The evolution of artificial intelligence (AI) has been remarkable, beginning with the conceptualization of neural networks in 1943 and progressing to the birth of machine learning (ML) in 1959 and the advent of deep learning in 2006. This trajectory led to the era of Generative AI (GenAI), which emerged around 2017. GenAI refers to the subset of AI that focuses on creating new content, from text to images, by learning from vast datasets. This leap forward enables machines to not only interpret data, but also to generate original outputs that can mimic human creativity and reasoning.
As the technology becomes more sophisticated, consumers are increasingly integrating large language models (LLMs), an application of GenAI, into their daily lives. From asking virtual assistants for weather updates to receiving personalized recommendations, the comfort and confidence in using such technology are on the rise. This adoption signifies a shift in the public's perception of AI, viewing it as a reliable and integral part of modern living.
Part of this shift can be seen in how GenAI is revolutionizing strategic business thinking, enabling businesses to unlock new revenue sources, achieve productivity gains, and innovate existing business models, ultimately leading to value creation. In particular, firms and departments dealing with finance and accounting can leverage GenAI to enhance data entry and reconciliation, enrich forecasting and analysis, and fortify risk management.
GenAI applications in the finance function
The finance function is pivotal in supporting optimized enterprise decisioning – and rethinking enterprise structures through the lens of GenAI is key to unlocking a spectrum of new possibilities for value creation. Knowledge management and decision support in particular are among the most potent use cases for scaled AI capabilities.
GenAI can enhance an organization's data value by asking better questions, optimizing multi-variable choices, and enabling actions at scale. In addition, GenAI can write code on demand to extract information from data sources, create reports with appropriate data visualization, and provide persona-based analysis. It also enables conversations with virtual agents for a deeper understanding of results.
In monthly financial reporting cycles, analysts would traditionally spend hours writing code to extract data from various sources, compiling it into spreadsheets, and then painstakingly creating visualizations. GenAI allows them to input their requirements, after which the AI writes the necessary code on demand, pulling information from databases, cloud storage, and even real-time market feeds.
The data is not just tabulated – it's transformed into compelling visual reports that highlight key financial metrics and trends. Moreover, GenAI can provide persona-based analysis, tailoring insights to the specific needs of each stakeholder. The CFO receives a high-level overview emphasizing strategic implications, while line managers get detailed breakdowns relevant to their departments.
Content creation, a repetitive and complex task, has also been redefined by GenAI. Finance teams can leverage GenAI to assist in generating various analytical documents. Variance reports, budgets, and forecasts are produced with a level of detail and accuracy that was previously unattainable. GenAI sifts through historical data, identifies anomalies, and presents findings in a clear, concise manner. Moreover, GenAI can extend its capabilities to responding to common queries from colleagues or clients. Instead of drafting individual responses, finance professionals can rely on GenAI to provide accurate and contextually relevant answers, freeing up their time for more strategic tasks.
GenAI has become an essential collaborator in meetings and project planning as well. It helps document discussions, distilling them into actionable items and comprehensive plans.
Last but not the least, perhaps the most transformative application of GenAI within the finance function is in forecasting. A GenAI model can take in vast amounts of historical financial data and current market trends to predict future performance with remarkable accuracy. It identifies patterns that might elude even the most experienced analysts and uses natural language processing to incorporate insights from news articles and external data sources. This ability allows organizations to anticipate market movements and adjust their strategies proactively. Whether in terms of revenue, expenses, profit, or cash flow, forecasts can provide more than just numbers — they can become strategic tools that inform decision-making at the highest levels.
Realizing GenAI advantages
To fully realize the advantages of GenAI in finance and accounting, companies need to enhance their finance and accounting functions with innovation intelligence, invest in infrastructure and develop talent in AI while putting proper governance and controls in place.
Amidst the possibilities and efficiencies that AI can create for the finance function, blind optimism and hype around this disruptive technology can have a counterproductive impact on a business that is unaware of its risks. To avoid this, companies can take the “innovation intelligence” approach through implementing planning, education and an agile test and learn strategy.
Another critical determinant of an organization’s success will be how they enhance their comprehension of and refine their data infrastructure. Companies should have a tech stack with a solid foundation and support from experts to ensure their legacy data and technologies are unimpeachable before adding any GenAI applications on top of existing systems.
Based on the EY 2023 Financial Services GenAI Survey, 44% of leaders identify access to skilled resources as a barrier to GenAI implementation. Part of the solution is to deploy upskilling programs that can equip the current workforce with the necessary skills in an increasingly AI-centric world. The human role of AI implementation is just as important as technology infrastructure.
The GenAI imperative in the finance function
Incorporating GenAI into finance is not just an option – it has become an imperative for long-term value creation. However, while it brings significant gains, it is also crucial to be mindful of potential risks. While aligning GenAI across the organization will be essential to unlock greater value, organizations must consider how GenAI can be used not only to transform the finance function, but also to redefine the future of business decision-making.
Maria Kathrina S. Macaisa-Peña is a Business Consulting Partner and the PH Finance Fields of Play Leader of SGV & Co.
This article is for general information only and is not a substitute for professional advice where the facts and circumstances warrant. The views and opinions expressed above are those of the author and do not necessarily represent the views of SGV & Co.
