About Course
Agentic AI is giving finance teams a new opportunity to shape how organisations plan, fund and govern digital investment. As AI systems take on planning, tool use and multi-step execution, the finance function is well placed to lead on how this new kind of spend gets costed, budgeted and reported, a capability that goes well beyond treating AI as a fixed software licence.
This course is designed for finance professionals who are asked to build AI investment cases, track AI spend, assess total cost of ownership and report on AI initiatives. It applies a practical Agentic Profit and Loss framework to cost attribution, budgeting, FinOps-style tagging, build-versus-buy analysis and board-level AI return-on-investment (ROI) reporting.
The course covers the economics of agentic AI, FinOps-style cost attribution and tagging, build-versus-buy-versus-on-premises comparisons, and budgeting and board reporting for variable inference and agent run-time spend. Each of these is grounded in a working case scenario so the concepts translate directly into tools learners can apply back at work.
Training is delivered through classroom-facilitated sessions built around a live case scenario, culminating in an oral assessment.
Who Should Attend
Minimum Entry Requirements
- At least 1–2 years of experience in finance, financial planning and analysis, business finance, financial control, procurement, project finance, technology finance, transformation, investment evaluation or a related role
- Familiarity with basic budgeting, cost analysis, return-on-investment concepts and business-case preparation
No prior coding experience required; basic awareness of generative AI or enterprise AI use cases is helpful
The Agentic AI Series
This course is part of a collection of Agentic AI courses curated by SITLEARN, spanning finance, legal, human resources, marketing, operations, and risk and security. Each course imparts agentic AI foundations customised to the specific function. View the full collection here.
Learning Outcomes
By the end of this course, learners will be able to:
- Explain agentic AI's cost and value gap relative to conventional software ROI models
- Build a cost-attribution model covering inference, orchestration, tooling and human oversight
- Avoid common agentic AI business-case errors, including undercounted oversight cost
- Apply FinOps tagging and chargeback principles to agentic AI run-time spend
- Compare build, buy and on-premises deployment paths on a common cost basis
- Calculate the breakeven usage volume at which each deployment path becomes economic
- Construct a budget for variable inference and agent run-time spend
- Apply a capability capitalisation model to agentic AI investment
- Present an AI investment case in financial language a board and CEO will accept
Teaching Team
Ian Loe Wai Yew
Trainer
Course Details
Schedule
| Course Run | Dates | Time |
|---|---|---|
| January 2027 | 25 - 26 Jan 2027 | 9:00 am – 6:00 pm |
| March 2027 | 15 - 16 Mar 2027 | 9:00 am – 6:00 pm |
Day 1
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Day 2
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Certificate and Assessment
A Certificate of Attainment will be issued to participants who:
- Attend at least 75% of the course
- Undertake and pass non-credit bearing assessment during the course
Participants who meet the attendance requirement but do not pass the assessment will receive a Certificate of Participation.
Mode of Assessment: Oral Questioning (30 minutes)
Fee Structure
The full fee for this course is S$2,507.00.
| Funding Category | Eligible Funding | Course Fees Payable After Funding |
|---|---|---|
| Singapore Citizen (Below 40) | 70% | S$752.10 |
| Singapore Citizen (40 & Above) | 90% | S$292.10 |
| Singapore PR / LTVP+ Holder | 70% | S$752.10 |
| Non-Singapore Citizen | Not Eligible | S$2,507.00 |
Note: All fees above include GST. GST applies to individuals and Singapore-registered companies.
Course Runs
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