If you need to teach colleagues to use generative AI tools, the skill you need most is training design and facilitation, not more AI knowledge. The Bodhih Certified Train The Trainer Program is a four-day, 32+ hour trainer-skills certification (80% practice) where you redesign your own AI session into a hands-on prompt lab with safe-use rules and follow-up that measures behaviour change. It is not a technical AI credential.
Is this an AI certification or a trainer certification?
It is a trainer certification. The Bodhih Certified Train The Trainer (TTT) Program does not teach you how large language models work, how to build AI products or how to use a specific vendor's tool. It teaches you how to design, deliver and evaluate training, which is the skill most people who are asked to "roll out GenAI" across a team are missing.
Some courses called "AI trainer certification" are technical (model training, data labelling). This page is for two other groups:
People who teach AI tools at work
Subject matter experts, digital champions and L&D staff who must run GenAI sessions for colleagues: prompt labs, live demos, safe-use rules, and follow-up that shows whether people actually changed how they work.
Trainers who use AI to build training
Facilitators who want to draft outlines, activities, case studies and quiz items faster with AI, while keeping a human review step so the content stays accurate and fits the audience.
Why AI tool training needs trainer skills, not just tool knowledge
Most GenAI sessions fail for teaching reasons, not technical ones. The presenter knows the tool well, shows thirty minutes of impressive demos, and participants leave without having typed a single prompt about their own work.
AI sessions bring a specific mix of difficulties. The group is usually split between enthusiasts who are already ahead, sceptics who distrust the output, and anxious participants worried about their jobs. Outputs vary each time you run the same prompt, so a scripted demo can go wrong in front of the room. The real goal is behaviour change at the desk, which a feedback form cannot measure. Each is a facilitation problem the TTT addresses.
How the four TTT days map to AI-training situations
Each day of the programme covers a skill you will use in a GenAI rollout. You bring your own AI session (or a draft of one) and redesign it during the four days.
| TTT day | What it covers | Where it shows up in AI training |
|---|---|---|
| Day 1 | Knowles' andragogy, Kolb's cycle, Bloom's Taxonomy, baseline delivery | Adults learn a tool by using it on real tasks. Kolb's cycle turns "watch me prompt" into try, reflect, refine, apply. Bloom's helps you write objectives beyond "understand ChatGPT", such as "draft and fact-check a client summary". |
| Day 2 | ADDIE, Training Needs Analysis, experiential activity design, storytelling | A needs analysis tells you which tasks in which roles are worth automating, and what people are already doing with AI informally. Activity design gives you prompt labs and before/after exercises instead of slides. |
| Day 3 | Platform skills, 7 types of difficult participants, questioning techniques, virtual training | Handling the sceptic, the expert who derails, and the silent anxious participant. Recovering calmly when a live demo produces a wrong answer. Running screen-share labs online. |
| Day 4 | Kirkpatrick's four levels, final certification delivery, building your trainer brand | Measuring whether people use the tool safely four weeks later (Level 3), not just whether they enjoyed the session. Your final delivery can be your own AI session. |
The full day-by-day detail is on the TTT curriculum page.
What a good GenAI session plan looks like
A good GenAI session is mostly hands-on, built on participants' own tasks, and ends with a commitment to use the tool on a specific piece of work. Here is a 90-minute lab structure we suggest as a starting point; adjust the timings to your group.
- Open with a real task (10 min). Ask each participant to note one recurring task that takes them time, such as a weekly report, meeting notes or customer replies. This becomes their working material.
- Set the safe-use rules (10 min). State clearly what may and may not be pasted into the tool, which tools are approved, and that every output must be checked before use.
- Short demo with a deliberate flaw (10 min). Show one prompt, then show the tool getting something wrong. This builds healthy scepticism and lowers the anxiety of the cautious.
- Prompt lab, round one (20 min). Participants work in pairs on their own task. Mix confident and hesitant users so peers coach each other.
- Debrief and refine (15 min). Use questioning to draw out what worked: adding context, giving an example, asking for a format. Participants rewrite their prompts.
- Prompt lab, round two (15 min). Apply the improved approach and check the output against a simple review checklist: accuracy, tone, confidential details, and sources.
- Commit and close (10 min). Each person names the task they will use the tool on this week. Schedule a short check-in to collect examples.
Measure behaviour, not attendance. A useful follow-up asks: "Show us one piece of work where you used the tool, and what you changed in the output." That is Kirkpatrick Level 3 evidence. See our guide to the Kirkpatrick model.
Using AI to design training faster, with human review
AI can speed up the first draft of training material, but the trainer remains responsible for accuracy, relevance and fit to the audience. Treat AI output as a draft from a fast assistant who does not know your learners.
Sensible uses include drafting an outline from your objectives, generating role-play variations and writing first-draft quiz questions at different Bloom's levels. TTT skills let you judge the draft: is the objective measurable, does the activity fit Kolb's cycle, does the assessment test the objective?
A simple review routine: check every fact against your source, replace generic examples with ones from your organisation, cut anything you cannot explain yourself, and pilot the activity with a small group before a full rollout.
Data-privacy cautions for AI training
The safest rule to teach is simple: do not paste anything into an AI tool that you would not be allowed to email to an outside party. Your organisation's IT, legal and data-protection teams decide what is permitted, and your session should reflect their policy rather than your own assumptions.
- Use made-up or anonymised sample data in labs, never real customer, employee or patient records.
- Confirm which tools and accounts are approved before the session, and show participants how to use those.
- Remind participants that outputs can be wrong or invented, and that they remain accountable for anything they send.
- Avoid uploading confidential documents, source code or contracts unless your policy explicitly allows it.
When to pair TTT with the AI for Trainers course
Take the TTT first if you are new to designing and running training, and add the AI course when you want deeper hands-on practice with AI tools in your own design work. The two cover different ground.
The TTT builds core trainer competence: adult learning, design, facilitation, difficult participants and evaluation. Bodhih also runs a separate AI for Trainers course focused on using AI in the trainer's own workflow. If your organisation needs its wider workforce trained on GenAI rather than its trainers, Bodhih offers Generative AI training for employees.
If you train technical teams, also see technical train the trainer, and for online labs, virtual trainer certification.
Programme facts at a glance
The Bodhih TTT is four consecutive days with a small batch and repeated practice.
Upcoming open batches include Mumbai (18–21 Nov 2026) and Bengaluru (9–12 Dec 2026); check the batch calendar on fees and upcoming batches. Live online and in-house batches are available on request. Bodhih holds a 4.8/5 Google rating from 141 reviews (as of 24 Oct 2026). Call +91 99000 11603 or email solutions@bodhih.com.
Frequently asked questions
Is the Bodhih TTT an AI certification?
No. The Bodhih Certified Train The Trainer Program is a trainer-skills certification. It teaches adult learning, training design, facilitation and evaluation. It does not certify technical AI knowledge such as machine learning or model building. It suits people who will teach AI tools to colleagues, or trainers who use AI to prepare training, and need to design and run sessions that change how people work.
How do I become an AI trainer at my company?
Start by learning the approved tools well on real tasks in your own role, then build trainer skills: needs analysis, hands-on activity design, handling mixed-confidence groups and measuring behaviour change. A train-the-trainer programme covers the second part. Then pilot a short prompt lab with a small team, collect examples of real use, and refine before a wider rollout.
How should I train employees on generative AI?
Keep it hands-on and based on participants' own work. Set safe-use rules first, show a demo that includes a mistake, then run paired prompt labs on real tasks with a review checklist. End with a commitment to use the tool on a named task, and follow up a few weeks later to collect examples. Measure use at work, not just session feedback.
Can I bring my GenAI session to the TTT and work on it?
Yes. Participants work on their own content during the four days and leave with a redesigned module. If you are preparing a GenAI session, you can use it as your working material, practise parts of it in your 6+ practice deliveries with expert feedback, and use it for your final certification delivery.
What does the TTT cost for someone in India?
The fee for Indian public (open) batches is ₹40,000 + GST per participant, with group discounts for 3 or more people. International participants attending an open batch in India pay USD 500 (non-residential). Corporate, in-house and online batches outside India are priced on request. Check the batch calendar for upcoming dates in Mumbai and Bengaluru.
Should I take the TTT or Bodhih's AI for Trainers course?
They cover different needs. The TTT builds core trainer competence in design, delivery and evaluation. The AI for Trainers course focuses on using AI in a trainer's own workflow. If you are new to running training, the TTT is the foundation; add the AI course if you want deeper hands-on practice with AI tools. Contact Bodhih for details of the AI course.
Is it safe to use real company data in AI training labs?
Generally, use anonymised or made-up sample data in labs and follow your organisation's IT and data-protection policy on which tools and inputs are approved. A useful rule to teach is not to paste anything into an AI tool that you would not be allowed to share outside the organisation. Participants should also check every output before using it.