[Cloud Goods Sharing] CFO Guide: Staying Ahead in the AI Era

Today, departments across enterprises are increasingly prioritizing the integration of artificial intelligence (AI) capabilities into their operations—and finance is no exception. AI is helping finance professionals automate labor-intensive tasks like data reconciliation, month-end closing, and data conversion. Consequently, the traditional tools and skills once critical to these professionals are undergoing a transformation. In some cases, they are being significantly enhanced through the integration of machine learning algorithms, data analytics, and predictive modeling, propelling the finance function toward more strategic and data-driven roles.

One reason CFOs are turning to AI is the need to bridge talent gaps. Many have already adopted AI tools to address staffing shortages and augment existing finance teams. Yet, as automation and AI usage grow, finance professionals inevitably face concerns: “How do I develop my skills to stay ahead in the AI era?”

The answer lies in understanding and cultivating essential skills—those that enable finance professionals to maintain their value and core role. Here are five key skills:

01

Deep Industry Expertise

AI tools designed to empower finance users are trained on accounting and financial theory. However, nuanced industry expertise isn't documented in textbooks or publicly available materials that AI can learn from. Thus, deep industry knowledge is a specialized skill possessed only by finance professionals with extensive experience in their field.

For instance, finance in manufacturing is complex, focusing on production processes and supply chains, while retail emphasizes sales analytics and customer behavior—two vastly different areas. AI can offer insights, but it requires the financial team's deep knowledge to provide context for these tools. It is by leveraging their industry-specific expertise that finance professionals can ask the right questions, guide AI model development, and accurately interpret AI-based results based on industry nuances. This knowledge also underpins numerous tasks: making informed decisions; forecasting industry trends; identifying subtleties others might overlook.

02

Mastering Core Financial Processes

While AI can accelerate financial processes, it remains crucial for finance professionals to understand the underlying principles behind these tasks. They must possess a solid grasp of matters like closing the books, financial planning, revenue recognition rules, and regulatory standards to ensure AI-generated outcomes are grounded in sound financial practices. For instance, an AI tool might predict a revenue surge based on historical data and market trends, but finance professionals must validate these forecasts against upcoming product launches or internal challenges the AI may not account for. This is only possible when finance professionals understand the composition of financial processes and the theoretical foundations behind established protocols.

03

Basic Programming Skills

Today, technology drives business, and programming is no longer the exclusive domain of engineers. While programming may seem daunting at first for finance professionals, it is actually a skill that can be learned and mastered even without deep technical expertise. Basic knowledge of languages like Python and R—especially for financial modeling and AI—can set finance professionals apart. Additionally, ERP systems such as Oracle NetSuite offer robust APIs that enable programmatic access to financial data.

Finance users with programming skills can automate data collection, cleaning, and visualization, significantly boosting team efficiency. Imagine automating tedious financial processes like manual spreadsheet updates, running Monte Carlo simulations to assess financial risks, or creating internal dashboards for financial KPIs—you'd become the star performer on your team. Even when you need to engage data scientists or programmers with deep technical backgrounds for more complex tasks, having foundational knowledge enables more substantive conversations.

04

Data Visualization

People remember and connect with narratives more easily than memorizing arguments or financial figures. However, in finance, all narratives must be grounded in data. Given the complexity and sheer volume of financial data, traditional presentation methods like spreadsheets or tabular reports can overwhelm executives. What they truly need are concise, clear, and actionable insights to support informed decision-making. Therefore, finance professionals should master data visualization to effectively communicate complex information in a clear and compelling manner. This requires not only skills in data analysis, storytelling, and foundational technology, but also strong design principles and aesthetic sensibility.

05

Data Science Literacy

Many businesses make decisions by analyzing vast amounts of data: historical sales figures, online search trends, customer reviews, global economic indicators, competitor product launches, and more. Traditional financial models may not fully leverage this rich information.

By leveraging data science expertise and predictive analytics tools, finance users can generate data-driven forecasts for key outcomes—such as income statements detailing revenues and expenses. Additionally, these techniques help identify anomalies within vast datasets of payments, invoices, and journal entries.

You might wonder: Data science? Isn't that reserved for data scientists and tech specialists? In fact, learning foundational data science concepts is easier than ever thanks to online resources. For finance professionals, understanding the fundamentals builds greater trust in AI-driven insights and enables better optimization of outcomes. By mastering the basics, you can consolidate disparate datasets, select the most appropriate model (whether time-series forecasting, regression models, or neural networks), and grasp the key drivers influencing results. While AI streamlines the process, a finance professional's foundational knowledge is essential for correctly interpreting and relying on AI outcomes.

Data science requires the right analytical tools, and the Oracle NetSuite SuiteAnalytics platform delivers comprehensive insights for finance users. It provides real-time data on operations and finances across all business functions. Oracle NetSuite's Planning and Budgeting solution equips financial analysts with statistical models to run what-if scenarios, forecasting metrics like revenue and expenses based on various possible outcomes. Oracle NetSuite also features data visualization capabilities that transform complex datasets into compelling narratives—vital for finance teams to communicate their insights and analysis.

As AI continues reshaping the industry landscape by integrating into finance workflows, professionals must evolve with the times. By mastering these five essential skills, finance professionals can ensure they not only keep pace with industry transformation but also lead the future of finance.