The future of FP&A with AI
Webcast summary
Artificial intelligence (AI) is transforming financial planning and analysis (FP&A), enabling organizations to drive greater value and deliver actionable insights faster than ever before. AI capabilities are reshaping the roles of humans and technology in the finance organization. Adopting AI in FP&A processes can accelerate data-driven outcomes, provide real-time insights, and add top-line and bottom-line value. AI will shape the future of FP&A by automating tasks, enabling advanced analytics, and allowing finance professionals to focus on strategic decisions.
The webcast highlighted how AI is transforming FP&A, enabling faster, more accurate insights and freeing up humans to drive strategic value as business partners.
Panelists discussed the following topics:
Transforming FP&A with AI and the role of humans
AI and GenAI are being used to automate routine FP&A tasks. In consumer organizations, AI checks point-of-sale data for accuracy and tagging. GenAI can automate accruals and prepaids, while AI agents can handle contracts by identifying exceptions in accounts payable outsourcing (APOs), invoices, and contracts. AI can also automate book closings, generate variance explanations and insights, create key performance indicators (KPIs) and key risk indicators (KRIs), and prepare responses for investor questions during analyst calls.
With AI handling routine tasks, humans can focus on driving business value. AI provides analyzed data and recommendations to humans, who then make decisions based on their business knowledge. This requires trusted AI and governance. The future involves routine work being performed by automated team members, while humans concentrate on enhancing the top and bottom line of the organization. Humans will still be required to validate AI outputs and ensure they align with business needs.
The world now demands instantaneous, on-demand forecasting. Traditional models based on monthly or quarterly time series are being replaced by daily forecasting capabilities. This allows organizations to model impacts on financial statements, supply chain, and commodity sourcing in real-time. AI agents provide data and analysis and recommend actions to humans for decision-making.
Intelligent planning core capabilities
Predictive and prescriptive analytics harness transaction data to predict outcomes and recommend actions, replacing traditional trending and driver-based forecasting methods.
Real-time scenario modeling for agile decision making: Scenario modeling has become critical for real-time crisis response, analytics, and decision making in the face of unexpected events such as hurricanes and tariffs. The ability to rapidly model scenarios is key for agile financial forecasting. In the last five years, scenario modeling has become the hottest capability for real-time decision making.
Interconnected business planning across functions: Financial planning is no longer siloed, but interconnected with supply chain, demand, marketing, and strategic workforce planning. Automatically generating profitability insights across products, customers, brands, and categories is now possible. The shape of the workforce should be determined based on interconnected planning.
Performance-centric capabilities: While focusing on advanced capabilities, organizations cannot lose sight of performance-centric capabilities. AI can automatically serve up insights for monitoring and measuring business performance, identifying M&A opportunities, complementary brands, and products for rationalization.
Practical, targeted insights: Consumer organizations still need to run the business by managing product, customer, brand, and category profitability. AI enables these insights to be generated automatically.
Future FP&A organizational structure
Traditional budgeting, forecasting, and reporting are being centralized into a capability hub that leverages AI and technology. This eliminates the need for dedicated planners in every function and focuses on reducing cycle times and improving accuracy. The hub handles first-pass forecasting and budgeting, allowing FP&A to shift to strategic business partnering, providing insights, running scenarios, and identifying opportunities and risks.
FP&A's performance metrics should align with business outcomes such as growth and profitability optimization. FP&A teams will be leaner, augmented by digital agents and AI, and traditional roles will be upskilled to focus on strategic capabilities.
Getting started with adopting AI in FP&A
The AI in FP&A journey starts with redefining the FP&A strategy and evaluating gaps to leading practices. This helps identify where advanced technologies and modeling techniques can be used. Organizations should assess their current state of technology and AI within FP&A to determine the starting point.
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The future is now
Rapid advancements in AI provide finance leaders with an opportunity to enhance their FP&A processes. It is an opportune moment to re-imagine your FP&A function by utilizing AI capabilities and enabling the team to strategically support the business.
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