GENERATIVE AI TRAINING · INDIA
Generative AI Training in India
Skillopedia’s generative AI training in India takes teams from “we have licences” to a governed, measurable way of working. We have trained 200,000+ professionals across 335+ organisations in 10+ years, and we rebuild every programme around your own documents, your reviewers and your regulator before day one. Short teach, long lab, and an evidence trail your risk function will accept.
- Customised to your industry, documents and systems — not a fixed deck
- Every module ends in a hands-on lab on your own live work
- Governance, verification and a 30-60-90 rollout plan included
- On-site across India, virtual, or hybrid across time zones
Talk to the trainer before you commit to anything.
A 20-minute call, no deck. We look at what your team produces today, tell you honestly whether generative AI training will move it, and send an outline the same week.
TRUSTED BY THE TEAMS THAT DO NOT EXPERIMENT LIGHTLY
Some of the 335+ organisations we have trained
BOOK YOUR PROGRAMME
Tell us what your India team actually does all day.
We will come back within one working day with a proposed outline, the right format and a fixed quote. If we are not the right fit for what you need, we will say so and point you somewhere better.
- Response within one working day
- Outline built on your documents, not a template
- NDA signed before any material is shared
- Fixed fee — no per-seat surprises
Prefer to talk first? Book a 20-minute call or message us on WhatsApp.
WHY INDIA, WHY NOW
Why India is investing in generative AI right now
India’s AI training market is saturated with awareness sessions and starved of governed practice. Enterprises here run at a scale where inconsistent AI output becomes a quality problem within weeks — so the value is in a house standard that 500 people can actually follow, not a keynote 500 people enjoyed.
Market context: India has the largest concentration of global capability centres in the world and the DPDP Act 2023 now governs how their data is handled.
The organisations pulling ahead in India are not the ones with the most licences. They are the ones where a finance analyst, a legal reviewer and a marketing lead all use the same reviewed method — and where somebody can prove, in numbers, that it worked. That is the gap this programme is built to close.
THE HONEST PART
Where most AI training fails
We have been called in to fix the aftermath of enough failed programmes to know the patterns. If your last AI training did not stick, it almost certainly died of one of these.
Prompt roulette
Everyone invents their own prompt, quality swings wildly between people, and nothing is reusable next week. Without a shared, versioned prompt standard the organisation never compounds what it learns.
Pilot purgatory
A clever demo in a workshop that never becomes a workflow. No owner, no measurement, no integration into the system where the work actually happens — so it quietly dies after 30 days.
The security stand-off
Enthusiastic teams versus a risk function with no policy to point at. Training that never answers "what may I paste, and who signs it off?" gets blocked at exactly the moment it starts to matter.
Invisible ROI
Nobody baselined the task before the training, so nobody can prove anything after it. Finance sees a licence cost and no evidence, and renewal becomes a fight.
Trainer theatre
A motivational speaker who has never shipped a workflow inside a regulated enterprise. Great energy, zero transfer — participants leave inspired and unchanged.
One-size-fits-nobody content
The same generic deck delivered to finance, legal, engineering and marketing. Every function nods politely and none of them can apply it to Monday morning.
No verification discipline
Teams are taught to generate and never taught to check. The first confidently wrong output that reaches a client destroys trust in the whole programme.
No day-31 plan
The workshop ends, the champions have no mandate, managers have no scoreboard, and usage decays to the same handful of early adopters it started with.
None of these are tool problems. They are design problems — which is why the fix is a programme, not a longer workshop.
HOW SKILLOPEDIA IS DIFFERENT
What changes when a practitioner runs the room
Every line below is something a client has explicitly told us was missing from a previous vendor. Compare us against whoever else is on your shortlist.
| What you are comparing | A typical generative AI training vendor | Skillopedia |
|---|---|---|
| Who delivers it | A generalist trainer reading vendor slides | A practitioner who builds these workflows for enterprises weekly and has trained 200,000+ professionals |
| Curriculum | Fixed deck, same for every client | Rebuilt around your documents, your systems and your review process before day one |
| Depth | Chat prompts and productivity hacks | Full product surface — projects, knowledge, agents, connectors, automation and API where relevant |
| Governance | A slide that says "be careful" | A written AI-use standard: what may be pasted, who reviews, what gets logged, mapped to your regulator |
| Hands-on | A demo the trainer clicks through | Every module ends in a lab where participants build on their own live work |
| Output | Notes and goodwill | A prompt library, reusable templates, a governance one-pager and a 30-60-90 rollout plan |
| Measurement | A happy-sheet feedback form | Pre-training task baselines, post-training re-measurement and a 30-day adoption review |
| After the session | Silence | Champion enablement, a follow-up clinic and an office-hours window for real questions |
| Track record | A handful of logos | 335+ organisations across 13 sectors, 10+ years, 4.9/5 average rating |
INDIA’S MOST DEMANDING TEAMS TRUST SKILLOPEDIA
The Indian organisations getting AI right trained for it
Anonymised because most of these sit behind confidentiality agreements — the numbers are from post-programme measurement, not from a brochure.
A listed financial group
Cut investment-memo first drafts from 6 hours to 70 minutes.
A global capability centre
Standardised AI usage across 600+ analysts.
A pharma major
Saved 11 hours per medical writer per week.
Client organisations across the sectors that matter in India:
COURSES WE OFFER
Six formats — pick the one that fits the problem
Most clients run two or three of these in sequence: a leadership briefing to set direction, functional cohorts to build the habit, then champions to keep it alive.
Executive Briefing
Half day · CXO and leadership
A boardroom-level session on what generative AI changes for strategy, cost, risk and competitive position — with a live working demo on your own business material, not a slide deck.
- Where AI creates and destroys margin in your industry
- A defensible AI investment and risk position
- Reading an AI business case critically
- Governance questions leaders must ask
- Your own 90-day leadership commitments
Business & Functional Track
1 day · non-technical teams
The core programme for finance, legal, HR, marketing, sales, operations and customer teams. Short teach, long lab, everything built on the documents that function actually produces.
- Context engineering fundamentals
- Function-specific workflow labs
- Reusable prompt and template library
- Verification and review discipline
- A personal 30-day working plan
Technical & Engineering Track
2 days · engineering and data
For developers, data teams and platform engineers: agentic development, API and SDK use, tool calling, evaluation harnesses and integration with your own repositories and systems.
- Agent design and tool use
- API, SDK and structured output
- Evaluation and regression testing
- Repo-aware development workflows
- Security and secrets discipline
Enterprise Rollout Programme
4–12 weeks · organisation-wide
A phased programme across multiple functions and sites: leadership alignment, function tracks, champion certification, a written governance standard and measured adoption.
- Multi-cohort delivery calendar
- Certified internal champions
- Written AI-use standard
- Manager adoption scoreboards
- Quarterly re-measurement
Keynote & Offsite Session
60–90 minutes · large audiences
A high-energy keynote for town halls, annual offsites and customer events — live demos, real numbers and a clear call to action, sized for hundreds of people in the room.
- Live demo on the audience's own scenario
- What is actually changing in the next 12 months
- Myths that waste enterprise budget
- Practical first steps for every role
- Q&A with the full audience
Train-the-Trainer
2 days · internal champions
Certify a cohort of internal champions to run clinics, onboard new joiners and maintain the prompt library after the main programme ends.
- Facilitation and lab-running practice
- Maintaining the prompt library
- Handling risk and policy questions
- Running a 60-minute clinic
- Certification and assessment
WHAT WE ACTUALLY COVER
Train across the whole generative AI stack — tool-agnostic, workflow-first
Most teams use perhaps 15% of what they are paying for. These are the twelve surfaces we take people through — depth adjusted to the audience in the room.
Choosing the right model
A practical decision rule for when to use Claude, ChatGPT, Gemini or a small local model — by task, cost and risk.
Context engineering
The skill that actually separates good output from bad: structuring inputs, examples and constraints.
Projects, Gems & Custom GPTs
Persistent, shared workspaces so team output stops depending on individual habit.
Knowledge grounding & RAG
Making answers rest on your own documents — and spotting when retrieval has failed.
AI agents
Multi-step, tool-using workflows with human checkpoints, and where agents are the wrong answer.
Connectors, MCP & integration
Wiring assistants into the systems where the work lives, with permissions IT can approve.
Data & analysis workflows
Spreadsheets, reporting and analysis patterns that survive review.
Multimodal work
Documents, images, audio and video used for real business output.
Evaluation & verification
Testing before deployment, and catching confidently wrong output.
Governance & risk
Permitted data, review responsibility, logging and regulator-mapped controls.
Change management
Champions, manager scoreboards and the human side of an AI rollout.
Unit economics
What a workflow actually costs to run, and how to argue the business case.
Because we are not reselling a licence, model recommendations are made on merit — including when the answer is “use the cheaper one”.
MODULE OUTLINE
The curriculum, module by module — with the labs
Every module ends in a hands-on activity on your own work. These five are the defaults; they get swapped for your artefacts during discovery.
Module 1 — Foundations that actually matter
How these models work well enough to predict where they fail — tokens, context, temperature, hallucination and the tasks they are structurally bad at.
Hands-on in this module
- Run the same task on three models and score the differences yourself
- Break a prompt deliberately to see the failure mode up close
- Map five of your own weekly tasks onto a "safe / needs review / never" grid
- Rewrite one vague request into a specification the model can execute
- Build your personal cheat-sheet of when not to use AI at all
Module 2 — Context engineering
The single highest-leverage skill: giving the model role, task, constraints, examples and source material in a structure that produces repeatable output.
Hands-on in this module
- Convert one of your real requests into a structured prompt with explicit constraints
- Add two worked examples and measure the quality jump
- Build a reusable prompt template for a task you repeat weekly
- Test the same prompt across three inputs to check stability
- Version and comment your prompt so a colleague can reuse it
Module 3 — Working with your own documents
Grounding output in your material: uploading, structuring and referencing source documents, and recognising when retrieval has silently failed.
Hands-on in this module
- Load a real (redacted) document set and interrogate it
- Force citations and check every one of them against source
- Deliberately ask a question the documents cannot answer, and observe the behaviour
- Build a summary format your reviewers will accept
- Create a source-of-truth checklist for your team
Module 4 — Persistent workspaces
Moving from one-off chats to shared, configured spaces with standing instructions and knowledge, so quality no longer depends on who is typing.
Hands-on in this module
- Set up a shared workspace for your function with standing instructions
- Load reference material and a house style guide into it
- Run the same task inside and outside the workspace and compare
- Write the instruction block that encodes your team's standard
- Hand the workspace to a colleague and have them test it cold
Module 5 — Verification and review
The discipline that keeps AI output out of trouble: structured checking, source tracing, and designing outputs that are fast to review.
Hands-on in this module
- Apply a four-step verification routine to a generated document
- Find the planted error in a convincing AI-written analysis
- Redesign an output format so a reviewer can check it in half the time
- Write your function's review checklist
- Agree who signs off what, and record it
Module 6 — Automation and agents
Multi-step and tool-using workflows: where they pay back, how to keep a human in the loop, and where a simple template beats an agent.
Hands-on in this module
- Decompose one real end-to-end process into steps and decide what AI may own
- Build a two-step assisted workflow with a human checkpoint
- Add a failure path — what happens when the model is wrong
- Estimate time saved and error risk for the workflow
- Present the workflow to the group for challenge
Module 7 — Governance, security and compliance
What may be pasted, what must never be, who reviews, what gets logged — written down in language your risk function will accept.
Hands-on in this module
- Classify ten real data examples as permitted, restricted or prohibited
- Draft your team's AI-use one-pager
- Map each control to the regulation or policy that requires it
- Run a mock incident: an AI-assisted error reached a client — what now?
- Agree the logging and evidence trail your auditors will expect
Module 8 — Measuring impact and the 30-60-90
Turning a training day into a change programme: baselines, scoreboards, champions and a plan with named owners.
Hands-on in this module
- Baseline three tasks with real before-numbers
- Set target metrics your manager will accept
- Write your personal 30-60-90 plan
- Nominate and brief a team champion
- Book the 30-day review before you leave the room
Module 9 — Choosing between Claude, ChatGPT and Gemini
A practical decision rule by task, cost, risk and data sensitivity — tested live rather than argued theoretically.
Hands-on in this module
- Run one identical high-stakes task across all three tools
- Score outputs blind against your own rubric
- Build your team's model-selection decision table
- Price each option per 100 runs
- Agree the default tool per workflow and write it down
Module 10 — Building an AI agent end-to-end
Designing, building and stress-testing a multi-step agent for one real process, including the human checkpoints and the failure path.
Hands-on in this module
- Map the process and mark every decision point
- Build the agent with explicit tool boundaries
- Stress-test it with deliberately bad inputs
- Add monitoring and a human escalation path
- Present the agent and defend its risk profile
WHO SHOULD ATTEND
Built for the whole organisation, taught function by function
Everyone shares the same core method, then splits into function labs. That is why finance and engineering can be trained in the same programme without either being bored.
CXOs & business heads
Leaders who must set an AI position, approve spend and answer for risk.
Finance & accounting
Reporting, commentary, variance analysis, board packs and audit preparation.
Legal & compliance
Contract review, clause comparison, policy drafting and regulatory summaries.
HR & L&D
Job descriptions, policy, interview design, learning content and internal communication.
Marketing & communications
Campaign development, long-form content, localisation and brand-consistent output.
Sales & business development
Proposals, RFP responses, account research and follow-up discipline.
Operations & supply chain
SOPs, exception summaries, supplier documentation and process reporting.
Engineering & data
Agentic development, code review support, test generation and evaluation.
SECTORS WE HAVE CATERED TO
Industry context we do not have to be taught
335+ organisations across 13 sectors. These are the six that dominate our India work — and the client names below each are from that sector.
Banking, Financial Services & Insurance
Banks, AMCs, NBFCs and insurers under RBI, SEBI and IRDAI supervision.
Clients include: HDFC Bank, Kotak Mahindra, IndusInd Bank, NatWest, Swiss Re, Allianz.
Technology, IT & GCCs
GCCs, IT services and product engineering organisations.
Clients include: Accenture, Microsoft, Capgemini, Cognizant, HCL, Mphasis.
Pharma, Life Sciences & Healthcare
Regulatory, medical writing and quality functions.
Clients include: Pfizer, Abbott, Bayer, Sun Pharma, Glenmark, Piramal.
Manufacturing & Industrial
Auto, industrial, chemicals and engineering groups.
Clients include: Bosch, Siemens, ABB, Tata Motors, Mahindra & Mahindra, Maruti Suzuki.
Media, Advertising & Publishing
Networks, agencies and publishers.
Clients include: Ogilvy, Publicis Groupe, MullenLowe Lintas, TBWA, BBDO, Sony.
Consulting, Legal & Professional Services
Advisory, audit and shared-service functions.
Clients include: EY, Adani Group, Aditya Birla Group, GMR Group, Mitsui & Co., TMF Group.
TOOLS WE COVER IN SESSIONS
The stack participants actually touch
Hands-on means hands on these — configured against your own tenant and your own documents wherever your policy allows it.
Because we are not reselling a licence, model recommendations are made on merit — including when the answer is “use the cheaper one”.
And the craft that sits underneath
- Context engineering — structuring inputs so quality is repeatable
- Verification routines that catch confidently wrong output
- Data hygiene — what may be pasted, and what never may
- Prompt versioning so the team compounds instead of restarting
- Reviewer-friendly output design that halves review time
- Unit economics — what a workflow costs per hundred runs
- Change management — champions, scoreboards and manager habits
- Measurement — baselines before, re-measurement after
EVERY SESSION IS CUSTOMISED AND HANDS-ON
How we build and run the programme
There is no standard deck to send you, because there is no standard deck. This is the six-step process behind every engagement.
1. Discovery
We interview a cross-section of the team, collect real artefacts (with your redactions) and agree the three workflows the programme will move.
2. Design
Content, labs and datasets are rebuilt around your material. Nothing generic survives this step.
3. Hands-on delivery
Short teach, long lab. Participants build on their own live work with facilitators on the floor.
4. Guardrails
We write the AI-use standard with your risk, legal and IT stakeholders in the room, not afterwards.
5. Rollout
Champions, a 30-60-90 plan, manager scoreboards and a follow-up clinic to keep adoption climbing.
6. Measurement
Baselines taken before the session are re-measured after it, so you can show finance a number.
Ratio we hold to: roughly 30% teach, 70% lab. Participants leave with work they actually finished, not notes they will not reread.
Where we deliver
On-site anywhere in India, virtual, or hybrid across multiple sites and time zones (IST (UTC+5:30)).
Frequently on-site at: Mumbai · Delhi NCR · Bengaluru · Hyderabad · Chennai · Pune · Kolkata · Ahmedabad & GIFT City · Kochi · Jaipur · Indore · Chandigarh tricity.
Cohort size
Hands-on cohorts of 20–35 for facilitator attention during labs. Multiple back-to-back cohorts for larger populations. Keynote formats scale to several hundred.
Language: English delivery with Hindi and regional-language output QA.
Duration & scheduling
Half day, one day, two days, or a phased 4–12 week rollout. Weekend and split-shift schedules available for operations teams.
Lead time: 2–4 weeks is typical, to allow discovery and content rebuild.
GOVERNANCE, SECURITY & COMPLIANCE
The section your risk function will read first
Adoption dies at the control conversation unless the training answers it directly. We write your AI-use standard during the programme, with risk, legal and IT in the room — mapped to DPDP Act 2023, RBI/SEBI/IRDAI circulars, ISO 27001 control mapping and client contractual clauses.
- NDA signed before any material changes hands
- Redacted or synthetic samples unless you authorise otherwise
- No client material retained after the engagement
- Delivery inside your own tenant where required
- A written data-classification grid: permitted, restricted, prohibited
- Named review and sign-off responsibility per output type
- Logging and evidence trail your auditors will accept
- Incident drill: what happens when an AI-assisted error escapes
MEASUREMENT & ROI
You will be able to show finance a number
Before the session we baseline three real tasks — actual minutes, actual rework, actual review rounds. Thirty days later we re-measure the same three tasks and write it up. No satisfaction scores standing in for impact.
Typical outcomes on documentation-heavy roles: 6–12 hours saved per participant per month, review rounds down from three to one, and weekly active usage climbing rather than decaying after week four.
- Pre-training baseline on three named tasks
- Weekly active usage tracked by function, not headline licence count
- Review-round and rework-rate measurement
- A 30-day adoption report with the actual numbers
- Manager scoreboard so line leaders own adoption
- Quarterly re-measurement built into the rollout plan
INCLUDED AS STANDARD
What you keep after everyone goes back to work
These are not upsells. Every engagement ships with all eight.
Role-based prompt library
A reviewed, versioned prompt pack for every function in the room — not a generic list of 100 prompts.
Reusable templates & artefacts
Working project spaces, document templates and checklists configured against your own material during the labs.
AI-use governance one-pager
A plain-language standard covering permitted data, review responsibility and logging — ready to circulate internally.
30-60-90 rollout plan
Named owners, target workflows and success metrics for the three months after the session.
Champion enablement pack
Everything your internal champions need to run their own follow-on clinics.
Session recordings & handbook
Recordings plus a written handbook so joiners after the programme are not left behind.
Certificate of completion
Individual certificates for every participant, plus an attendance and completion report for L&D.
Post-programme office hours
A scheduled clinic after 30 days to unblock real work, not hypothetical questions.
WHO DELIVERS IT
Hitesh Motwani — Lead AI Trainer & Founder, Skillopedia
Hitesh Motwani has spent 17+ years teaching professionals how to actually work differently — not just how a tool works. He has trained 200,000+ professionals, delivered 50+ keynotes, and taught at IIMs, ISB, BITS and SP Jain. Since 2023 his practice has been almost entirely generative AI: designing and delivering governed, hands-on AI programmes for banks, pharma majors, manufacturers, media networks and global capability centres. He builds the workflows himself before he teaches them, which is why the labs work on real documents instead of toy examples.
- 17+ years in corporate learning and communication
- 200,000+ professionals trained across 335+ organisations
- Faculty and guest speaker at IIM Ahmedabad, IIM Bangalore, ISB, BITS Pilani and SP Jain
- 50+ keynotes on generative AI, AI agents and the future of work
- Programmes delivered across India, the GCC, ASEAN, the UK and the US
- 4.9 / 5 average participant rating across a decade of delivery
WHAT PARTICIPANTS SAY
4.9 / 5 across a decade of delivery
“The first AI session our compliance team did not walk out of. The governance one-pager alone paid for the programme.”
VP, Digital Transformation
Financial services
“We had licences for eight months and almost no usage. Sixty days after the programme we were at 86% weekly active in the commercial team.”
Chief Technology Officer
Real estate & development
“The labs used our actual documents. That is the whole difference — people finished real work in the room instead of watching a demo.”
Head of Learning & Development
Pharmaceuticals
“Hitesh told us to not buy a tool we were about to buy. That is when I knew this was not a sales pitch.”
General Manager, Technology Strategy
IT services
“Our medical writers are saving around eleven hours a week each, and the review quality went up, not down.”
Director, Medical Affairs
Life sciences
DELIVERY ACROSS INDIA
We come to you, anywhere in India
Most programmes run on-site in your own offices — it makes the labs better, because the systems and the documents are right there. Virtual and hybrid delivery is available where teams are distributed.
Delivery options
- On-site at your office or an offsite venue
- Virtual cohorts with live labs and breakouts
- Hybrid across multiple sites and time zones
- Split schedules for shift-based operations teams
- Multi-city rollout with one shared standard
- Private cohorts only — never mixed with other clients
FREQUENTLY ASKED QUESTIONS
Everything procurement usually asks
No. We can run the programme on free or trial tiers so your team learns the method first, and we will tell you honestly which paid features are worth buying afterwards for your specific workflows. If you already hold enterprise licences, the labs are configured against your own tenant so nothing has to be re-learned later.
Yes — that is the core of how we work. Before delivery we run a discovery call, collect a sample of your real (redacted) artefacts and rebuild the labs around them. A India bank, a manufacturer and a media network do not get the same session, because their documents, reviewers and regulators are not the same.
We sign your NDA, work only with redacted or synthetic samples unless you explicitly authorise otherwise, and never retain client material after the engagement. The governance module maps your controls to DPDP Act 2023, RBI/SEBI/IRDAI circulars, ISO 27001 control mapping and client contractual clauses. Where required we deliver inside your own tenant so no data leaves your environment.
Half-day executive briefings, one-day functional programmes, two-day technical tracks, multi-week enterprise rollouts and 60–90 minute keynotes. Delivery is on-site across India, virtual, or hybrid across multiple locations and time zones.
Hands-on cohorts work best at 20–35 participants so every person gets facilitator attention during labs. We run multiple cohorts back to back for larger populations, and keynote formats scale to several hundred people in one room.
We baseline three real tasks before the session — actual minutes, actual rework — and re-measure the same tasks 30 days later. You get a written adoption and impact report with the numbers, not a satisfaction score. Typical outcomes are 6–12 hours saved per participant per month on documentation-heavy roles.
Free content teaches features. This teaches a governed method: what your team may use AI for, how output is reviewed, who signs it off, and how the standard survives after the trainer leaves. That is the part that determines whether adoption compounds or decays.
Yes. Every participant receives a certificate of completion, and L&D receives an attendance and completion report plus the post-programme adoption review.
Yes. We regularly run multi-city and multi-country rollouts with a single shared standard, local output-QA labs and a consolidated adoption scoreboard. English delivery with Hindi and regional-language output QA.
You keep the prompt library, templates, governance one-pager and 30-60-90 plan. Your certified champions run follow-on clinics, and we hold a scheduled office-hours session after 30 days to unblock real work.
Two to four weeks is typical — enough time for discovery, artefact collection and content rebuild. Urgent slots can sometimes be accommodated; the fastest way to check availability is a 20-minute discovery call.
Pricing depends on format, cohort count, customisation depth and location. Half-day briefings, one-day functional programmes and multi-week enterprise rollouts sit at very different price points. We quote a fixed fee after the discovery call — no per-seat surprises.
NEXT STEP
Your competitors in India are already training. Are you?
Send the form, or book the call directly. Either way you get a written outline built on your own documents within one working day — and an honest answer about whether we are the right fit.