10 tasks I wish AI could perform for financial planning and analysis professionals

It’s no secret that artificial intelligence (AI) transforms the way we work in financial planning and analysis (FP&A). It is already happening to a degree, but we could easily dream of many more things that AI could do for us.

Most FP&A professionals are consumed with manual work that detracts from their ability to add value to their work. This often leaves chief financial officers and business leaders frustrated with the return on investment from their FP&A team. However, AI can help FP&A professionals elevate the work they do.

Developments in AI have accelerated tremendously in the last few years, and FP&A professionals might not even know what is possible. It’s time to expand our thinking and consider how we could maximize the potential uses of AI.

As I dream up more ways that AI could help us, I have focused on practical tasks that FP&A professionals perform today. I also considered AI-driven workflows that are realistic to implement within the next year.

1. Advanced financial forecasting: Enables continuous updates of forecasts in real time based on the latest data. Automatically generates multiple financial scenarios and simulates their impacts under different conditions. Uses advanced algorithms to predict revenue, expenses and cash flows with high accuracy.
2. Automated reporting and visualization: Automatically generates and updates reports and dashboards by pulling data from multiple sources in real time. Provides contextual explanations and insights within reports to highlight key drivers and anomalies. Enables user-defined metrics and visualizations tailored to specific business needs.
3. Natural language interaction: Enables users to interact with financial systems that use natural language queries and commands, allowing seamless data retrieval and analysis. Provides voice-based interfaces for hands-free operation and instant insights. Facilitates natural language generation to convert complex financial data into easily understandable narratives and summaries.
4. Intelligent budgeting and planning: Adjusts budgets dynamically based on real-time performance and external factors. Automatically identifies and analyzes variances between actuals and budgets, providing explanations for deviations. Offers strategic recommendations based on financial data trends and projections.
5. Advanced risk management: Uses AI-driven risk models to identify potential market, credit and operational risks. Develops early warning systems that alert to potential financial issues or deviations from planned performance. Helps ensure compliance with financial regulations through automated monitoring and reporting.
6. Anomaly detection in forecasts: Improves forecasting accuracy by using advanced machine learning models that incorporate both historical data and real-time inputs. Automatically detects anomalies in financial data, providing alerts for unusual patterns or deviations from expected behavior. Offers detailed explanations and potential causes for detected anomalies to guide corrective actions.
7. Collaborative financial planning: Facilitates collaboration among FP&A teams and other departments through shared platforms and real-time data access. Enables natural language interactions with financial models and data. Implements AI-driven assistants to answer queries, perform tasks and support decision-making processes.
8. Continuous learning and improvement: Develops machine learning models that continuously learn from new data and improve over time. Incorporates feedback mechanisms to refine forecasts and analyses based on actual outcomes. Captures historical data and insights for future decision-making.
9. Strategic scenario planning: Analyzes market trends and competitive positioning to support strategic planning. Evaluates potential investments and their financial impacts by using AI-driven analysis. Optimizes asset and project portfolios based on AI-driven recommendations.
10. Financial model explanations: Automatically generates clear, detailed explanations of financial models, including assumptions, calculations and potential impacts. Provides visualizations and scenario analyses to demonstrate how changes in inputs affect outcomes. Helps ensure transparency by enabling users to drill down into model components and understand the rationale behind projections and recommendations.

This is not a short wish list, but it should make us all excited about the future of FP&A. Today, FP&A professionals spend too much time on manual work in spreadsheets or dashboard updates. Implement these capabilities, and you’ll easily free up several days each month for value-adding work.

Finally, use your newfound free time to realize the mission of FP&A to drive the right strategic choices in the company. How many companies have FP&A teams that facilitate the strategy process? I have yet to meet one.

However, with added AI capabilities, this could soon be a reality. Let’s elaborate on how some of the capabilities on the wish list can elevate our work to a strategic level.

• Strategic scenario planning: How do you know what choices are available to make? It can easily become an endless desktop exercise that fails to produce useful insights. By using AI in analysis, you can get more done faster and challenge your thinking. This helps FP&A bring relevant choices and insights to the strategy table instead of just being a passive facilitator.
• Advanced forecasting: How do you know whether you’re making the right strategic choice? The answer is simple: you don’t. However, you can improve the qualification of the choice. That’s where advanced forecasting comes in. By considering all available internal and external information, you can forecast the most likely outcomes of a choice. If the forecasts align with your strategic aspirations, it’s probably the right choice.
• Collaborative planning: Many strategies fail to deliver the expected financial outcomes due to misalignment and silo-based thinking. Executing the right choices is challenging if the strategy wasn’t a collaborative effort or if its cascade was done in silos. Using collaborative planning, FP&A can facilitate cross-functional awareness about strategic progress and highlight areas needing attention.

If you’re unsure where to start, identify a concrete task today that aligns with any item on the wish list. Then, explore what tools are already available within your company to automate or augment the output using AI.

If no tools are available, you need to build the business case by aligning with your colleagues about the most pressing needs and presenting them to management.

Alternatively, you can try IBM Planning Analytics on your work for free. When these tools work for you, they can work for others too.

Don’t overthink the issue. Start implementing AI tools in your daily work today. It’s critical to use these as enablers to elevate the work we do in FP&A. Where will you start?