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More than $200 billion expected AI technology is expected to flow into the global AI industry by 2025 – nearly five times present GDP of smaller countries like El Salvador. However, the results (products, services, profits) must justify the influx of capital and the frenzy. This has not happened yet. AI companies will lead to an increase in demand for AI. Needs About $600 billion to repay investors profitably at this point.
artificial intelligence Needs “A killer app to prove it’s not a bubble.” Combining AI, blockchain, and cryptocurrencies for secure, seamless, user-driven payments could be a use case for AI redemption. Things like Amazon One’s palm recognition feature It has already shown good results. In addition, the combination of AI and blockchain technology would solve persistent problems such as high centralization, bias in training data, lack of transparency, etc. – and that would be an overall improvement.
The best part is that such goals are easily achievable today. The blockchain-crypto stack has become extremely high-performance and user/developer friendly. AI models are likely to be It arrives Human-level intelligence by 2027.
Experience is more important than methods.
About 96% of adults in the United States shop or pay online at least once a year, According to According to Forrester’s “State of the U.S. Consumer and Payments” report 2024, digital payment adoption rates are highest 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, such as voice assistants, chatbots, etc.
Given this demographic, retailers need to focus on providing a rich and seamless checkout experience. This is sometimes more important than the variety of payment methods available. While younger consumers are typically open to trying/adopting new methods, compromising on the experience is not an option.
AI—both predictive and generative—can help payment providers and merchants serve new consumers efficiently. For example, Microsoft’s Co-Pilot for Finance can They can be integrated with finance apps, so users can “talk” to their financial data. From identifying key spending areas to asking budget-related questions, these AI-powered tools enable users to make more informed payment/spending choices.
Similarly, retailers and online platforms can offer personalized payment options, offers, etc., using AI to analyze user engagement patterns, etc. Offering timely discounts can also boost sales.
In addition to user experience and accessibility, the integration of AI greatly enhances the security of payment systems. Advanced machine learning, natural language processing, etc., enable efficient anomaly detection and help detect financial fraud in real-time or even before it happens. AI also enables additional layers of user-facing security, such as biometric verification.
Leading financial institutions such as: Hsbc Bank and PayPal Banks are already using AI-based systems to combat money laundering and other payments-related crimes. As technology evolves, more 61% of businesses worldwide are excited to use AI to simplify and secure their payment processes.
Insured insurance
Securing digital payments using predictive security mechanisms and data analytics is one of the major contributions of AI to the global financial industry. However, developing and training AI models is resource-intensive. OpenAI spent “over $100 million” training GPT-4, which is nearly impossible for any medium-sized company.
More and more potential builders will be pushed out of the AI race as development and training costs rise. Complete This percentage is expected to increase in the coming years. This will lead to further centralization in an industry where the balance is already tipped in favor of a large few. In this context, two-thirds of all funds raised by AI startups gold For big tech companies.
Web3 payment infrastructure is necessary The increased use of AI means increased data creation/mining. Managing these massive data sets – often containing sensitive information – on highly centralized servers seriously threatens security, privacy, and end-user autonomy.
That’s partly why Web3-focused entrepreneurs and venture capitalists are embracing decentralized AI—for payments and more. So much so that the sector attracted more than $207 million in funding in less than 96 hours in early July.
As a globally distributed, transparent, and tamper-resistant database technology, blockchain is an ideal complement to AI systems. Decentralized payment systems can benefit from AI’s ability to ensure a seamless and interoperable user experience, but there are aspects that currently hinder the mass adoption of Web3 native payment systems.
Artificial intelligence in payments is more A $55 billion opportunity by 2031, blockchain and cryptocurrencies are critical to making this a reality. This combination will allow merchants and service providers to offer a rich payment experience alongside a wide range of payment methods – fiat, crypto, and more.
If the AI industry is serious about finding the “killer app” to embrace in the long term, it can’t afford to ignore the decentralized payments model. This is where solutions to ongoing problems coexist with the future of innovation. It’s the obvious way forward.