ChatGPT Enterprise training for hr & people teams in Singapore
ChatGPT Enterprise training for hr teams in Singapore: one hands-on day, onsite, on your own files. Recruitment preparation. Onboarding and policy.
ChatGPT Enterprise for hr & people teams
HR teams repeat the same drafting tasks across every role and every joiner. This programme builds those into custom GPTs on your own frameworks, and is explicit about which HR material may never be uploaded.
Where the work happens
- File analysis
- Custom GPTs
- Projects
- Canvas
The distinguishing exercise is building a custom GPT on your own files that a whole team can reuse, plus the verification standards that keep its answers trustworthy.
Who this programme is for
HR, talent and people operations teams. Teams building shared internal tools.
- HR business partners who answer the same policy questions every week
- Talent acquisition teams preparing role profiles, interview questions and assessment rubrics
- People operations teams running onboarding and employee communications
- HR leaders deciding where AI may support people decisions and where it must not
Not the right fit
- Teams looking for a vendor demo rather than hands-on practice
- Anyone expecting AI to screen out, rank or decide on candidates or employees without human judgement
- HRIS implementation or system integration projects — this is applied assistant training
What the day covers
Module 1: Recruitment preparation
Role profiles and structured interview guides are generated from your competency framework, uploaded once and reused.
Exercise. Draft role profiles, structured interview questions and competency rubrics for human-led assessment.
What you leave with. A reusable hiring preparation pack.
Module 2: Onboarding and policy
A policy-answering GPT is built on your approved handbook, and drilled on declining questions the handbook does not cover.
Exercise. Build an onboarding plan and draft policy answers grounded in approved documents.
What you leave with. An onboarding checklist and source-backed policy response template.
Module 3: People reporting
Anonymised feedback is analysed for themes, with explicit checks for what the summary left out.
Exercise. Summarise anonymised feedback and prepare workforce reporting with explicit checks for omissions and bias.
What you leave with. A reviewed people report and quality checklist.
A worked example: A policy-answering GPT on your handbook
One exercise from the day, as it runs on your own material in ChatGPT Enterprise.
- What goes in
- Your approved employee handbook and leave policy.
- What is asked
- Build a GPT that answers staff policy questions, quotes the section it relied on and declines when the handbook is silent.
- What comes out
- A shareable GPT plus a ten-question test set.
- What the reviewer checks
- Three of the ten test questions are deliberately outside the handbook; the GPT passes only if it declines all three.
Singapore rules the exercises respect
HR material is the most sensitive data most organisations hold, and Singapore law sets clear limits on how it is used.
- Employee personal data is covered by the PDPA, including purpose limitation: data collected for payroll is not automatically available for an AI exercise.
- Hiring content is reviewed against the Tripartite Guidelines on Fair Employment Practices and the Workplace Fairness Act passed in 2025.
- Survey and feedback analysis is aggregated so that small teams cannot be identified.
- Decisions about individuals stay with people. The programme covers preparation and review, not automated screening.
What this day does not cover
Scope is agreed before the session so the day stays hands-on.
- API work, function calling or anything that requires writing code. This is a day for the people doing the business task.
- Admin configuration, workspace provisioning or SSO setup.
- Fine-tuning. The programme builds custom GPTs on your own files, which is a different thing and the one most teams actually need.
Before the session
- A licensed ChatGPT Enterprise seat for each participant
- Working knowledge of your own HR processes, handbook and policy library
- Anonymised or sample working files — a role description, a policy extract, an onboarding checklist
- 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 hiring and review cycles. Module order is adjusted to your calendar 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; employee records, candidate data and case files 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 about candidates and employees stay with your people. The programme teaches AI-assisted preparation and review, never automated hiring or employment decisions.
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 ChatGPT Enterprise for hr & people
Can a custom GPT answer policy questions for the whole team?
That is the exercise, built on your approved handbook. The important half is drilling it on questions the handbook does not cover, so it declines rather than improvises — which is the behaviour you are relying on if it answers employees directly.
What is a custom GPT and why does the day centre on building one?
It is a reusable assistant configured once with your own files and instructions, then shared with the team. It matters because it turns a good prompt one person wrote into a repeatable standard everyone uses — including the review checkpoints written into its instructions.
Is our uploaded material used to train the model?
Enterprise plans are sold on the basis that business data is not used for training, and your administrators can confirm the terms that apply to your workspace. We cover what to upload and what to keep out regardless, because access scope inside your own organisation matters as much as the vendor terms.
How does the programme handle PDPA for employee data?
Exercises use anonymised or synthetic records unless your data protection officer has cleared real data for the purpose. Purpose limitation is covered explicitly, because data collected for payroll or performance is not automatically available for an AI exercise.
Can the assistant screen candidates?
The programme does not teach automated screening. It covers drafting role profiles and interview guides and reviewing them against fair employment guidelines. Decisions about candidates stay with people.