motion with a clear vision: to create a forum for serious discussions on payments. We wanted a place where real conversations about payments, technology, regulation, and scale can happen, grounded in actual operational experience. That aligns closely with how we approach payments at Monri. We operate across markets that are often overlooked in global discussions, yet face the same complexity as larger ecosystems — fragmented regulation, multiple payment methods, and rising customer expectations. Money Motion is not about showcasing products and sales pitches. It is about exchanging insights, lessons learned, and sometimes hard truths about where the industry really is. For us, the conference is an extension of how we think about payments: pragmatic, experience-driven, and focused on real problems, not industry buzzwords. This year, we expect to gather over 900 companies and more than 3,000 professionals from 20+ countries, making it the leading fintech event in Central and Eastern Europe.

Which payment trends will be most prominent at Money Motion 2026, and why are they particularly relevant right now? 

One of the most prominent trends will be AI-driven payments. As the payments ecosystem becomes increasingly automated, AI will play a central role in predicting user intent, streamlining checkout processes, and managing fraud, chargebacks, and compliance in real time. This shift is particularly relevant in the current climate, where fraud is becoming more sophisticated, regulatory expectations are rising, and businesses face pressure to maintain slim margins. The ability to make smarter, faster decisions will be a critical competitive advantage moving forward, with the rise of agentic commerce driving further automation, personalisation, and operational efficiency in payment systems. Another key trend is the rise of stablecoins, tokenized money, and the future of settlement. Over the next 12 to 24 months, the industry will focus on whether regulated stablecoins, tokenized bank deposits, or central-bank-backed digital currencies can drive greater efficiency in settlement processes. This trend is highly relevant now, as these developments will influence market standards, licensing approaches, and interoperability—ultimately shaping cross-border payments, treasury management, and the speed and cost of settlements. Alongside these developments, the wallet warsare intensifying. Digital wallets are evolving beyond simple payment tools to become platforms for identity, credentials, loyalty, and access. This transformation is particularly important now, as new digital identity initiatives and increased competition between banks, payment providers, and bigtech push stakeholders to redefine who controls user authentication, data, and distribution channels. Moreover, resilience and sovereignty of payment railsare becoming key priorities for businesses. With rising geopolitical risks, companies are reassessing their dependence on a few centralised global infrastructures. Ensuring that payment systems are resilient, redundant, and regionally connected is now crucial for mitigating risk and maintaining operational continuity. Finally, the growth of micropayments and new retail economics is reshaping digital business models. As more businesses rely on small, frequent transactions—such as in-app purchases or machine-to-machine payments—the need for improved user experience and faster settlement times is pressing. If these areas don’t improve, entire sectors may struggle to scale sustainably. These trends reflect a rapidly evolving payments environment. As technology, regulation, and global dynamics intersect, they will redefine how payments are made, settled, and secured in the future.

AI is a recurring theme across the industry. How do you see AI being applied across the payment stack in 2026, from fraud to routing to orchestration? 

In 2026, we will likely still be talking extensively about AI, with implementation progressing more slowly than the conversation around it. In the years that follow, however, I expect AI to become increasingly embedded as a foundational capability, while becoming far less visible as a standalone ‘feature’. Fraud systems will become more adaptive and better at balancing security with conversion. In routing and orchestration, AI will increasingly be used to make decisions in real time, based on a wide range of variables: issuer behaviour, transaction context, cost structures, latency, and historical performance. Artificial intelligence is entering its second phase – from the era of simple ‘chatbots’, we are transitioning into the era of AI agents that can independently handle complex financial processes. This includes everything from compliance checks and real-time fraud detection to data analysis and investment portfolio optimisation. These systems not only reduce the need for manual processes but also enable fintech companies to create entirely new business models that were previously impossible. One of the biggest shifts is hyperpersonalisation of services—AI tailors each user interaction to their habits, needs, and financial goals. This enhances the user experience by predicting needs, offering personalised advice, and adjusting products or investment strategies in real time. For fintech, this means faster, safer, and more efficient data processing, along with the chance to innovate business models that were once impossible. With the rapid rise of instant payments, real-time value movement is becoming the market standard. This drives the evolution of agentic commerce, where intelligent digital agents are increasingly making payment decisions. According to McKinsey, in the next decade, agentic commerce will reshape the global economy, with digital agents expected to handle billions of transactions worth USD 3 to USD 5 trillion annually by 2030, relying on real-time payment infrastructure.

Why is traditional payment orchestration no longer sufficient for today’s complexity, and what gaps is AI helping to close? 

Traditional payment orchestration was built for a simpler world, where rules could be defined upfront and applied consistently. However, in today’s fast-paced payments ecosystem, conditions change constantly—consumer preferences evolve, regulatory requirements shift, and new fraud tactics emerge. This makes traditional systems, which rely on static rules, increasingly insufficient for handling the complexity of modern transactions. One of the gaps that AI is already helping Monri as an orchestrator, still not to close, but for now to accelerate, is the integrations that we perform regularly with various acquirers and different payment methods.  As consumer behavior becomes more dynamic, traditional systems struggle to offer personalised payment options or adapt to new payment methods in real time. AI addresses these challenges by introducing real-time adaptability and intelligent decision-making into payment orchestration. With machine learning, AI systems can continuously analyse transaction data, adapt to changing consumer behavior, and even predict future payment preferences. This dynamic approach not only ensures smoother user experiences but also helps businesses stay compliant with regulations without manual intervention. By continuously learning from data, AI allows payment orchestration systems to remain agile, reduce fraud, and optimise transaction flows in ways that traditional rule-based systems simply cannot match. 

Do you expect AI-driven orchestration to become a competitive differentiator or a baseline requirement for payment providers? 

In the short term, it will be a differentiator. However, over time, AI-driven orchestration will become a baseline expectation. Much like cloud infrastructure or real-time monitoring today, it will no longer be something you advertise – it will simply be something you are expected to have. The real differentiation will then move to how effectively providers manage AI, how safe and transparent their systems are, and how well they can align optimisation with their clients’ business goals.