Source: Crypto.news
Safer, smoother payments can be AI’s ‘killer app’
Compiled by: BitpushNews an
The global AI industry is expected to attract more than $200 billion in capital inflows by 2025, about five times the GDP of a small country like El Salvador. However, products, services, and profits must justify this capital, which has not yet been achieved. Currently, AI companies need about $600 billion to generate profitable returns for investors.
AI needs a “killer app” to prove it’s not a bubble. Combining AI with blockchain and cryptocurrency for secure, seamless, and user-centric payments can be a use case that saves AI. For example, Amazon One’s palm print recognition has achieved good results. Plus, the combination of AI and blockchain will solve persistent problems such as high centralization, training data bias, lack of transparency, etc. - it’s an all-round improvement.
Most importantly, such a goal is already quite achievable today. The blockchain-cryptocurrency technology stack has become extremely performant and user- and developer-friendly. And AI models are expected to reach human-like intelligence by 2027.
User experience takes precedence over payment method
According to Forrester's 2024 (US Consumer and Payment Status) report, about 96% of American adults make online purchases or payments at least once a year. Young adults have a higher rate of digital payment adoption, using an average of more than four connected devices across four online platforms. In addition, they are also comfortable using emerging touchpoints and transaction channels (such as voice assistants, chatbots, etc.).
With this group in mind, retailers must focus on providing a rich and seamless payment experience. Sometimes, this is more important than offering multiple payment methods. While young consumers are often willing to try or adopt new methods, their payment experience requirements are uncompromising.
Predictive and generative AI can help payment service providers and merchants serve the new generation of consumers more effectively. For example, Microsoft's financial collaboration tool Co-Pilot for Finance can be integrated into financial applications, allowing users to "talk" to their financial data. From identifying major spending areas to asking budget-related questions, these AI-driven tools enable users to make smarter payment and spending choices.
Similarly, retailers and online platforms can use AI to analyze user interaction patterns and provide personalized payment options, offers, etc. By providing timely discounts, sales growth can also be promoted.
In addition to user experience and accessible design, integrating artificial intelligence significantly improves the security of payment systems. Advanced machine learning, natural language processing and other technologies unlock efficient anomaly detection, helping to detect financial fraud in real time or even before it occurs. AI also enables additional layers of user security, such as biometric verification.
Leading financial institutions like HSBC and PayPal are already using AI-based systems to combat money laundering and other payment-related crimes. As technology develops, more than 61% of companies around the world are looking forward to using AI to simplify and protect payment systems.
Protect payment security
Securing digital payments is one of AI's main contributions to the global financial industry, using predictive security mechanisms and data analysis to ensure security. However, developing and training AI models requires a lot of resources. OpenAI spent "more than $100 million" to train GPT-4, which is almost impossible for any small or medium-sized company.
As development and training costs continue to rise over the coming years, more and more potential developers will be forced out of the AI race. This will lead to further concentration in an industry that already favors a few large companies. For context, two-thirds of funding raised for emerging AI projects has gone to large tech companies.
Web3 native payment infrastructure is necessary to offset the potential negative impact of increased institutional adoption and participation. The same applies to AI-driven payment systems. More AI means more data creation and extraction. Managing these massive datasets — which often contain sensitive information — on hyper-centralized servers poses a serious threat to security, privacy, and end-user autonomy.
This is partly why Web3-focused entrepreneurs and venture capitalists are pushing for decentralized AI — both for payments and other uses — to the point where the space attracted more than $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 networks can leverage AI to ensure a seamless and interoperable user experience, but current factors are hindering the widespread adoption of Web3 native payment networks.
AI in payments will be a $55 billion+ opportunity by 2031, and blockchain and cryptocurrencies will be critical to making it a reality. This combination will enable merchants and service providers to offer a rich payment user experience, as well as a wide range of payment methods — fiat, crypto, and more.
If the AI industry truly hopes to find the “killer app” that will enable sustained, long-term adoption, it cannot ignore the paradigm of decentralized payments. Here, solutions to enduring problems coexist with space for future innovation. It is the obvious way forward.
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