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Amazon uses generative AI to manage its finances
Amazon.com Inc. is ramping up its use of generative artificial intelligence across its finance teams, as many companies look for ways to effectively move from testing and experimenting with the technology to prime time.
Amazon.com is ramping up its use of generative artificial intelligence across its finance teams as many companies look for ways to effectively move from testing and experimenting with the technology to prime time.
The e-commerce giant initially adopted rules-based systems, one of the first forms of AI that uses a set of rules to solve problems and make decisions, in its financial organization, which it then enhanced with machine learning. Generative AI now assists finance employees with more complex analyses.
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The e-commerce giant initially adopted rules-based systems, one of the first forms of AI that uses a set of rules to solve problems and make decisions, in its financial organization, which it then enhanced with machine learning. Generative AI now assists finance employees with more complex analyses.
Their finance teams are turning to generative AI in areas such as fraud detection, contract review, financial forecasting, staff productivity, interpretation of rules and regulations, and tax-related work, measures in part aimed at reducing costs, increasing efficiency and increase accuracy. company executives said. These use cases are in a mix of experimentation and implementation stages.
“While experimentation and understanding the technology are things we really want to accelerate, deploying this into production and making sure we’re in a well-controlled situation is very, very important to us,” said Dave George, vice president of financial technology at Amazon.
More broadly, Amazon is shifting its focus to AI innovations, with the capabilities of its Amazon Web Services cloud computing unit driving a surge in sales across the company in the most recent quarter.
Amazon said it expects cash capital expenditures to increase significantly this year as it makes investments in technology infrastructure, specifically generative AI efforts. The company recorded $13.9 billion in cash capital expenditures during the first quarter, up 6% from the same period a year ago. Amazon Web Services accounted for 17.5% of Amazon’s $143.31 billion in revenue for the quarter, up from 16.8% of its $127.36 billion in the same period a year ago.
Creating value from AI
The tone has changed in recent months across industries for financial executives navigating generative AI, from fascination with technological advances to a serious focus on its application and generating value from it. Some of the biggest technology companies continue to be more aggressive and more willing to embrace generative AI.
Amazon’s internal tax people also make use of the technology. The tax compliance team created a tool that uses generative AI to help validate incoming invoices for value added taxes, which companies typically pay at different stages of producing a good or service.
When the team receives an invoice, the tool automatically checks the validity of the invoice before payment occurs, George said. Instead of manually validating these invoices, generative AI allows the team to automate the process, he said.
The many use cases
Generative AI also helps Amazon review the many contracts it has with suppliers and customers. A tool takes into account Amazon’s standard benchmark data, policies, and past contract history to determine changes needed to accommodate contracts. The AI then extracts key information for more streamlined human review.
“There’s a benefit to that because humans aren’t dealing with very, very dense contracts,” said George, who leads the financial organization’s two generative AI working groups, one focused on innovation and the other on security.
The company trains models on vast datasets of financial transactions to detect and prevent fraud and financial anomalies. The models can identify patterns and irregularities that would be virtually impossible for humans to detect, said John Felton, chief financial officer at Amazon Web Services.
“This enhanced fraud detection capability not only protects our bottom line, but also helps us ensure compliance,” said Felton, who, along with George, reports to the company’s CFO, Brian Olsavsky, who has held the role since 2015. The company declined to comment on estimated cost savings.
These controls around transactions increasingly incorporate generative AI and models that can interpret and explain the findings. Staff who previously worked with a random sample now focus on a list of the highest-risk transactions enhanced by generative AI, George said.
Before generative AI, employees worked with a random sample, he said. “Humans now have a much more rewarding job,” George said.
One potentially promising area of applying AI to corporate finance is making complex queries to retrieve certain data; for example, the ability to quickly obtain sales information for new customers in Mexico who subsequently placed orders within a month, said Mark D. McDonald, a senior director at consulting firm Gartner who focuses on AI in finance.
AI idle
But for many companies, finance has been slow to adopt technology compared to other parts of the business such as sales, marketing and customer support. “Finance tasks are rooted in number analysis, and generative AI is a technology rooted in word analysis,” McDonald said, adding that machine learning is best suited for number analysis.
Amazon is one of the few companies that has built its own large language models from scratch. Amazon Web Services said tens of thousands of companies are using its AI application development platform, known as Bedrock. Most companies pay to use proprietary models from vendors like OpenAI and tweak those models as needed, or build their own generative AI tools using open source models.
AWS employees use an AI app builder in Bedrock to automate daily work tasks, such as helping write documents and summarizing meetings, Felton said.
One of the big advantages of generative AI is the opportunity to increase employees’ personal productivity by allowing them to expand their skills and engage in more critical thinking, George said. Accounting and finance departments in companies across all industries have long been areas filled with repetitive tasks.
But George also acknowledged a “valid concern” from employees about technology’s potential effect on job security. “I think there is a sweet spot where we can get the benefit of generative AI from an enterprise perspective as well as from a human experience perspective,” he said.
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