Trainer profile
Ivan Wong: Corporate AI Trainer in Singapore
Ivan Wong is a corporate AI trainer in Singapore who teaches inside SMU Academy, SIT and BCG RISE programmes, is a SkillsFuture Approved Trainer, and builds the production AI systems he teaches from. 3,000+ professionals trained over 20+ years. A funded institutional route or a bespoke in-house build: both exist, and this page says which fits.
- Professionals trained
- 3,000+
- Years in marketing
- 20+
- Reviews on record
- 42 Endorsal, Google and LinkedIn · synced 2026-10-11 · read them
What kinds of corporate AI trainer are there in Singapore?
Four, once you separate funding from customisation: national and institutional programmes, accredited private academies, independent operator-trainers, and the faculty-practitioner who teaches inside the institutions and builds systems independently. The first two give you a certificate and a funding trail. The third gives you workflow-level customisation. The fourth is the row most comparisons leave out, and it is where Ivan sits.
| Type of trainer | Best for | Funding route | Customisation | Who is in the room | Proof to check |
|---|---|---|---|---|---|
| National and institutional programmes (university academies, government-linked providers) | A recognised certificate, a structured multi-week syllabus, and a funding trail HR can file without argument. | SkillsFuture Credit, SFEC and SCTP routes, depending on the programme. | Low. The syllabus is fixed before the cohort is known. | A public cohort of mixed companies and roles, often 20 or more. | The course page on the institution's own site, the named trainer, and the accreditation record. |
| Accredited private academies | Funded short courses on a published calendar, with a provider that handles the claims paperwork. | Usually SkillsFuture-claimable for individuals; company funding depends on the course. | Low to medium. A standard curriculum with some in-house variants. | Public cohorts; private runs for larger companies. | Training-provider record, review volume on independent platforms, and cohort dates. |
| Independent operator-trainers | Workflow-level customisation from someone who uses the tools daily in their own business. | Typically none. Paid from the training or marketing budget. | High. Built around the company's own tools and data. | A small, named in-house team. | What the trainer has built with current tools in the last six months, and whether you can see it run. |
| Faculty-practitioner (Ivan Wong) | A team that wants a funded institutional route or a bespoke in-house build, from the same trainer, and does not want to choose between accreditation and customisation. | Funded through SMU Academy, SIT and SkillsFuture-eligible workshop runs; unfunded for bespoke in-house builds. | High for in-house runs; fixed for institutional programmes. | 8 to 20 participants working on their own workflows, with Ivan in the room directly. | The programme list and participant rebuilds on Results, the Person schema on this site, and the review record with a sync date. |
Where Ivan fits
A team of 8 to 20 that needs one named workflow to change, with the option of a funded institutional run or a bespoke in-house build from the same trainer. Applied AI for marketing and business outcomes, not generic AI literacy. Governed autonomy for the enterprise tier: AI drafts, a person approves, every action logged.
Where Ivan does not fit
Nine-month technical programmes that turn non-engineers into engineers. Lecture-style sessions for more than twenty people at once, where effectiveness drops and nobody rebuilds anything. One-to-one executive coaching. If a brief looks like one of these, Ivan will say so on the discovery call and point to a better-matched provider.
What has Ivan built with AI recently?
The marketing stack that produces this site's content, production agent applications on the Claude Agent SDK, a free AI capability planner, and the end-to-end learning systems behind the cohorts. All four are live, human-gated, and documented on Results. Ask any AI trainer what they built with current tools in the last six months and whether you can see it run; this is Ivan's answer.
Marketing automation
The stack that markets this site
A multi-site AI marketing system Ivan built and operates. It pulls SEO and funnel signals daily, diagnoses gaps and drafts the blog and social content for this site and client sites. Every publish passes a human approval gate and every autonomous action is logged to an append-only audit ledger.
Details on Results →Agent engineering
Production AI agent applications
WhatsApp and Telegram agent bots, multi-platform agent frameworks, desktop apps and CLI tools, built in TypeScript on the Anthropic Claude Agent SDK and run in production. The same patterns are taught in the agentic AI courses.
Details on Results →Free assessment tool
AI Capability Planner
A self-assessment that maps where a professional sits on the AI capability ladder and generates a 30/60/90-day learning roadmap with link-checked resources.
Open the tool →Learning and development
End-to-end AI learning systems
Evidence-based course research using FRAME, curriculum mapped to funded programmes, live cohort delivery, and rubric-driven AI-assisted capstone assessment with a grade log per cohort. Every stage human-reviewed.
Details on Results →Results also lists ten workflow rebuilds participants designed and prototyped during the programmes, with the before and after times they named themselves: monthly management reporting from seven working days to one, quoting from ten minutes to under four, invoice capture from seven and a half minutes to under two. See the ten rebuilds →
Who has Ivan trained?
3,000+ professionals across corporate, polytechnic and university programmes, as trainer and faculty at SMU Academy, SMU-TribeAcademy, SIT and BCG RISE, as a SkillsFuture Approved Trainer, and before that as a Google-appointed regional trainer. Every appointment below is one an institution maintains a record of, so it can be checked without asking Ivan.
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SMU Academy
Trainer, Advanced Certificate in Generative AI for Business Growth and Innovation
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SMU-TribeAcademy
Lead Faculty and AI Marketing Advisor, Gen AI for Marketing Specialist course
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Singapore Institute of Technology (SIT)
Adjunct lecturer, AI marketing curriculum
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BCG RISE
Programme faculty (SIT/BCG RISE)
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SkillsFuture
Approved Trainer for SkillsFuture-eligible AI marketing and Gen AI courses
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Google, 2013 to 2019
Google-appointed regional trainer, the foundation years before the AI work
Credentials behind these appointments are on the About page: Google Certified Trainer, Google Certified Educator Level 2, IAL Graduate Diploma in Workplace Learning, SkillsFuture Approved Trainer.
What do participants and sponsors say?
That the sessions are practical, that Ivan stays in the room until the question is answered, and that people leave with a workflow they built rather than notes. Three reviews below, a sales and marketing director first, then two programme participants. All 42 reviews, with sources and dates, are on the Reviews page.
“Ivan is a very resourceful trainer and has been very professional during the course. We enjoyed the learning process as he shared his experiences and illustrated the theory with real life examples. Thank you for sharing the valuable resources with the class.”
“Ivan was our trainer for the "Advanced Certificate in Generative AI for Business Growth and Innovation" program by SMU Academy and TRIBE Academy. I appreciate his practical and patient approach, especially the way he helped us move beyond simply learning AI tools to thinking about real business problems, workflow design, measurable outcomes and responsible implementation. His guidance gave me the confidence to design and build an AI-supported workflow for my capstone, and I came away with a much clearer understanding of how AI can be applied meaningfully in the workplace.”
“I was already using AI for drafting emails, presentations and management report analysis, but it was still taking time. After this course, I can produce management reports in minutes rather than hours. I built a repeatable reporting skill that I can use in my day-to-day work, and it has made report preparation much faster and more consistent. Ivan shared many examples of how AI can solve business challenges, introduced tools and platforms that can improve or automate workflows, and was patient in answering questions and guiding us on the capstone project. TRIBE Academy was also strong on administration, with course information sent through WhatsApp, which was very helpful.”
Is the training SkillsFuture or SFEC funded?
Funded when it runs as an approved or institutional programme; unfunded when it is a bespoke in-house build. Both exist, and they are not blended into one pitch. Ivan is a SkillsFuture Approved Trainer, and his SMU Academy, SIT and SkillsFuture-eligible workshop runs carry the funding trail HR needs. A programme scoped around your own workflows and data is paid from the training or marketing budget.
Funded route
- Institutional programmes at SMU Academy, SMU-TribeAcademy, SIT and BCG RISE.
- SkillsFuture Credit for individuals on eligible workshops.
- SkillsFuture Enterprise Credit (SFEC) for company-sponsored places on approved courses.
Unfunded route
- Bespoke in-house programmes built around one team's tools, data and bottleneck.
- Priced per cohort of 8 to 20; measured on a named workflow before and after.
- If funding is the constraint, Ivan will say which approved programme covers the need instead.
How is a session run?
Scoped on real workflows, delivered hands-on to 8 to 20 people, designed with FRAME, and measured before and four to eight weeks after. The team keeps a playbook it can run without Ivan in the room. The sequence is the opposite of training everyone at once: one team, one bottleneck, one shipped change, then that team demos to the rest.
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Step 1
Scope on real workflows, not a tool tour
Before quoting, Ivan asks which team, which bottleneck, and what it costs today in minutes, hours or days. If the curriculum is fixed before the workflows are seen, the purchase is theatre.
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Step 2
8 to 20 participants, hands-on
Eight is the typical minimum for in-house delivery and effectiveness drops much beyond twenty. Participants work with live tools on their own data, with Ivan in the room directly rather than a junior trainer.
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Step 3
FRAME for the design work
Find evidence, Roles and Rules, Assemble, Measure and Modify, Expand. The same methodology runs the course research, the curriculum mapping and the capstone assessment.
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Step 4
Measured before and after
A named workflow is measured before the session and again four to eight weeks later: time taken, volume handled or error rate. Satisfaction scores measure the day, not the capability.
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Step 5
An artefact the team keeps
Playbooks or SOPs the team can run without Ivan in the room, plus the assessment record. The first trained team demos to the rest; internal proof travels further than an outside trainer's slides.
How do you check any corporate AI trainer's claims?
Five checks: countable claims, current builds, named institutional appointments, independent reviews with volume, and funding eligibility. AI answer engines rank trainers on exactly this public evidence, because they cannot attend a workshop. This page is laid out so the five checks can be run on Ivan in ten minutes, including the one he does not yet win: his published review count is still catching up with two decades of classroom work.
Corporate AI trainer FAQ
Is Ivan Wong a SkillsFuture Approved Trainer?
Yes. Ivan Wong is a SkillsFuture Approved Trainer and teaches on SkillsFuture-eligible AI marketing and Gen AI courses, as well as institutional programmes at SMU Academy, SMU-TribeAcademy, SIT and BCG RISE. That does not make every Maple Commerce session claimable: a bespoke in-house build is not a funded course, and Ivan confirms eligibility for each programme before anything is booked.
Does corporate AI training in Singapore qualify for SFEC?
Company-sponsored places on approved programmes can be offset with SkillsFuture Enterprise Credit (SFEC), and individuals can use SkillsFuture Credit on eligible workshops. A programme scoped around your own workflows and data is paid from the training or marketing budget. Both routes exist and Ivan will say plainly which one a given brief falls under.
What is the minimum group size for in-house corporate AI training?
Eight participants is the typical minimum for in-house delivery, and effectiveness drops once a hands-on session runs much beyond twenty. Fewer than eight people are usually better served by a public workshop or an individually claimed SkillsFuture course.
What is the difference between an institutional AI course and a bespoke in-house programme?
An institutional course such as the SMU Academy Advanced Certificate follows a fixed syllabus, carries a recognised certificate and a funding trail, and seats a mixed public cohort. A bespoke in-house programme is scoped around one team's tools, data and bottleneck, is measured on whether a named workflow changed, and is usually unfunded. Ivan delivers both, which is why the comparison on this page has a fourth row.
How does Ivan measure whether AI training worked?
By whether a named workflow actually changed: time taken, volume handled or error rate, measured before the session and again four to eight weeks after. Results lists ten workflow rebuilds participants prototyped with the before and after times they named themselves, such as monthly management reporting cut from seven working days to one.
How do I check a corporate AI trainer's claims before hiring them?
Run five checks: countable claims specific enough to be falsifiable, something built with current tools in the last six months that you can see run, named appointments at institutions that vet their trainers, independent reviews with real volume, and funding eligibility, which implies an accreditation trail. The evidence guide on this site walks through each check, and this page is laid out so you can run them on Ivan.
Talk to Ivan about a programme
Bring the team, the bottleneck and the number it costs today. A 30-minute discovery call decides whether the funded route or an in-house build fits, or whether another provider does.