Safer, smoother payments can be AI’s ‘killer app’

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More than $200 billion is expected to flow into the global AI industry by 2025, about five times the current GDP of small countries like El Salvador. But the results (products, services, and profits) must justify the capital infusion and frenzy. So far, it hasn’t. At that point, AI companies will need about $600 billion to be able to profitably pay back investors.

AI needs a ‘killer app’ to prove it’s not a bubble. Combining AI with blockchain and crypto for secure, frictionless, and user-centric payments could be the use case to save AI. Things like Amazon One’s palm recognition feature, which is already showing good results. Also, AI combined with blockchain will solve persistent problems like high centralization, bias in training data, lack of transparency, etc.; it will be a holistic improvement.

The best part is that such goals are quite achievable today. The blockchain-crypto stack has become significantly more performant and user/developer friendly. And AI models are likely to reach human-level intelligence by 2027.

Source: Situational awareness Experiences are more important than methods

According to Forrester’s ‘State of the US Consumer and Payments’ report for 2024, nearly 96% of US adults shop or pay online at least once a year. Digital payment adoption rates are higher among younger adults, who use more than four connected devices across four online platforms on average. They are also comfortable with emerging touchpoints and transaction channels like voice assistants, chatbots, etc.

Given this demographic, retailers should focus on providing a rich and seamless payment experience. Sometimes, it’s more important than the variety of payment methods available. While younger consumers are often open to trying/adopting new methods, compromising on experience is not an option.

Both predictive and generative, AI can help payment providers and merchants efficiently serve the next generation of consumers. For example, Microsoft’s Co-Pilot for Finance can be integrated with finance apps so users can ‘talk’ to their financial data. From identifying key spending areas to asking budget questions, these AI-powered tools allow users to make more informed payments/spending choices.

Similarly, retailers and online platforms can use AI to analyze users’ interaction patterns to offer personalized payment options, offers, etc. Offering timely discounts can also boost sales.

Apart from UX and accessibility, integrating AI significantly enhances the security of payment rails. Advanced machine learning, natural language processing, etc. unlock effective anomaly detection and help detect financial frauds in real-time or even before they happen. AI also enables additional user-facing security layers like biometric verification.

Leading financial institutions like HSBC and PayPal are already using AI-based systems to combat money laundering and other payments-related crimes. And as the technology evolves, over 61% of companies worldwide are excited about using AI to streamline and secure their payment gateways.

Securing the safe

Securing digital payments with predictive security mechanisms and data analytics is one of AI’s primary contributions to the global financial sector. However, developing and training AI models requires a lot of resources. OpenAI spent “more than $100 million” to train GPT-4, which is nearly impossible for the average medium-small company.

As development and training costs continue to rise in the coming years, more and more potential builders will be left out of the AI ​​race. This will lead to further centralization in an industry where the balance is already tilted in favor of a large minority. For context, two-thirds of all funding raised by emerging AI projects has gone to Big Tech companies.

Web3 native payment infrastructure is necessary to offset the potential negative impact of increased enterprise adoption and participation. This also applies to AI-powered payment systems. More AI means more data creation/mining. Managing these vast datasets, often containing sensitive information, on hypercentralized servers poses serious threats to security, privacy, and end-user autonomy.

That’s one reason why Web3-focused startups and VCs are turning to decentralized AI for payments and more, so much so that the sector attracted over $207 million in funding in less than 96 hours in early July.

As a globally distributed, transparent, and tamper-proof database technology, blockchain perfectly complements AI systems. Decentralized payment rails can benefit from AI’s ability to provide a seamless and interoperable UX, but there are currently aspects that prevent mass adoption of web3 native payment rails.

AI in payments is a $55 billion+ opportunity by 2031, and blockchain/crypto is critical to making it a reality. This combination will allow merchants and service providers to offer a rich payment UX (fiat, crypto, and more) along with a broad set of payment methods.

If the AI ​​industry is serious about finding the ‘killer app’ for sustainable, long-term adoption, it cannot do away with the decentralized payments paradigm. This is where solutions to persistent problems coexist with scope for innovation for the future. This is the clear path forward.

Peko Wan

Peko Wan is the co-CEO of Pundi X. He has over 15 years of experience in the IT industry. Prior to joining Pundi X, he worked at Opera Software and Ogilvy & Mather. Pundi X deploys a blockchain-based point-of-sale solution and is building partnerships with governments, payment companies, and retailers. They were named one of the top 50 Fintech Innovators by KPMG and H2 Ventures in 2018, great vendors in the blockchain business by Gartner, and one of the top 10 Fintech leaders by the Singapore Fintech Association in 2019.