A host of macroeconomic challenges, from evolving regulations to geopolitical tensions, are creating risks for economies, industries and businesses around the globe. Organisations seeking to navigate these complex issues successfully are leaning harder than ever on their chief financial officers (CFOs) and finance functions to help them find innovative ways to increase operational efficiency and safeguard their financial health while driving sustainable growth.
As they do this, it means many of those businesses are also relying on AI in some capacity to help inform and guide their decision-making and strategy-setting. In fact, according to the Global AI in Finance Report, 66% of Chinese enterprises have already begun actively applying Artificial Intelligence (AI) in their finance functions.(1) The widening embrace of AI by finance organisations is a positive trend for companies aiming to manage the impacts of macroeconomic challenges more effectively. AI-enabled finance functions can reshape how businesses make critical decisions to respond to inflation, interest rate volatility and many other issues that create risk and economic uncertainty.
By implementing powerful tools like machine learning, predictive analytics and automation, CFOs and their teams can:
Deliver more actionable data insights faster
When finance functions have AI tools to analyze large and diverse datasets, they can perform their analyses with greater speed and accuracy. They can also gain real-time insights into financial performance, market trends and economic indicators. The information they glean from their analyses can be crucial for surfacing opportunities for the business to reduce costs, increase efficiency and manage risks without undermining growth and innovation.
For example, with advanced AI capabilities, finance teams can identify inefficiencies in supply chain management and quickly pinpoint remedies such as consolidating suppliers or renegotiating contracts. And with generative AI capabilities, CFOs and their teams can create compelling narratives about financial data and the results of their analyses so stakeholders can absorb complex information more easily and move swiftly to apply those valuable insights for competitive advantage.
Achieve next-level FP&A—a high priority
Economic turbulence can quickly upend traditional planning and budgeting processes. Market instability, supply chain disruptions and rising borrowing costs are just some of the recent challenges that have spurred many finance functions to accelerate their transformation efforts and embrace AI capabilities that can enhance their agility and equip them with more foresight.
For instance, integrating AI into an enterprise resource planning (ERP) system can revolutionize financial planning and analysis (FP&A). While ERP systems handle the “what” of financial data (e.g., transactions, balances), FP&A focuses on the “why” and “what’s next.”
With machine learning algorithms and advanced analytics in the mix, FP&A teams can process vast amounts of data, including unstructured data, to identify trends and anomalies they might otherwise miss. The result is more accurate financial models and, here again, faster and more data-driven decision-making.
Create dynamic financial models that reflect current conditions
To navigate macroeconomic challenges with confidence, businesses must have the support of effective business planning and scenario modeling. However, traditional financial models can fall short when environments become volatile. That’s because they often rely on historical data and static assumptions.AI-enabled finance functions have the advantage of using real-time data to adjust their financial models to better reflect what’s happening with current market conditions. They can also simulate economic scenarios to assess the potential impact of these situations on the business. For example, they can use AI to model how different interest rate levels, inflation rates and geopolitical events could potentially impact the cash flow, profitability and overall financial health of the company.
CFOs can, in turn, use this same information to help the business avoid or mitigate risk and develop more effective contingency plans. (The top use of AI for CFOs, according to the aforementioned Forbes survey, is risk management.) They can also use generative AI capabilities to distill complex data into visualisations and reports for the executive team, which can help to enhance decision-making as well as cross-functional collaboration.
Provide more accurate, reliable forecasts
Accurate forecasting is a cornerstone of effective financial leadership, and AI can significantly enhance this capability. CFOs and finance teams can improve forecast accuracy and reliability by using predictive analytics powered by machine learning to identify trends and correlations within massive datasets.
Unlike traditional methods that may overlook subtle patterns, AI algorithms can continuously refine predictions by learning from new data. This is why AI-enabled finance functions are well-positioned to help companies anticipate market shifts, predict customer behavior and mitigate risks. For example, with predictive AI capabilities, they can forecast demand fluctuations so the business can produce and manage inventory more strategically to avoid overstocks or shortages.
Allocate resources more strategically to support strategic priorities and enhance the bottom line
An AI-enabled finance function can be instrumental in helping a business become more adept at optimizing how it distributes its resources—including money, time, personnel and materials—so it can reduce costs without negatively impacting quality or performance.
Finance teams can use AI to analyze financial data and predict cash flow fluctuations. And by forecasting periods of high or low liquidity, CFOs can make informed decisions about short-term investments, debt management and working capital adjustments, helping to ensure the business can make the best use of its cash.
Also, organisations can use AI-driven tools to run profitability analyses that diagnose which areas of the business are best suited for cost reductions.AI can also help elevate talent management by analyzing performance data to highlight productivity trends and pinpoint areas for improvement. By analyzing employee performance, skill sets and project demands, AI can recommend optimal staffing levels and resource distribution across departments. With this insight, companies can make sure they are deploying their talent in the best way to support strategic priorities, drive innovation and achieve the desired business outcomes.
Ready to build an AI-enabled finance function?
Whether you want to equip your finance team with AI capabilities, modernize your ERP system, or access specialised skills and resources for other finance transformation projects or priorities, Robert Half can help you achieve your goals.
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