Agentic AI: Revolutionizing the Future of Payments

How Agentic AI is Accelerating the Autonomous Payment Transition: By Dmytro Spilka

Agentic AI is already beginning to redefine how payments are made and the ways in which we can manage our money. The infusion of intelligence, automation, and decision-making tools in real time to the financial landscape can bring far greater benefits to support modern working trends in the future. Today, the global payments industry generates more than $2.7 trillion in annual revenue from sources such as deposit spreads, card economics, cross-border flows, and merchant acquiring. McKinsey data suggests that around 50% of this revenue comes from collecting net interest income on deposits and consumer-card economics such as revolving balances and rewards that aren't redeemed. It's expected that agentic AI could address these revenue streams by empowering more individuals to become engaged with their finances. The technology, which is a subset of AI, can contribute plenty of positives to the fintech ecosystem, with the potential to redefine payments, cash management, and fraud detection by uniting intelligence, automation, and real-time decision-making to financial operations. With far greater efficiency, security, and customer engagement leveraged by agentic AI, the benefits for adopters could be seismic, and we're already gaining a clearer picture of how the technology will help shape the autonomous payment transition. The Future of Credit While traditional credit scoring models are dependent on gaining a static snapshot of risk at a single moment, agentic AI has the ability to aid banks as well as fintechs to continually assess the creditworthiness of individuals by incorporating real-time transaction data and uniting it with behavioral trends, as well as taking wider economic indicators into account. These automated measures can pave the way for more precision in the risk assessment process and greater flexibility for lending models that could continue to adjust in real-time as new data arrives. Although agentic AI decisions could risk models becoming biased against credit applicants based solely on their past, the technology may pave the way for a fairer lending landscape, where institutions and regulators can balance the power of AI with transparency and ethical oversight to make key decisions based on more complex borrower insights that determine their overall creditworthiness. Full Payment Autonomy Agentic AI payments will also help to support the emergence of Internet of Things (IoT) commerce, where interconnected devices can bring full autonomy to the making and receiving of payments without the need for any human intervention. The foundations of IoT agentic AI are already in place and very visible across different industries. For instance, Samsung's AI Vision Inside technology is helping your fridge to replenish your food with the help of internal cameras and a pairing with Instacart's product-matching system. Here, the artificial intelligence can suggest a shopping list for you, creating an order for you to pay for in just a couple of clicks. There's also plenty of potential for electric vehicles (EVs). For instance, if your EV detects a low battery, it can find the closest station and automatically pay for a charging session, all with the help of agentic AI. Supporting the Remote Economy With more employees embracing remote work in recent years, agentic AI can help to support a brand new remote economy to support evolving worker needs. While reports suggest that 82% of remote workers opt to complete their tasks from home, with 5% using co-working spaces and 2% preferring coffee shops, frictionless payments can help support growing demands for flexibility to match the needs of on-the-go employees. The use case of the Singapore-based coffee ordering platform, Luckin Coffee, which was integrated into Alipay's AI agent for agentic ordering and payments via a conversational interface, is helping to provide a glimpse of what remote work could look like in the future. Whether a remote employee is working from home or in a co-working space, they can simply tell the AI app that they want to place an order after selecting their drinks, and after identity verification, the payment is processed without having to leave the conversation with the agent. This helps Luckin Coffee's mobile app to mimic an interaction with a barista, ensuring a more interactive experience for employees who may be feeling more isolated when working from home. Regulatory Considerations Embracing agentic AI in payments will come with some regulatory considerations. For instance, if an AI agent makes a payment to the wrong vendor, who's liable? The user, the platform, or the agent's creator? Could technology intervene if repeat transactions are erroneously set up by a bot? The EU has taken a strong approach to regulating AI, banning high-risk practices like subliminal techniques, exploiting user vulnerabilities, social scoring, and biometric-based profiling. These can all carry implications for the payments landscape and require considerations among fintechs adopting the technology. Autonomous Payments Agentic AI will certainly play a crucial role in the future of autonomous payments, and its rollout can have a major impact at a time when more individuals are craving flexibility when it comes to making purchases. The idea of consumers parting with their money without physically handing over money or unlocking their wallet could be jarring, but the convenience of AI handling essential purchases is likely to shape the future of spending. With this in mind, users can benefit from more data-based recommendations for purchases that minimize inconveniences, albeit with brand-new regulatory implications for consumerism.

Bringing Agentic AI in Payments, What to Expect

By Sudeshna Singh Think about how long it would take for an invoice to be processed for a business or how long it would take for a customer to make an online purchase if they had to go through several verification steps. These are things that happen on a daily basis, showing how payments can get delayed. There are 3.4 trillion transactions processed every year around the world, with a total value of $1.8 quadrillion, but many people still use old systems that cost more and make things less efficient. Agentic AI is a step in the right direction because it lets payments be handled on their own, cuts down on the need for human involvement, and makes it easier for businesses and consumers to move money around. Why Payments Need Agentic AI Traditional automation in payments has brought some relief in areas such as fraud detection and transaction monitoring, but the wider process remains dependent on human oversight. Invoices often take days to process, creating delays and tying up resources. Agentic AI can ease this burden by enabling intelligent agents to manage entire payment cycles, from initiation and reconciliation to settlement. Payments then move from being repetitive tasks to automated functions that deliver greater speed and accuracy. The case for agentic AI is about efficiency as well as resilience. Manual oversight introduces the possibility of errors, lost data, and compliance gaps. By moving payment cycles into autonomous systems, organizations can create more reliable operations with better audit trails and real-time transparency. This helps both businesses and regulators build confidence in the system. Promising Use Cases Already Taking Shape A number of examples demonstrate the potential applications of agentic AI in payments. With single-use virtual cards, an agent can only authorize a certain amount for a specific transaction, giving the customer more control and lowering the possibility of fraud. With the help of smart contracts and programmable money, agents can only make payments when specific requirements are fulfilled, guaranteeing that goods or services are provided before money is disbursed. Agents can also manage invoice-to-cash and procure-to-pay workflows in corporate payments, which speeds up intricate transactions. Even in debt recovery, agentic AI can tailor outreach and forecast default risk, increasing recovery rates while preserving client relationships. Another area gaining attention is cross-border payments. Today, these transactions are slowed by multiple checks, currency conversions, and intermediary banks. An agent-led system could streamline these processes by verifying compliance conditions instantly, applying real-time foreign exchange rates, and releasing funds once rules are met. This could cut settlement times from days to minutes while reducing the cost of international transactions. In retail environments, agentic AI can also enable personalized purchasing flows. An agent could recognize a customer's preferences, apply loyalty rewards, compare available payment options, and execute the transaction in the background. For the consumer, the experience would feel seamless, while merchants gain efficiency and stronger customer engagement. These instances show how pilots can provide quantifiable advantages without subjecting organizations to excessive use. These examples reflect areas where pilots can deliver measurable benefits without exposing institutions to undue risk. The Barriers to Adoption Despite all of its potential, agentic AI in payments has unavoidable challenges. Since regulations differ greatly between jurisdictions and there are severe consequences for non-compliance, regulatory compliance is the most important issue. Given that anti-money laundering fines alone totaled more than $6 billion in 2023, banks and other financial institutions are still exercising caution. Another barrier is trust. According to surveys, less than one in five customers in countries like the US feel comfortable letting AI handle their payments. Institutional confidence is equally limited. Executives worry about how autonomous systems would behave in high-stakes contexts, such as large corporate payments or settlement of securities. The risk of an error or unauthorized action makes many leaders cautious about moving too quickly. The hesitancy is exacerbated by technical constraints, as scalability and reliability have not yet been thoroughly implemented in large-scale deployments. Many existing payment systems were not built for agent-led activity, and retrofitting them is complex and expensive. This creates a gap between the promise of new technology and the practical reality of legacy infrastructure. Building the Right Foundations Success with agentic AI will rely on institutions' eagerness to modernize their infrastructure. Modular and interoperable systems incorporating blockchain, programmable money, and orchestration platforms will allow agents to operate across networks without the constraints of silos. To comply, more robust tools for identity authentication, monitoring, and reporting will be required, thereby ensuring regulators of compliance. Establishing trust will involve decentralized identity and multi-signature wallets, which offer transparency and security. Concurrently, investment in skilled staff and controlled pilots will enable organizations to become confident in the responsible deployment of agentic AI. Conclusion Payments are at the start of an important development where agents will increasingly handle processes that were once entirely manual. Progress will be steady rather than sudden, with early applications like virtual cards and automated reconciliation setting the tone for wider adoption. For businesses, banks, and regulators, the task is to ensure implementation of agentic AI in a way that balances efficiency, compliance, and trust. Those who prepare their systems and strategies today will be best placed to lead in the next chapter of digital payments. The institutions that act early, modernize their systems, and build trust with both regulators and customers will shape the new standards of digital payments. Those that delay risk being left dependent on outdated methods in an industry that is moving toward autonomy. The question is no longer whether agentic AI will enter payments, but how quickly organizations can adapt to it. (The author is Sudeshna Singh, Senior VP & Head of Marketing, ToneTag, and the views expressed in this article are his own)