Claude AI training for leadership & strategy teams in Singapore
Claude AI training for leadership teams in Singapore: one hands-on day, onsite, on your own files. Decision briefs. AI opportunity assessment.
Claude Cowork for leadership & strategy teams
Leadership reading is long and consequential: board packs, diligence material, regulatory guidance. This programme uses Claude for that reading, with reasoning explicit enough to challenge.
Where the work happens
- Long documents
- Contract review
- Structured extraction
- Multi-source synthesis
This programme is built around long, dense documents — the contracts, reports and policy sets where the work is reading carefully rather than writing quickly.
Who this programme is for
Executives, department heads and transformation leads. Knowledge, legal and research teams.
- 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
Not the right fit
- 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
What the day covers
Module 1: Decision briefs
Board packs and long reports are synthesised into a decision brief with alternatives and evidence gaps.
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
Candidate use cases are assessed against the documents that describe how the work is actually done today.
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
Governance and acceptable-use positions are drafted against the regulatory and policy material that constrains them.
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.
A worked example: Board pack to decision brief
One exercise from the day, as it runs on your own material in Claude Cowork.
- 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.
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.
What this day does not cover
Scope is agreed before the session so the day stays hands-on.
- Coding, scripting or developer workflows, even though the tool is capable of them. This is a day on document and analysis work.
- API integration or automated pipelines.
- Legal advice. We cover how to review a document carefully and what to escalate, not what position to take on it.
Before the session
- A licensed Claude Cowork seat for each participant
- 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
Format and schedule
- 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
- Typically one full day, or two half-days scheduled around leadership calendars. Module order is adjusted to your priorities and tool stack.
- How each module runs
- 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.
- Afterwards
- Participants leave with the prompt patterns, templates and review checklists produced during the session, so the work continues after the training day.
How your data is handled
- 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 runs the session
Abhijit Ghosh
Founder, Eagentix · Data & Generative AI Practitioner · Singapore
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.
Questions about Claude Cowork for leadership & strategy
How does this help with board packs and diligence material?
Long reading is synthesised into a decision brief that states alternatives and evidence gaps rather than smoothing them over. The gaps are the part a leadership team actually needs.
Why choose Claude for this work rather than the assistant bundled with our office suite?
Because the bottleneck here is long, dense reading rather than quick drafting. The programme is built around documents that take a person an afternoon, and around making the reasoning visible enough that a reviewer can check it clause by clause.
How long can the documents be?
Long enough that the constraint in practice is your review capacity, not the tool. We work with your real documents on the day, and part of the exercise is deciding what still needs a full human read.
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.