How to effectively learn AI Prompting, with the 'AI for VP of Finances (Prompt Course)'?

Lead Finance With AI: Practical Workflows for VPs

This course gives a VP of Finance a complete, practical system for applying AI and ChatGPT across core responsibilities. It connects budgeting, forecasting, cash flow, capital structure, reporting, tax planning, risk, and strategic planning into a coherent set of workflows that speed up analysis, improve clarity, and standardize deliverables. You will learn how to turn scattered data and recurring tasks into repeatable, auditable AI-assisted processes that support faster decisions and stronger stakeholder communication.

What you will learn

• How to integrate AI and ChatGPT into day-to-day finance operations in a way that is reliable, explainable, and auditable.
• Methods for improving budget preparation and analysis, including structured scenario reviews, variance commentary, and executive-ready narratives.
• Approaches for cash flow monitoring and forecasting that connect short-term liquidity needs with medium-term planning.
• Ways to use AI-assisted models to compare capital structure options, estimate cost of capital components, and assess debt policy choices.
• A consistent approach to cost reduction analysis that distinguishes genuine structural savings from one-off cuts, with clear tracking and governance.
• How to translate economic trend signals into planning assumptions, and reflect those assumptions in forecasts and risk registers.
• Financial modeling guardrails that help prevent common mistakes and improve documentation, version control, and peer review.
• Faster reporting cycles with automated draft narratives, variance explanations, and board-ready summaries that still preserve your oversight.
• Structured methods for investment portfolio review and capital allocation, including performance diagnostics and rebalancing frameworks.
• An AI-assisted process for initial M&A screening, synergy estimation ranges, and integration risk mapping.
• Systematic KPI and performance metrics analysis that links operational drivers with financial outcomes and strategic goals.
• Risk management workflows that identify, rate, and monitor financial and operational risks with clear mitigation plans.
• Strategic planning routines that pull together insights from budgets, forecasts, and market trends into measurable priorities.
• Tax planning review steps that surface risks and opportunities, and support compliance-ready documentation.
• Governance, privacy, and model limitations practices that keep AI use responsible, secure, and aligned with internal controls.

How the course is organized

The curriculum is arranged into focused modules that mirror a VP of Finance's operating calendar. Each module includes guided workflows, review checklists, and quality standards that help you turn AI outputs into executive-grade deliverables. The material is structured so you can adopt individual parts right away or implement the full system as a linked set of processes. By the end, you will have a repeatable approach for monthly, quarterly, and annual cycles that reduces rework and improves transparency.

How to use the prompts effectively

The course teaches durable prompting habits that make AI outputs more useful and dependable without getting lost in technical details. You will learn how to:

• Provide clear context and constraints so the model works with the facts, definitions, and formats you need.
• Guide the model to produce structured, audit-friendly outputs such as bullet-point analyses, tables, and executive summaries.
• Iterate with feedback loops that tighten accuracy, spot gaps, and reduce ambiguity.
• Set objective quality criteria and verification steps so outputs are consistent with policy and finance standards.
• Redact sensitive information and establish safe data boundaries, while still gaining useful insights.
• Maintain a versioned prompt library with naming and documentation conventions that support team sharing and review.

How the modules work together

The modules are interlinked by design. Budget work informs forecasting; forecasting feeds cash flow management; cash flow insights influence capital structure choices. Economic trend analysis sets the backdrop for strategic planning and risk assessments. Reporting draws from each area to build clear narratives for leadership and the board. Tax planning and compliance checks ensure recommendations are viable and audit-ready. This integrated approach means you do not treat each process in isolation; instead, you build a coordinated, AI-assisted finance engine.

Where this course adds value

• Speed and clarity: Reduce time-to-insight for recurring deliverables while improving the readability and usefulness of outputs.
• Consistency: Apply standardized workflows and formatting so analyses are comparable across periods, business units, and stakeholders.
• Breadth: Explore more scenarios and sensitivities within the same review window so you can catch outliers and edge cases earlier.
• Governance: Integrate documentation, review steps, and audit trails so AI-supported work meets internal and external expectations.
• Communication: Turn technical analysis into concise narratives and visual summaries suited for executives, boards, and non-financial leaders.
• Capability building: Enable your FP&A, treasury, controllership, and strategy teams to adopt a common set of AI practices.

Practical outcomes you can expect

• Faster month-end and quarter-end commentary production with clearer variance explanations.
• More credible forecasts with transparent assumptions and scenario alternatives.
• Improved cash visibility and liquidity planning, especially for near-term obligations and covenant reporting.
• Structured decision memos for capital structure questions, investment proposals, and cost initiatives.
• Repeatable M&A screening and synergy hypothesis templates that save time early in the funnel.
• Performance metrics that tie operational levers to financial outcomes, with ongoing monitoring routines.
• Tax and compliance documentation that is easier to compile, review, and keep current.

Ethics, security, and risk controls

Responsible AI use is foundational throughout the course. You will learn to set guardrails on data sharing, redact sensitive elements, and maintain human review over conclusions and recommendations. The course addresses model limitations, error handling, and bias checks, and shows how to build approvals, sign-offs, and traceability into each workflow. The result is a practical governance approach that fits finance controls rather than working against them.

Data and tool readiness

You do not need specialized systems to gain value. The course explains how to work with spreadsheets, CSV exports, ERP reports, and BI dashboards using safe processes and structured prompts. For teams with more advanced setups, there are guidelines for connecting document repositories, establishing repeatable data refresh cycles, and improving collaboration between finance, data, and IT stakeholders.

Team adoption and leadership

The material supports both individual use and team rollouts. You will find strategies for change management, skill uplift, and establishing a shared prompt library with review and approval workflows. Leaders can assign modules to specific sub-teams-FP&A, treasury, tax, accounting, and strategy-while keeping a unified playbook for cross-functional work products like board packs and budget books.

Assessment and certification

To confirm learning, the course includes applied checkpoints and a capstone that brings the modules together. By completing these, you demonstrate that you can run an AI-assisted finance operating rhythm with proper controls, documentation, and communication standards.

Who should enroll

• VPs of Finance who want a structured, efficient way to apply AI across their portfolio of responsibilities.
• Direct reports and high-potential leaders in FP&A, treasury, controllership, and strategy who contribute to executive deliverables.
• Finance teams seeking consistent standards for AI use, documentation, and cross-team collaboration.

Why start now

AI already fits well with recurring finance workflows that depend on clear inputs, repeatable logic, and well-defined outputs. This course helps you adopt those practices in a way that respects controls and improves quality, without adding complexity to your month-end, planning, or board cycles. If you want faster reviews, sharper insights, and better documentation-while keeping human judgment at the center-this course provides the playbook.