For CFOs, finding the most effective way to use AI in finance is a priority now, not someday. Nearly two-thirds of CFOs say their organizations have a strategic need for AI. According to a June survey by Duke University's Fuqua School of Business, the Federal Reserve Bank of Richmond and the Federal Reserve Bank of Atlanta, companies aim to automate tasks that are typically performed by employees over the next 12 months.
The majority of CFOs planning automation projects in the Duke/Fed survey expect to employ AI to perform a wide range of tasks, including data reconciliation, month-end processing, and data transformation (converting raw data into a uniform format or structure). These are complex and ambitious endeavors. But as CFO work becomes more strategic and data-driven, and AI adoption accelerates, they fit perfectly into the capabilities CFOs will need.
What skills will finance professionals need to hone if they want to succeed in this new AI augmented reality? Here are the five most important.
Industry Expertise
AI tools for finance are trained on accounting and finance tactics and theories. But nuanced industry expertise isn't found in textbooks or publicly available documents, which are the data sources from which AI can learn. Finance experts are the ones who can bring that knowledge, which is an essential component to decision-making. For example, manufacturing finance focuses on production processes and supply chains, while retail finance focuses on sales analytics and customer behavior. Using industry-specific knowledge, CFOs can ask the right questions, guide the development of AI models, and accurately interpret AI-driven outputs.
Mastering Core Financial Processes
AI can accelerate processes, but finance teams need to oversee its correct execution. Finance professionals need a deep understanding of areas such as financial close, financial planning, revenue recognition rules, and regulatory standards to ensure that AI-generated outputs are rooted in sound financial practices.
Basic coding skills
Coding isn't just for engineers. Basic knowledge of languages frequently used in financial modeling and AI, such as Python and R, can help you stand out as a finance professional. A basic understanding of coding can also enable more informed conversations with data scientists and programmers. Additionally, ERP systems can offer robust APIs, allowing programmable access to financial data to automate data collection, cleansing, and visualization.
Data Visualization skill
Presenting complex and voluminous financial information to non-finance executives in spreadsheets and tabular reports can leave them overwhelmed. Finance professionals must master data visualization to communicate complex information through data dashboards, interactive reports, charts, and other visual representations. This requires expertise in data analysis and storytelling, as well as fundamental technical skills. A good sense of design and aesthetics is also important.
Data Science Insights
Similarly Beyond coding, data science knowledge helps finance professionals work with AI to analyze vast amounts of data. Understanding the fundamentals helps finance executives integrate different datasets, choose the best model (time series forecasting, regression models, neural networks), and understand the key factors that influence the results. AI streamlines this process, but finance professionals' fundamental knowledge is essential to correctly interpret and trust the AI results.
Want to learn more about the skills finance leaders need as AI transforms the finance industry? Download the full CFO AI Survival Guide here.
