Finance teams are under pressure to plan faster, analyze deeper, and support better decisions — but many are still trapped in spreadsheet-heavy workflows, manual reporting cycles, and fragmented planning systems. This course explores how AI is changing FP&A and how finance leaders can move toward faster, more connected, and more intelligent planning, analysis, and decision support.
Course ID: BSBAI
Beyond Spreadsheets: Building the AI-Enabled Finance Function
Learning Objectives
Upon completion of this course, participants will be able to:
- Recognize how AI has evolved from chat-based assistants to agentic workflows and why this shift matters for modern FP&A.
- Distinguish between traditional FP&A processes and AI-native, agentic FP&A operating models.
- Identify the limitations of legacy planning platforms and evaluate the characteristics of modern, AI-first planning architectures.
- Recall concepts such as continuous forecasting, scenario modeling, AI-generated commentary, and autonomous data workflows to improve planning and decision-making.
- Recall how AI technologies, including reasoning models, Model Context Protocol (MCP), and multi-agent systems, can be applied securely within finance functions.
- Estimate how to develop a practical roadmap for introducing AI-enabled planning capabilities into their finance organization while maintaining governance, auditability, and control.
- Identify immediate actions they can implement to improve FP&A efficiency, forecasting accuracy, and strategic decision support.
Major Topics
- Why spreadsheet-heavy FP&A workflows slow down modern finance teams
- The shift from traditional FP&A to AI-enabled and agentic FP&A
- How finance can move from manual data manipulation to more strategic advisory work
- The changing role of AI in planning, reporting, forecasting, and variance analysis
- The journey from chat-based AI to copilots, agents, and multi-agent finance workflows
- How AI can support continuous forecasting, autonomous data gathering, self-generating commentary, and scenario modelling
- The FP&A performance management loop: data collection, reporting, forecasting, and strategic decision support
- Why legacy planning tools often fail to keep pace with modern business needs
- Practical considerations for trusted data, governance, auditability, human review, and finance controls
- Operational actions finance teams can take to begin building an AI-enabled finance function
Who Should Attend
CFOs, finance directors, FP&A leaders, finance managers, controllers, management accountants, business partners, analysts, consultants, and finance professionals who want to understand how AI can improve planning, forecasting, reporting, analysis, and decision-making.
Fields of Study
FinancePrerequisites
None. No prior AI experience is required. A basic familiarity with FP&A, budgeting, forecasting, reporting, or finance operations may be helpful but is not required.