AI in digital payments: the new UPI business model

The signal from India: why it matters in Europe too

As of June 30, 2026, TechCrunch reported the statements of Dilip Asbe , CEO of NPCI (National Payments Corporation of India). Asbe clearly stated that AI will be deeply involved in the next era of digital payment growth. In particular, he highlighted how new UPI apps could compete more effectively only if equipped with a truly sustainable business model.

This scenario might seem distant from the Italian reality. However, the UPI system is today the global benchmark for real-time payments. In fact, it processed over 131 billion transactions in the fiscal year 2024-25 alone. Consequently, the dynamics emerging in that context often anticipate what will happen in Western markets with a 12-24 month delay.

Therefore, for marketing managers and digital leaders in Italian companies — especially in retail, B2B, and fintech — reading these signals in advance is a concrete competitive advantage.

The numbers reshaping the global payments market

The global digital payments market is currently worth over $11 trillion. According to McKinsey Global Payments Report , growth is robust but the pressure on margins is equally strong. In fact, the commoditization of basic payments has eroded the profitability of traditional players.

Furthermore, the advent of instant payments — in Europe driven by the EU Regulation on Instant Payments coming into effect in 2025 — has accelerated the need to find new revenue streams. Therefore, the central question is no longer how to grow volumes , but how to monetize intelligently .

In this context, AI acts as an enabler of three fundamental levers:

• Customization of the commercial offer in real-time, based on user payment behavior.
• Fraud detection and risk scoring predictive, which reduces operating costs and increases user trust.
• Dynamic optimization of commissions and pricing models, adaptable to the transactional context.

Furthermore, applications emerge related to the analysis of aggregated data to build spending profiles useful for third-party marketing — with all the regulatory implications of the case, particularly under the European GDPR.

From the UPI lesson to the Italian context: three strategic readings

The Indian case offers three insights directly applicable to the Italian market. First of all, the issue of revenue model . UPI was designed as a free infrastructure for the end-user. Consequently, apps built on it have struggled to find margins. AI now allows for the creation of value-added layers — recommendations, analysis, embedded financial products — that justify indirect monetization.

Subsequently, the theme of competition between apps . Similar to what happens with Asian super-apps, in Europe too, a concentration around a few dominant players (Revolut, Klarna, Satispay in Italy) is emerging. However, AI lowers the barrier for newcomers who know how to leverage it well. Therefore, it's not a given that the big incumbents have an insurmountable advantage.

Finally, there's the issue of trust and user experience . AI applied to payments isn't just backend. It's also conversational interface, proactive assistance, intelligent notifications. For this reason, companies integrating AI into the payment experience measurably improve retention and NPS.

Operational implications for marketing managers and digital leaders

For those who manage strategies of Digital marketing in companies with an e-commerce or fintech component, the implications are concrete. In fact, payment is no longer the end of the funnel: it is a touchpoint rich in data and engagement opportunities.

Therefore, it is worth considering some operational directions:

• Integration between CRM and payment data : AI can correlate purchasing behaviors and payment methods for more precise segmentation. This fuels more relevant campaigns on Google Ads and Linkedin .
• AI-based Loyalty Programs : predictive models allow offering incentives at the right time, increasing conversion rates and reducing churn.
• Content and SEO for fintech : the growing interest in digital payments and AI generates significant search volumes. A strategy of SEO and Copywriting targeted can intercept qualified demand.
• AI applied to campaigns : the AI services by SHM Studio include automatic optimization of budgets and messages, with direct impacts on ROAS.

Beyond this, those operating in B2B should monitor the evolution of payments embedded in management software. In fact, this integration is redefining purchasing processes and, consequently, the touchpoints for marketing.

The construction site still open: risks and variables to keep an eye on

Despite this, the path is not without obstacles. Therefore, it is useful to map the main risk variables for those who want to move in this space.

The first point is regulatory . AI applied to payment data directly touches GDPR, PSD3 (in the process of being transposed), and the guidelines of the European AI Act. Consequently, any initiative must be designed with an approach privacy by design from the architecture.

The second point is technological . As highlighted by Gartner in its analyses on AI in financial services , many organizations underestimate the complexity of integrating legacy systems and AI models. Therefore, data governance is often the main bottleneck.

The third point is cultural . Adopting AI in payment processes requires a mindset shift in organizations. In fact, it's not just about implementing a tool, but about redesigning decision-making flows and KPIs. For this reason, change management is an integral part of the project.

In summary, the opportunities are real and significant. However, they require a structured, not improvised, approach.

SHM Studio's perspective: where the game is played in the next 24 months

We at SHM Studio we observe this evolution with strategic interest. In fact, the convergence between AI, digital payments, and marketing is not a niche topic: it is destined to redefine entire sectors by 2027-2028.

For Italian SMEs and mid-market companies, the window of opportunity is open. However, it will close quickly as larger players consolidate their positions. Therefore, acting early—even on seemingly minor aspects like checkout optimization or post-payment personalization—can make all the difference.

Furthermore, AI is not a separate investment from marketing: it's a multiplier for ongoing initiatives. Therefore, the first step isn't necessarily building proprietary models, but integrating artificial intelligence into existing touchpoints — from the website to campaigns, from web presence to conversion funnels.

Those who want to explore how these dynamics apply to their specific context can contact the SHM Studio team for a preliminary analysis. Also, in the SHM Studio blog we regularly publish analyses and updates on AI, digital marketing, and emerging technologies for the Italian market.