4 minute read
The AI revolution
Tech titan Bill Gates calls artificial intelligence (AI) a technological revolution comparable to the advent of computers, mobile phones and the internet. While a bold claim, it’s no overstatement: AI promises to automate and potentially surpass the human capacity for analysis and learning.
This rapidly developing technology could also rewrite the rules in payments and commerce. For consumers, AI could reduce friction and provide enhanced personalization. For businesses, AI could help redirect human effort and talent towards more value-creating activities.
The ChatGPT moment
AI has been around for decades but has recently jumped into the public’s imagination with the introduction of ChatGPT—a natural language generative AI tool.
“ChatGPT is a trigger moment for generative AI because of the combination of a simple and user-friendly interface with a powerful tool that provides an outcome that is easy to digest.”
But generative AI is about more than just producing fully fleshed-out text or imagery in response to prompts. “Generative AI is self-learning and offers improved predictive capabilities over time,” says Guido Sacchi, Chief Information Officer at Global Payments. “It’s a feedback loop that continuously validates results and feeds them into the model. The model keeps refining itself to produce better results.”
For businesses, generative AI can support sales forecasting, customer service, human resources, accounts payable and receivable, fraud mitigation and more. Ultimately, these applications drive greater performance and free up teams to focus on more value-added and innovative work.
According to McKinsey, generative AI could add $2.6 trillion to $4.4 trillion in value to the global economy annually across the 63 different business use cases they analyzed.
A revolution decades in the making
Generative AI didn’t happen overnight. Research into AI dates back to the 1950s, but it wasn't until 1997 that AI scored its first major public victory: IBM’s Deep Blue system defeated reigning world chess champion and grandmaster Gary Kasparov. Two decades later, AI progressed to the point where Google’s Alpha Go defeated a human Go champion, Ke Jie (Go is an even more complex game than chess).
Now, AI and machine learning (ML) applications have become even more sophisticated. Combined with ML models and speech recognition, AI can take large data sets, recognize patterns within the information and perform real-time analysis of human conversations.
Rewriting the rules
Building off of decades of AI and ML, generative AI in payments and commerce is proving to be a propulsive force. Consider the following examples.
Boosting customer support. Chatbots have become commonplace customer service tools for many businesses. Generative AI-powered chatbots, however, are poised to make significant strides in meeting and anticipating customer needs. They’ll be able to answer common queries about payment balances, order statuses and returns, freeing up customer service teams to address more complex or sensitive issues. In short, customers will get a more personalized experience, deepening their relationship with their go-to brands.
Enhancing operational efficiencies. API integrations for businesses are often rigorous and time-intensive. "During integrations, a point of friction for many companies is the time it takes to build APIs to capture and push all the necessary information,” says Adam Mitchell, EVP of product, technology and enablement at Global Payments. Generative AI’s ability to streamline software development “will help simplify important software integrations like shopping carts, CRMs, and email marketing tools.”
Managing fraud and risk. Generative AI opens the door to better fraud detection. With generative AI, one could produce synthetic examples of fraud based on the patterns established by actual cases. These sequences would, in turn, help improve fraud-detection systems. Generative AI is like a coach to an athlete who needs to train for rare but critical game situations.
Friction-free payments and authentication. Amazon’s “pay-by-palm” technology allows customers to speed through in-store checkout by scanning their palms on a POS device. Using biometric authentication, generative AI and machine learning, the customer’s identity is accessed and payment is processed—another step towards making the payment experience “invisible” for the end user. “The authentication space is ripe for further innovation,” says Global Payments’ Sacchi. “People want maximum security with minimum friction.”
Preparing your business for the path ahead
While there is potential for significant enhancements from AI in payments and commerce, there are risks. As with all AI-empowered tools, there is potential for embedded bias in AI algorithms, challenges to data security and other considerations. Companies across all industries must remain vigilant.
But clearly, leaders who integrate AI in payments and commerce have the opportunity to enhance the customer experience while greatly increasing productivity and operational efficiency. Those who deploy AI thoughtfully are likely to capture these opportunities and greatly enhance their business and brand.
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