How to effectively learn AI Prompting, with the 'AI for Finance and Accounting specialists (Prompt Course)'?

Start applying AI to your finance workflows this week

This course gives finance and accounting specialists a practical, structured path to put AI and ChatGPT to work across everyday responsibilities. Through focused modules and ready-to-use workflows, you will learn how to turn messy data and shifting requirements into clear, consistent outputs for analysis, reporting, and decision support. The content is built for practitioners who care about accuracy, controls, explainability, and speed.

Who this course helps

• FP&A professionals managing forecasts, budgets, and variance analysis
• Controllers and accountants preparing statements, reconciliations, and reports
• Auditors and internal control teams seeking documentation and testing support
• Tax professionals summarizing rules, planning scenarios, and compliance checks
• Investment and credit analysts evaluating risk, returns, and counterparty strength
• Finance leaders aiming to standardize AI-assisted workflows across teams

What you will learn

• How to structure effective AI interactions for forecasting, budgeting, and cash flow planning
• Ways to accelerate financial statement and ratio analysis with clear, repeatable instructions
• Methods to analyze portfolios, credit quality, and market trends with consistent assumptions
• Approaches for cost-benefit assessment, risk analysis, and scenario testing
• How to support audit tasks, controls documentation, and evidence gathering
• Techniques for automating recurring reports with standardized formats and checks
• Processes for tax summaries, planning comparisons, and compliance monitoring
• Frameworks to evaluate M&A opportunities and economic impacts using structured workflows
• Best practices for quality assurance, governance, and human review

How the modules fit together

The modules are arranged to cover the full finance cycle-from planning and analysis to reporting and assurance-so you gain a complete toolkit that works across roles and industries. Each topic is self-contained but connects naturally with others:

• Market and economic analyses inform forecasting assumptions and risk views.
• Budget and cash flow workflows align with reporting automation to shorten monthly closes.
• Risk, credit, and portfolio analyses share similar data patterns and validation steps.
• Audit support builds on the same documentation habits used in tax and compliance monitoring.
• M&A assessments reuse statement analysis, trend evaluation, and scenario testing methods.

Using the prompts effectively

Success with AI in finance comes from clarity, constraints, and verification. The course shows you how to steer outputs with precision while keeping your process auditable and safe.

• Start with purpose: Define the business question, the decision to be made, and the audience.
• Provide the right context: Share the relevant data, timeframe, accounting standards, and assumptions.
• Specify outputs: Request the exact formats you need (tables, bullet summaries, JSON schemas) and include labels, units, and sign conventions.
• Set constraints: Include policies, thresholds, materiality limits, and acceptable data sources.
• Iterate with intention: Test a small sample, review results, add clarifications, and re-run on full data.
• Embed checks: Ask for reconciliations, tie-outs, and reasonableness tests; require explanations for outliers.
• Document decisions: Capture assumptions, data lineage, and version history for auditability.
• Use structured workflows: Separate data preparation, analysis, and reporting to keep steps clean and repeatable.

Data handling, controls, and assurance

Because finance work carries confidentiality and compliance needs, the course emphasizes safe practices and verification techniques.

• Confidentiality: Anonymize sensitive fields, use minimal necessary data, and manage access.
• Retention settings: Understand how your AI tool stores or discards data and select options that fit company policy.
• Source control: Maintain approved data sources and attach citations in outputs.
• Validation: Reconcile subtotals to totals, cross-check ratios, and test samples against ground truth.
• Numerical integrity: Require consistent rounding, units, and time periods; flag negative values where not expected.
• Bias awareness: Note coverage gaps in training data and apply weighted judgments in risk and credit outputs.
• Audit trail: Preserve prompt versions, datasets, and outputs to support reviews.

Tooling and workflow integration

The course shows practical ways to fit AI outputs into the tools finance teams already use.

• Spreadsheets: Generate tables ready for paste-back; standardize column headers and naming conventions.
• BI and dashboards: Produce clean CSV or JSON with data dictionaries for ingestion.
• ERP/GL exports: Provide mapping instructions and chart of accounts context for categorization tasks.
• Scheduling and automation: Identify tasks suitable for daily, weekly, or month-end cycles.
• Collaboration: Create review-ready executive summaries alongside detailed appendices.
• Change management: Establish review steps so outputs can be trusted and adopted by stakeholders.

Course format and learning experience

Each module focuses on a specific finance function while reinforcing shared methods for clarity, controls, and repeatability.

• Concept brief: What the workflow solves and where it fits in finance processes.
• Setup guidance: What data to prepare, what to include or exclude, and what parameters to fix.
• Quality checklist: Built-in checks, reconciliations, and review steps.
• Scalability tips: How to move from ad hoc analysis to scheduled, standardized runs.
• Common pitfalls: Data leakage risks, unit mismatches, and ambiguous instructions to avoid.
• Team playbook: How analysts, controllers, auditors, and managers share the same templates.

Coverage across finance functions

The curriculum spans planning, analysis, assurance, and compliance so you can apply one consistent approach to multiple needs.

• Forecasting, budgeting, and cash flow management for better planning cycles
• Financial statement analysis and reporting automation for faster, clearer close processes
• Portfolio, credit, and risk analysis for balanced decision-making
• Market trend and economic impact evaluation for context and sensitivity testing
• Audit support and regulatory compliance monitoring for stronger documentation
• Tax planning and M&A assessments for strategic choices

Results you can expect

• Shorter cycles from data to insight, with fewer manual steps
• Consistent, explainable outputs that meet review standards
• Better coverage of scenarios, with clear assumptions and constraints
• Improved alignment across teams through shared templates and definitions
• Higher confidence in reported figures due to embedded checks and tie-outs

Capstone: build your finance AI playbook

To bring everything together, the course guides you to assemble a reusable playbook. You will connect forecasting and budgeting steps with statement analysis, reporting automation, and audit support, then add risk and compliance checks. The result is an end-to-end workflow that your team can run consistently and improve over time.

Prerequisites and time commitment

• Prerequisites: Comfort with spreadsheets, basic financial analysis, and familiarity with your company's data sources and policies.
• Time: Most learners complete the core content in a few focused sessions, with optional deepening modules for tax, audit, risk, and M&A.
• Optional skills: Familiarity with CSV/JSON formatting, BI tools, or simple automation is helpful but not required.

Why this approach works for finance and accounting

Finance problems reward clarity: defined objectives, standardized outputs, and strong controls. This course teaches you to express those needs succinctly, feed AI the right context, and demand verification at every step. By applying the same structure across planning, analysis, and reporting, you reduce rework, make reviews faster, and keep decision-making grounded in evidence.

Ready to get started?

If you want practical methods that respect accuracy, auditability, and compliance, this course gives you a clear path. Build confidence in a safe, incremental way, and turn AI into a dependable partner across your finance tasks.