Consumer expectations for payment experiences are rapidly evolving, driven by advancements in technology and a heightened awareness of digital risks. NMI’s 2025 Payments Survey, which gathered insights from 1,000 U.S. consumers, offers a clear perspective on these shifts, highlighting key areas where businesses must innovate to remain competitive and retain customer loyalty. For senior marketing and CX leaders, these findings represent not just technological trends, but strategic imperatives for operational models, governance, and measurable customer outcomes.
Optimizing Self-Service and Expanding Payment Flexibility
Consumers increasingly prioritize convenience and choice in their payment interactions, pushing businesses to refine self-service options and integrate a broader array of payment methods.
This demand for autonomy is evident in the strong preference for self-checkout. NMI’s survey found that 55% of respondents desire more self-checkout options by 2025 due to their elevated convenience. This sentiment is particularly strong among younger demographics, with 67% of Millennials (ages 26-41) and Gen Z (ages 18-25) expressing this preference. However, the survey also reveals a critical friction point: 44% of all respondents identify unattended payment experiences, such as self-checkouts and kiosks, as the most frustrating when they encounter issues. This indicates that while the desire for self-service is high, the tolerance for a suboptimal experience is low. Alongside self-service, the appetite for flexible payment options is substantial, with 81% of respondents finding it important for retailers and businesses to offer diverse methods, including digital wallets, mobile payments, peer-to-peer (P2P) solutions like Venmo, and Buy Now, Pay Later (BNPL) options. Digital wallets, such as Apple Pay and Google Pay, are gaining significant traction; 44% of respondents anticipate using them more frequently in 2025, with 60% of Gen Z leading this trend. Furthermore, 36% of Gen Z and 30% of Millennials already use payment methods embedded in alternative devices like smartwatches.
What to do:
- Invest in Robust Unattended Payment Infrastructure: Prioritize the reliability and user-friendliness of self-checkout and kiosk systems across retail, grocery, and quick-service restaurant environments.
- Prioritize User Experience (UX) Design: Develop intuitive, easy-to-navigate interfaces that minimize steps and potential points of failure. Conduct rigorous User Acceptance Testing (UAT) with diverse user groups.
- Ensure Accessible Human Assistance: Integrate clear, immediate options for human support within self-service workflows (e.g., a “call attendant” button with a service-level agreement of a <30-second response time).
- Integrate Diverse Payment Rails: Expand acceptance beyond traditional credit/debit to include leading digital wallets, popular BNPL providers, and relevant P2P options.
- Explore Embedded Payment Solutions: For relevant sectors like fitness, transit, or event venues, investigate integrating payment capabilities into wearables and smart devices.
What to avoid:
- Deploying self-service systems without comprehensive quality assurance and a clearly defined escalation path for technical issues.
- Limiting payment choices based solely on current transaction volume, ignoring emergent preferences from younger, digitally native demographics.
- Overlooking the end-to-end integration of new payment types across Point-of-Sale (POS) systems, e-commerce platforms, and mobile applications, which can create fragmented experiences.
Summary: The imperative is to deliver a frictionless, reliable, and diverse payment experience. Measurable outcomes include transaction success rates, Customer Effort Scores (CES) for self-service interactions, and digital payment adoption percentages.
Strengthening Security and Building Trust in AI-Driven Payments
While consumers embrace digital payments, their awareness of associated risks, particularly data breaches, is escalating. This demands a proactive stance on security and a transparent approach to integrating artificial intelligence (AI) into payment processes.
Security concerns are paramount for consumers. The NMI survey indicates that 71% of respondents desire increased security and fraud protection from payment technology in 2025, and 64% identify the risk of their data being compromised in a breach as their greatest payment-related concern. This heightened awareness extends to emerging technologies like AI. While AI is already transforming back-end payment operations, consumer acceptance of AI in front-end experiences is conditional. Only 26% of respondents would support AI-driven payment experiences if it meant a faster checkout process, even though 33% of Gen Z showed willingness. Critically, 51% of Gen Z expressed concern about over-dependence on AI in payments, and only 29% of Millennials and Gen Z would support AI-driven payments if there was transparency regarding its usage. This highlights a clear gap between technological capability and consumer trust, particularly concerning data collection methods like biometrics.
Operating Model and Roles:
- Chief Information Security Officer (CISO): Responsible for payment gateway security, PCI DSS compliance, fraud prevention systems (e.g., real-time anomaly detection, behavioral analytics).
- Chief Data Officer (CDO): Oversees data governance, privacy policies, and consent management frameworks (e.g., adherence to GDPR, CCPA).
- CX Leaders: Tasked with communicating security measures and AI benefits transparently, managing customer perceptions, and addressing trust-related inquiries.
- Legal and Compliance: Ensures all payment technologies and data handling practices comply with relevant regulations.
Governance and Risk Controls:
- Data Readiness: Implement robust data anonymization, tokenization, and encryption protocols for all payment-related data, classifying data based on sensitivity.
- Consent Management: Establish explicit, granular consent mechanisms for any data collection, especially biometric data or advanced profiling, ensuring alignment with privacy regulations and user understanding.
- AI Guardrails: Develop ethical AI guidelines, conduct regular AI model validation, and perform red-teaming exercises to identify potential biases or vulnerabilities in AI-driven fraud detection or personalization.
- Thresholds: Define acceptable fraud rates (e.g., <0.04% of transaction value) and chargeback ratios (e.g., <0.6%) for payment processing.
- Escalation Paths: Document clear protocols for responding to suspected fraud, data breaches, and customer security concerns, with defined roles and responsibilities.
What to do:
- Invest in Advanced Fraud Prevention: Implement and continuously update machine learning-driven fraud detection systems that can identify sophisticated attack patterns.
- Transparently Communicate Security: Clearly articulate the security measures in place (e.g., end-to-end encryption, multi-factor authentication) through in-app messages, website information, and customer support channels.
- Educate on AI Benefits with Transparency: Explain how AI enhances payment security or convenience (e.g., “AI-powered fraud detection protects your account”) without overstating its role or hiding its presence.
- Integrate Consent Management Platforms (CMPs): Ensure user consent preferences are captured, stored, and respected across all payment touchpoints.
What to avoid:
- Implementing AI in customer-facing payment processes without a clear value proposition, or without transparently informing users of its involvement and their data’s use.
- Collecting payment data beyond what is strictly necessary, increasing the attack surface and compliance burden.
- Under-investing in cybersecurity infrastructure and staff, which can lead to reputational damage and financial penalties from breaches.
Summary: Building consumer trust requires both robust security measures and clear, honest communication about how advanced technologies like AI are used to protect and enhance their payment experience.
Leveraging Loyalty Programs for Enhanced Customer Value
Loyalty programs remain a significant driver of consumer choice, particularly for younger demographics who prioritize instant gratification and personalized rewards.
The NMI survey highlights that rewards programs are a primary value proposition for merchants. Specifically, 87% of all respondents and a notable 90% of Gen Z consumers indicate they are more likely to shop with a retailer that offers instant rewards. This includes not only accruable points but also personalized discounts and benefits. The implication is that static, generic loyalty programs are no longer sufficient to capture and retain the attention of modern consumers, especially those with lower brand loyalty. The rise of AI offers new avenues for hyper-personalization, enabling businesses to deliver highly relevant and timely offers that resonate with individual customer preferences and spending habits.
What ‘Good’ Looks Like:
- Financial Services: A credit card issuer leverages AI to analyze cardholder spending patterns, offering personalized cash-back categories each quarter (e.g., “Earn 5% on groceries and dining this month based on your spending history”).
- B2B SaaS: A software provider offers tiered discounts on annual renewals or unlocks premium features based on platform usage, client tenure, and successful referrals.
- E-commerce/Retail: An online retailer provides instant, context-aware discounts at checkout for loyalty members, dynamically generated based on their browsing history, past purchases, and current basket contents (e.g., “Complete your order now and receive 10% off your next purchase of [related product category]”).
What to do:
- Design for Instant Gratification: Structure loyalty programs to offer immediate, tangible benefits and personalized rewards that are easily redeemed during the payment process.
- Utilize AI for Hyper-Personalization: Integrate AI and data analytics with CRM systems to segment customers effectively and deliver targeted promotions, dynamic pricing, and custom offers.
- Ensure Frictionless Integration: Embed loyalty program benefits directly into the payment flow, both online and in-store, minimizing extra steps or cognitive load for the customer.
- Align Rewards with Business Objectives: Design reward structures that encourage desired customer behaviors, such as increased frequency of purchases, higher average transaction values, or subscription renewals.
What to avoid:
- Generic, one-size-fits-all loyalty programs that fail to differentiate customer value or provide tailored incentives.
- Overly complex redemption processes that require customers to navigate multiple platforms or wait extended periods for rewards.
- Failing to integrate loyalty benefits seamlessly into the payment experience, leading to missed opportunities for engagement at the point of decision.
Summary: Loyalty programs must evolve beyond basic point systems to offer hyper-personalized, instant rewards, leveraging data and AI to drive meaningful customer engagement and measurable increases in Customer Lifetime Value (CLV), repeat purchase rates, and retention.
The NMI 2025 Payments Survey underscores a critical juncture for businesses. The future of payments demands a strategic, integrated approach that balances innovation with unwavering attention to customer experience, security, and trust. Leaders must prioritize robust self-service options, embrace payment flexibility, implement transparent AI strategies, and leverage personalized loyalty programs to meet the evolving demands of today’s digitally native consumer. Proactive adaptation in these areas will not only drive customer satisfaction but also secure a competitive advantage in a rapidly transforming payments landscape.
