In what ways is AI applied in finance, and how does it function?
AI in finance brings together several advanced technologies like machine learning, natural language processing (NLP), and deep learning to help finance teams work more efficiently. These tools can handle repetitive tasks automatically, improve the accuracy of financial data, and uncover insights that help teams make better decisions.
Here are some practical examples of how these AI technologies are used in finance departments:
Machine learning algorithms work by studying large sets of data to spot trends, predict what might happen next, and suggest actions. In finance, these tools are especially useful for tasks like detecting fraud and managing risk because they can learn to recognize unusual patterns that might signal a problem.
Natural language processing (NLP) helps computers understand and process written financial information. For example, NLP can scan and read documents like invoices or purchase orders, pick out important details such as supplier names, dates, and amounts, and organize that information neatly. It can also look for suspicious wording or transactions hidden in text.
Deep learning goes a step further by analyzing more complex data — including past records and even images. In finance, it can study years of supplier data, industry trends, and past disruptions to predict which suppliers might face issues in the future. This helps teams focus their risk assessments where it matters most.
Generative AI (GenAI) is a type of AI that can create new content like text or images by learning from existing data. In finance, it acts like an intelligent assistant that can quickly analyze large amounts of data, recognize patterns, and automatically produce useful documents, reports, or even draft contracts.
How is AI used in finance?
Now that we know how different AI tools work in finance, it’s easier to see where they help most. Finance teams often use AI to handle repetitive tasks like entering data, processing expense reports, and managing invoices. This saves time so staff can focus on more important work.
AI is also used for analyzing data, forecasting revenue, and helping leaders make better decisions by spotting trends and patterns that might otherwise go unnoticed. Plus, AI can help detect fraud and make it easier to stay compliant with regulations.
In Coupa’s second annual Strategic CFO Survey, they spoke with 500 CFOs from North America and Europe about AI in finance. All of them said they already use AI to lower costs and boost productivity. Nearly half (45%) plan to invest even more in AI to help their businesses grow.
Right now, most CFOs said they use AI for automating accounts payable (31%), followed by procurement (29%), and managing cash and liquidity (28%). Looking ahead to the next 6–12 months, they plan to invest most in accounts payable automation (34%), then procurement (31%), and third-party risk management (29%).
Examples of AI in finance
Many finance leaders today are already using AI tools to make their work faster and more accurate. By automating manual tasks, AI helps reduce risk and boost overall financial performance. Here are a few practical examples of how AI is making a difference in finance:
Detecting fraud and ensuring compliance:
AI helps spot suspicious transactions automatically, like payments that don’t match a user’s usual spending habits or come from unexpected locations. It can also compare invoices against purchase orders and past payment records to find duplicates or errors that people might miss. Beyond this, AI constantly monitors financial transactions and communications to catch anything that might break financial rules, helping companies stay compliant and avoid penalties.
Automating contract review and data extraction:
Instead of teams spending hours reading and typing out details from contracts, AI can quickly pull out important information like payment terms, obligations, and compliance requirements with high accuracy. This not only saves time but also reduces errors and makes financial reporting more reliable. Plus, it allows finance teams to spend more time on strategy and less on paperwork.
Benchmarking against peers:
AI can analyze large sets of performance data and compare a company’s results to others in the industry. This shows where a business is doing well and where there’s room for improvement. By highlighting these insights in real time, AI helps finance teams find ways to cut costs, use resources better, and adjust strategies to stay competitive. It also keeps them updated on industry trends and best practices, supporting smarter decision-making and better profit margins.
How AI benefits finance teams
AI brings powerful benefits to finance, helping teams work smarter, faster, and with fewer resources. Here are some of the biggest advantages:
Greater efficiency and lower costs:
AI handles routine tasks like entering data, processing invoices, and preparing reports automatically. This means finance teams can spend less time on manual work and more time on strategic analysis and planning.
Stronger fraud detection and risk control:
By instantly scanning transaction data, AI can spot unusual activity or patterns that might point to fraud. It also looks at historical trends and market data to help teams predict risks and make better decisions before problems arise.
Quicker, data-driven decision-making:
AI can process and analyze huge amounts of information far faster than people can. This helps finance teams uncover trends they might miss and provides actionable recommendations, improving forecasting and planning.
Simpler compliance:
AI can collect and organize data needed for compliance reports, saving time and helping companies stay ahead of changing regulations without extra effort.
Better industry benchmarking:
AI compares a company’s performance against thousands of others, highlighting where it can cut costs, become more efficient, or boost profits.
Confidence during economic shifts:
By tracking market trends and analyzing real-time data, AI helps finance leaders navigate uncertainty and adjust their strategies quickly.
In addition, many CFOs see big potential in Generative AI (GenAI). According to Coupa’s 2024 Strategic CFO Survey:
- 37% think GenAI will help detect fraud more effectively.
- 36% expect it to improve workflow efficiency.
- 35% believe it will provide deeper data insights and help evaluate suppliers better.
Overall, AI and GenAI are reshaping finance making teams faster, smarter, and more resilient.
Why the power of AI depends on the data behind it
AI can transform finance making processes faster, uncovering insights, and helping teams make smarter choices. But what truly makes AI effective isn’t just the technology itself; it’s the quality of the data that trains it.
Think of AI like a chef: no matter how skilled, the outcome depends on the ingredients. If AI is trained on scattered data pulled from random internet sources, short-term surveys, or small customer groups, its insights can be incomplete, biased, or even misleading. These gaps mean the AI might miss critical trends or suggest actions that don’t fit the real business context.
On the other hand, AI built on rich, proprietary datasets collected ethically and securely over years from thousands of businesses and millions of transactions has a far stronger foundation. This depth and diversity of data helps AI spot patterns more reliably, make balanced predictions, and support truly informed decision-making.
For finance teams, this means it’s not enough to use AI tools; it’s essential to understand where the data comes from and ensure it’s comprehensive, confidential, and responsibly sourced. In the end, AI’s real value comes not just from advanced algorithms, but from the quality, history, and integrity of the data that fuels it.
AI-driven finance: A smarter way to manage every dollar
Imagine a single platform that brings together every part of your company’s spending from supply chain and inventory to contracts, procurement, invoices, and payments all under one digital roof. That’s what Coupa’s AI-powered Total Spend Management platform offers: a central hub that gives finance teams complete visibility and control over where money goes and how it’s used.
By combining automation with powerful AI, this platform doesn’t just show what’s happening; it helps finance leaders act with confidence, even when the market is uncertain. It does this by analyzing real-time spending data and comparing your company’s performance against thousands of others, highlighting new opportunities to reduce waste, boost profitability, and become more sustainable.
What makes it even more effective is the depth of data behind it: the AI has been trained on over $8 trillion worth of real-world spending data gathered over nearly two decades from around 10 million buyers and suppliers. This rich “community intelligence” helps the platform offer insights that aren’t generic but deeply relevant tailored to your company’s unique rules, supplier relationships, market conditions, and operational challenges.
The result? Smarter, faster decisions that go beyond simple cost-cutting to deliver real, measurable value across the entire procure-to-pay process helping companies strengthen margins, reduce risks, and run more profitably.
Conclusion
AI is not just another tool for finance teams, it's a transformative force redefining how organizations operate, plan, and grow. As we’ve explored, AI helps automate routine work, spot hidden risks, and provide actionable insights that empower CFOs and finance teams to make better, data-driven decisions. Technologies like machine learning, NLP, deep learning, and Generative AI (GenAI) are already streamlining processes, improving compliance, and enhancing accuracy across financial operations.
Yet, the real power of AI doesn’t come from algorithms alone; it depends on the quality and depth of the data that fuels it. AI built on ethically sourced, extensive real-world data can deliver precise, reliable insights that finance leaders can trust.
Platforms like Coupa’s Total Spend Management demonstrate how AI can bring everything together from supply chain and procurement to invoicing and payments into a single, intelligent ecosystem. By learning from trillions of dollars in transactions and millions of suppliers, such platforms turn complexity into clarity, helping organizations navigate uncertainty with confidence and drive measurable business value.
In today’s fast-changing market, finance leaders who embrace AI and GenAI aren’t just keeping up, they're gaining a strategic edge, unlocking new efficiencies, and shaping a more resilient, future-ready finance function. AI is not just supporting finance, it's actively reshaping it for the better.