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    Visa Is Letting AI Spend Your Money and Changing How the World Buys

    The payments giant is embedding AI into everything from fraud detection to shopping, building a network where machines can make purchases

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    Visa Is Letting AI Spend Your Money and Changing How the World Buys

    Visa’s transformation into an AI-first company has been years in the making. Ramping up this year, the payments giant has woven artificial intelligence into nearly every part of its operations, from fraud detection and data management to software engineering and product design. “AI is part of the fabric of the company,” said Rajat Taneja, Visa’s president of technology, to Fortune. “In everything we do, we’re using it internally, and we’re using it to create intelligent and smarter, more capable products for our customer base.”

    That shift has required major investment and architectural rethinking. Over the past decade, Visa has spent $3.5 billion on its AI and data platform, and about $12 billion on technology overall. The result is a system that manages more than 400 AI solutions across risk, cybersecurity, and operations, powering 630 million daily transactions with millisecond precision. Sam Hamilton, Visa’s senior vice president of data and AI, told VentureBeat that the company maintains more than 300 active AI models and “hundreds of petabytes of data,” monitored constantly to prevent drift and bias.

    Visa’s internal AI framework includes a hybrid compute strategy that mixes on-premise and cloud infrastructure to balance performance and cost. “We evaluate everything on total cost of ownership and performance per dollar,” Hamilton said. “It’s not about chasing the latest hardware- it’s about optimizing for latency, security, and scalability.”

    AI is also changing how Visa’s workforce operates. The company has built more than 100 internal AI applications to support functions such as software development, dispute management, and finance. Since early 2023, every employee has had access to generative AI tools, including Microsoft Copilot and internal large language models, to help with coding, data analysis, and communications. “We’re seeing productivity improvements across the business,” CEO Ryan McInerney said in a CNBC interview. “In engineering, in marketing, in finance, and HR, it’s been a real unlock.”

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