AI for Finance Professionals
capability building,
designed for your organisation.
A custom-built corporate programme for FP&A analysts, controllers, financial accountants, treasury professionals, internal auditors, tax professionals, finance managers, CFO-track senior managers, and finance-systems specialists. We design the curriculum around your tech stack, project archetypes, and target business outcomes — delivered by domain-expert trainers and reinforced through AI-evaluated assessments.
A modular syllabus, built to be tailored.
Below is our reference curriculum. Every syllabus we deliver is tailored to your customer-specific requirements — module depth, sequencing, lab environments, and capstone projects are adapted to your team's starting point, tech stack, and target outcomes.
- AI in finance categories: FP&A, controllership, audit, treasury, tax, regulatory
- Vendor landscape: ChatGPT, Claude, Copilot for finance + finance-specialist tools (Workday AI, Oracle EPM AI, SAP AI, BlackLine AI, Anaplan AI)
- What's mature: variance commentary, summarisation, forecasting assistance. What's emerging: agentic close
- Strategic implications for finance operating model
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Demonstrable skills your team will apply on live projects.
Apply AI across the finance lifecycle
FP&A, controllership, audit, treasury, tax, regulatory reporting — with audit-grade discipline.
Use AI for non-coder financial analysis
Code Interpreter, NL2SQL, AI-augmented Excel for analyst-grade work without engineer dependency.
Govern AI use in finance with discipline
Confidentiality classifications, SOX-aligned audit trails, regulatory implications, vendor evaluation.
Pass GSDC AI for Finance certification
Two attempts; cohort first-attempt pass rate 89%.
Compress monthly close and analysis cycles
30-50% time saving on variance analysis, commentary drafting, board-pack production — documented pre/post.
Lead AI initiatives in your finance function
Equipped to evaluate vendors, design controls, and shape AI strategy for finance.
Where your team is now vs where they'll be after the programme.
Where most teams start
- ·Aware AI matters for finance but unsure which use cases are safe, compliant, and value-additive
- ·Limited fluency with AI in finance workflows (Excel Copilot, Codex/Claude for SQL, AI in Workday, Oracle, SAP)
- ·Cannot reliably use Code Interpreter / Advanced Data Analysis for non-coder financial analysis
- ·No working framework for AI in audit-grade documentation, SOX, regulatory reporting
- ·Concerned about confidentiality of financial data in AI tools but unclear on what's safe
- ·Limited fluency with AI for variance analysis, forecasting, and management commentary
Where they'll arrive
- ✓AI-augmented FP&A — variance analysis, forecasting, commentary, board-pack drafting at 3-5× the pace
- ✓Controllership AI fluency — close acceleration, reconciliation assistance, exception detection
- ✓Audit-grade discipline — knows what's safe to put in AI, what isn't, with SOX-aligned documentation
- ✓Code Interpreter mastery for non-coder financial analysis on real datasets
- ✓NL2SQL fluency for finance — querying ERP and data warehouse without engineer dependency
- ✓GSDC AI for Finance certification — credential for senior finance roles
Built for L&D outcomes, not seat counts.
Prompt discipline, not prompt luck
Learners move from trial-and-error prompting to named patterns such as role prompting, few-shot, prompt chaining, and self-critique.
Reusable team assets
The programme produces Custom GPTs, reusable workflow templates, and a shared prompt library that teams can govern and scale.
Daily productivity workflows
Labs focus on email, reports, slides, meetings, spreadsheets, research synthesis, and role-based business assignments.
Measured time savings
Capstone workflows document recurring task compression, review-cycle reduction, and before/after productivity improvements.
Responsible enterprise use
Learners practise confidentiality, IP, bias detection, verification checklists, and safe-use protocols before adoption at scale.
Sustainment built in
30-day, 60-day, and 90-day check-ins help learners keep pace as ChatGPT features and frontier models evolve.
A four-milestone path from skill gap to client-ready.
Foundation & baseline
Establish a working mental model of ChatGPT, frontier models, tokens, context windows, hallucination risks, and model-selection trade-offs.
Prompt engineering labs
Learners practise CRISPE, SPEAR, role prompting, constraint-led prompting, few-shot prompting, self-critique, and prompt iteration on real work scenarios.
Custom GPTs & workflow automation
Each learner builds reusable GPTs and connects ChatGPT to productivity tools for email, documents, spreadsheets, meetings, and research workflows.
Capstone & sustainment
Learners demonstrate a personal AI productivity system and continue with prompt-of-the-week, model-of-the-month, and 30/60/90-day check-ins.
Want this curriculum aligned to your tech stack and project archetypes?
Why enterprise teams choose the B2B engagement model.
Domain-expert trainers, not professional presenters.
"My job isn't to teach ChatGPT as a tool — it's to help professionals build repeatable AI workflows, verify the output, and reclaim hours from routine work."
Taught by people who've actually shipped the work.
Built for L&D leaders and their learners.
Who this is for
- ·Knowledge workers who want to apply ChatGPT productively in their daily workflows
- ·Business analysts, consultants, marketing professionals, project managers, and individual contributors
- ·Teams that use ChatGPT for occasional drafting but need reliable, business-grade outputs
- ·Managers looking to establish team-wide prompt standards and safe-use protocols
- ·Organisations that want to automate repetitive work across email, spreadsheets, calendars, and documents
Pre-requisites
- ·No coding prerequisite for business and productivity tracks
- ·Basic familiarity with workplace tools such as email, documents, spreadsheets, slides, and meetings
- ·Willingness to bring real recurring tasks into labs for workflow redesign
- ·Enterprise cohorts should align data-handling expectations before learners use company or client information
Trusted by L&D leaders across the world.
"The programme moved our team from random prompting to a repeatable method. The prompt library and Custom GPTs became assets we could actually reuse."
"The most useful part was workflow automation. Learners took their weekly reports, meeting recaps, and research tasks and reduced hours of repetitive effort."
"Responsible use was handled practically. The team finally understood what can be pasted, what must be masked, and how to verify output before sending it."
Questions L&D teams ask before signing.
Yes, but only when organizations use enterprise-grade AI platforms with encryption, access controls, compliance policies, and approved governance frameworks for sensitive financial data.