G eoffrey Hinton is one of the “godfathers” of artificial intelligence, critical in the development of deep learning, backpropagation and much more. In 2024 he was awarded the Nobel prize in physics in recognition of his immense contributions to the field of computer science. Not bad for someone who started his career with the aim
The future of finance: how AI and data can boost business performance – Financial Times
The office of the CFO is going through a new phase of transformation driven by artificial intelligence (AI). AI impacts how finance teams complete daily tasks and operations, and it has the potential to do much more. From automating repetitive tasks to uncovering hidden patterns in data and surfacing insights, AI has the potential to streamline operations, optimise workflows and improve decision-making.
AI uses a combination of techniques, such as machine learning algorithms, natural language processing (NLP), deep learning and generative AI to automate time-consuming tasks to improve accuracy of financial data and provide valuable insights to make smarter financial decisions. Given these applications, many finance teams may already be using AI within their systems and processes without even realising it.
Putting AI to use
With the understanding of how different AI technologies work in finance, there are a few use cases that come to mind. AI is commonly used to automate tasks like data entry, expense report processing and invoice processing with the goal of freeing up resources. Additionally, finance leaders use AI for data analytics, revenue and predictive forecasting, decision-making to identify missed trends and patterns, as well as being trained to detect fraudulent activities and simplify regulatory compliance.
In its second annual Strategic CFO Survey, spend management software company Coupa interviewed 500 CFOs across North America and Europe to understand how finance leaders are currently using AI and how they’ll invest in AI in the future. According to the survey, 100 per cent of finance leaders reported that they’re already using AI to cut costs and increase productivity across different business areas, with nearly half (45 per cent) planning to invest in AI to drive growth. Finance leaders (31 per cent) reported that they’re currently using AI in AP automation, followed by 29 per cent who are using AI in procurement, with 28 per cent of CFOs leveraging AI in cash and liquidity management. By 2025, finance leaders plan to make the most AI investments in the AP automation (34 per cent), followed by procurement (31 per cent) and third-party risk management (29 per cent).
How AI is enhancing financial operations
Many finance leaders have already integrated AI tools into their processes to increase efficiency by reducing manual tasks, enhance accuracy, reduce risks and improve financial performance. Common examples of how AI is used in finance include detecting fraud and non-compliant behaviour, automating contract analysis and data extraction, as well as benchmarking against peers.
AI offers several advantages for finance teams to do more with less and complete tasks with more precision. Some of the key benefits include:
- Increased efficiency and reduced costs: AI automates repetitive and manual tasks like data entry, invoice processing and generating financial reports. This frees up resources and staff for more strategic activities and analysis.
- Enhanced fraud detection and risk management: by quickly analysing transaction data in real time to identify suspicious transactions or patterns that might indicate fraudulent activity, AI helps finance teams prevent financial losses and protect customer information. By analysing historical data, market trends, patterns and shifts, AI enables smarter decisions through predictive analytics to minimise risks.
- Faster and more accurate decision-making: with the ability to analyse vast amounts of data, AI is able to identify patterns that finance teams might miss and make informed recommendations. AI-powered analytics also provide real-time prescriptive insights, enabling better forecasting.
- Streamlined regulatory compliance: by automating tasks such as data collection and reporting, AI can simplify regulatory compliance. This saves time and valuable resources while ensuring companies remain compliant ahead of any regulatory changes.
- Better industry benchmarks: AI-powered insights enable businesses to benchmark their performance against a global community to reduce risk, increase efficiencies, and improve margins and profitability.
- Navigate macroeconomic uncertainty with confidence: with automation, analysis of market shifts and patterns, and visibility of data, AI can provide enhanced recommendations to confidently navigate complex business issues and disruptions.
In addition to these advantages, CFOs and finance leaders hope to reap more benefits with generative AI. According to Coupa’s 2024 Strategic CFO Survey, 37 per cent of finance leaders believe generative AI will provide strategic advantages to fraud detection, while 36 per cent believe it will enhance workflow process optimisation. Additionally, 35 per cent of CFOs say generative AI will provide strategic advantages to both data analysis and insights and supplier evaluation.
High quality data for high quality results
And while AI provides a variety of benefits and is a central component of financial maturity, not all AI should be treated the same. The right data is crucial because AI solutions designed to support smarter decisions are only as good as the data they’re built on. Data scraped off the internet or based on surveys collected for a few months – or from a limited number of customers – and run through public large language models (LLMs) will train AI-driven solutions that reflect these limitations.
Companies must understand the data organisations use and look for providers that use propriety, secure and confidential data that have been safely and ethically sourced for years, from thousands of customers and millions of suppliers. By prioritising robust data that’s collected in this way, organisations can ensure that their AI solutions deliver impactful insights, empowering them to make smarter business decisions that drives growth for the future.
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