Eagentix Hands-On AI Training

Leadership & Strategy AI Training Singapore

Hands-on AI training in Singapore for executives and leadership teams on Copilot, ChatGPT, Gemini, Claude or Amazon Q, using your own reports.

AI training for leadership & strategy teams

AI training for leadership and strategy teams

Leaders are asked to set AI direction while having little time to use the tools themselves. This is a hands-on programme for executives, department heads and transformation leads who need to apply Microsoft Copilot, Claude Cowork, Gemini Enterprise, Amazon Q Enterprise or ChatGPT Enterprise to decision briefs, use-case assessment and governance — and to come out able to judge what their teams are being asked to adopt. Sessions are delivered in Singapore, on site or remote, using your tool licences and anonymised versions of your own material.

Who this programme is for

Executives, department heads and transformation leads.

  • Executives who need to brief, decide and set direction from long material
  • Department heads choosing which AI use cases their teams should pursue
  • Transformation and strategy leads building the case for AI investment
  • Leadership teams agreeing acceptable use, ownership and approval points for AI

Who it is not for

  • Teams looking for a vendor demo or an awareness keynote rather than hands-on practice
  • Anyone expecting a ready-made AI strategy rather than the skills to judge one
  • Technical architecture or platform-selection projects — this is applied assistant training

Assistants covered in the programme

The programme is delivered on the assistant your organisation already licenses. The techniques transfer between them.

Microsoft Copilot

Word, PowerPoint, Outlook and Teams inside Microsoft 365. Used for decision briefs, board-pack summaries and meeting preparation from documents you already hold.

ChatGPT Enterprise

Analysis over uploaded reports, custom GPTs for repeat briefing tasks, and prompt patterns for strategy documents.

Gemini Enterprise

Google Workspace leadership work: Docs briefs, Slides summaries and grounded answers over reports in Drive.

Claude Cowork

Long board packs, diligence material and regulatory guidance, synthesised with reasoning explicit enough to challenge.

Amazon Q Enterprise

Grounded answers over connected enterprise sources for organisations standardised on AWS.

Curriculum and hands-on modules

Module 1: Decision briefs

Hands-on exercise. Synthesize approved reports into a decision brief with alternatives, evidence gaps and questions for the team.

What you leave with. An executive briefing template and evidence checklist.

Module 2: AI opportunity assessment

Hands-on exercise. Map team workflows and compare candidate use cases by effort, value, data readiness and review requirements.

What you leave with. A prioritised opportunity shortlist with measurable pilot criteria.

Module 3: Governance and adoption

Hands-on exercise. Define ownership, acceptable use, human approval points and a practical adoption plan.

What you leave with. A governance checklist and 30-day team adoption plan.

The same leadership & strategy day on each assistant

The modules stay the same; the exercise changes with the tool your team is licensed for.

Microsoft Copilot: Decision log from a leadership meeting

What goes in
A Teams meeting recap and the pre-read deck.
What is asked
Produce a decision log: what was decided, who owns it, by when, and what was discussed but left open.
What comes out
A one-page log circulated the same day.
What the reviewer checks
Attendees confirm the decisions before circulation, because a recap can state a discussion as a decision.

ChatGPT Enterprise: Scoring candidate use cases

What goes in
Short descriptions of eight processes your teams have proposed for AI.
What is asked
Score each one for value, effort, data readiness and review burden, and say which scores rest on assumptions.
What comes out
A ranked shortlist with the assumptions listed.
What the reviewer checks
The leadership team overrides the scores where they know better; the point of the exercise is the conversation, not the ranking.

Claude Cowork: Board pack to decision brief

What goes in
A 120-page board pack.
What is asked
Produce a two-page brief: the decisions requested, the options presented, the evidence behind each and what is not in the pack.
What comes out
A brief a director reads before the meeting, not instead of it.
What the reviewer checks
Each option and figure in the brief carries a page reference the director can open.

Gemini Enterprise: Adoption plan in Docs

What goes in
Your team's list of candidate workflows and current Workspace usage.
What is asked
Draft a phased adoption plan with owners, a review point for each phase and what would make you stop.
What comes out
A plan in Docs presented from Slides.
What the reviewer checks
Each phase has a named owner and a measurable stop condition before it is approved.

Amazon Q Enterprise: Connection scope as a governance decision

What goes in
The list of sources connected today and proposed additions.
What is asked
For each source, record who can query it, what answers may be used for and who approves changes.
What comes out
A governance checklist for connection scope.
What the reviewer checks
The checklist is approved by the data owner for each source, not by the platform team alone.

Singapore rules the exercises respect

Singapore has published more practical AI governance guidance than most markets, and the leadership day uses it directly.

  • IMDA's Model AI Governance Framework, and its 2024 edition for generative AI, give a working structure for accountability, testing and disclosure.
  • AI Verify offers a testing approach the organisation can adopt as it moves from pilots to production.
  • The PDPC's advisory guidelines on personal data in AI recommendation and decision systems set expectations on consent and explanation.
  • For financial institutions, MAS's FEAT principles on fairness, ethics, accountability and transparency apply to how AI output is used.

How the sessions run

Delivery

On site in Singapore or remote, delivered live. Cohorts are kept small enough that every participant works on their own files rather than watching a screen share.

Duration and scheduling

Typically one full day, or two half-days scheduled around leadership calendars. Module order is adjusted to your priorities and tool stack.

Session structure

Each module follows the same pattern: a short walkthrough of the technique, a hands-on exercise on your own data, then a review of what the assistant got wrong and how to catch it.

After the session

Participants leave with the prompt patterns, templates and review checklists produced during the session, so the work continues after the training day.

Prerequisites

  • A licensed seat on at least one of the covered assistants (we can run the programme on whichever your organisation has)
  • Familiarity with your own strategy, operating priorities and current AI activity
  • Anonymised or sample working files — a recent report or board paper, a list of candidate use cases
  • No coding background required

Data handling and human review

  • Exercises run inside your own tenant and your own licences, so your data does not leave your environment for the training.
  • Files shared with the trainer in advance are anonymised extracts; board material, financials and strategy documents stay inside your own tenant and licences.
  • Every module includes verification: checking output against the source, confirming what the assistant left out, and marking what still needs a human read.
  • Decisions stay with the leadership team. The programme teaches AI-assisted analysis and preparation, and how to set the approval points your teams will work within.

Who delivers the training

Abhijit Ghosh

The programme is delivered by Abhijit Ghosh, who has spent 25 years in data and AI, including roles at Accenture, IBM, Deloitte, Cloudera, Tibco and Wipro. Sessions are run by the practitioner, not handed to a junior facilitator.

Frequently asked questions

Which AI assistant should our leadership team use?

Start with the one your organisation already licenses. Microsoft Copilot suits teams working in Outlook, Word, Excel and Teams; Gemini Enterprise suits Google Workspace; ChatGPT Enterprise and Claude Cowork are stronger for long, document-heavy work; Amazon Q suits AWS-standardised estates. The programme runs on whichever you have, and the techniques transfer between them.

Do participants need a technical or coding background?

No. The programme is built for practitioners, not engineers. If you can describe how the work is done today and you know your own documents and systems, you have the prerequisites. Nothing in the sessions requires scripting.

Will we work on our own material?

Yes. Private sessions run on your own reports and papers inside your own tenant. Where a file has to be shared with the trainer in advance, an anonymised extract is used, so board and strategy material stays inside your environment.

How long is the programme and how is it scheduled?

Typically one full day, or two half-days. Leadership teams usually prefer two half-days so the calendar holds. Module order is adjusted to your priorities and tool stack.

Is the training delivered in Singapore?

Yes. Sessions are delivered on site in Singapore, or live and remote for teams spread across the region.

What do participants take away?

An executive briefing template with an evidence checklist, a prioritised AI opportunity shortlist with measurable pilot criteria, and a governance checklist with a 30-day team adoption plan — all produced during the exercises using your own material.

How is this different from a vendor product demo?

A demo shows features on prepared data. This programme applies the assistant to your own work, including the cases where it produces confident, wrong output — because recognising and catching those is the skill that matters once the team uses it unsupervised.

Is this a strategy engagement or training?

Training. Leaders work hands-on with the assistant on their own material and leave with a shortlist, a governance checklist and an adoption plan they built. If you need ongoing executive ownership of the AI portfolio, that is the separate fractional AI leadership engagement.

Which Singapore AI governance frameworks does the session reference?

IMDA's Model AI Governance Framework, including the 2024 generative AI edition, AI Verify, and the PDPC's advisory guidelines on personal data in AI systems. Financial institutions also cover MAS's FEAT principles. These are used as working structures, not as legal advice.

What does a leadership team leave with?

A shortlist of use cases with owners, an acceptable-use position and the approval points that apply before anything reaches production.

Choose the assistant your team already licenses

Leadership & Strategy training by assistant