Today’s finance teams are more than just number crunchers. They are pivotal in driving strategic decision-making for growth and profitability, identifying risks and opportunities, and shaping future strategies. As business leaders demand more from their finance departments, many teams are finding themselves overwhelmed by the volumes of data needed to develop insightful recommendations.
From planning and forecasting, to analysis and reporting, finance departments rely on organisational data for meaningful predictions, insights, and indicators. Unfortunately, that data is scattered across the business, making financial forecasting and scenario planning time consuming and inaccurate. CFOs looking to increase efficiency and accuracy have already started looking at AI to automate their most time-intensive tasks, but the benefits of AI go much further than just speeding up data collection.
When properly integrated into finance operations, AI can become a CFO’s secret weapon in the fight against inefficiency, transforming teams into forward-thinking strategists. Using AI allows for faster, more accurate planning and predictions, empowering finance to become a better partner to the business.
Improved forecasting
90% of CFOs say that their biggest challenge is forecasting in uncertain markets. According to Gartner, companies that leverage AI in EPM experience a 30% improvement in forecast accuracy and a 25% reduction in financial close time, but AI’s real power lies in its ability to reveal patterns, uncover hidden risks, and recommend proactive strategies.
Legacy EPM systems were built for stability and predictability, but today’s fast-changing business landscape demands more agility than traditional financial planning tools can provide. AI is fundamentally changing the role of the CFO from a reactive decision-maker to a forward-thinking strategist. Using advanced analytics and predictive modelling, CFOs can simulate scenarios, anticipate disruptions, and identify opportunities before they materialise.
AI allows organisations to analyse vast datasets with greater transparency. This helps CFOs identify optimal timelines, anticipate regulatory changes, and leverage real-time predictive insights. AI-driven scenario planning, for example, can empower finance teams to manage risks more effectively, improve report accuracy, and adapt to market volatility with greater agility.
Accurate account reconciliation
Account reconciliation is a vital yet often challenging task. Traditional reconciliation methods require time and are prone to errors due to manual data entry and verification. AI simplifies the reconciliation process through the automation of repetitive tasks, significantly reducing the risk of human error.
AI uses machine learning, natural language processing, and data analytics to identify patterns and anomalies in large datasets, improving the accuracy of financial matching. This not only accelerates the reconciliation process but also ensures greater accuracy. Since AI can learn from past reconciliation patterns, it continuously improves its accuracy and efficiency, allowing CFOs to guide their organisations with confidence and precision.
For example, AI can detect potential fraud by identifying unusual patterns or transactions, or reduce errors by detecting discrepancies. This doesn’t mean that the entire process is automated, but rather that the AI can help finance teams identify where their expertise is needed most, helping to flag exceptions that require manual intervention, such as unmatched transactions or incorrect amounts.
Proactive decision-making
Businesses that have adopted AI-driven finance processes have seen measurable improvements. The most significant improvement reported by CFOs lies in their ability to make proactive, data-driven decisions that enhance performance, mitigate risks, and capitalise on opportunities.
AI enables dynamic, real-time decision-making that allows companies to changing market conditions. By accelerating re-forecasting cycles, for example, AI allows finance teams can quickly adjust to disruptions such as inflation, supply chain bottlenecks, or shifts in demand. This capability not only enhances operational efficiency but also positions organisations to seize opportunities and thrive in challenging environments.
AI’s transformative capabilities are equipping finance teams with the tools they need to guide strategic decisions and drive resilience across the organisation, eliminating manual tasks to allow them to spend more time on identifying risks, uncovering opportunities, and driving agility. As AI becomes more integrated into financial ecosystems, CFOs will continue to find new ways to optimise their financial planning, forecasting, and decision-making processes, allowing them to spend more time on effective business partnership and strategic leadership.
