Quick answer: artificial intelligence corporate training teaches your people to use the AI tools you already license, such as ChatGPT, Microsoft Copilot, Claude, Gemini, AI agents and n8n, on their real emails, reports, spreadsheets and decks. Hitesh Motwani builds one programme for each audience, from the boardroom to the front line, sets the data rules with your IT team, and supports people for 90 days so the habits stick.
Individuals: live cohort batches of the AI Accelerator Program are enrolling. Reserve yours →
Teams at these organisations have trained with Hitesh Motwani and Skillopedia
200,000+ professionals · 16+ countries · 4.8★ average session rating · Corporate clients include Google, Microsoft & Tata Group
The hub for every corporate AI programme Hitesh Motwani runs, with links to the programme for each group.
| What buyers ask | The short answer |
|---|---|
| What is it? | Live, hands-on training that makes AI part of daily work across an organisation, planned audience by audience rather than as one webinar for everyone. |
| Who is it for? | Boards and CXOs, people managers, function teams, all employees, HR and L&D, and technical teams who build with AI. |
| Which tools? | The ones your IT team has approved: ChatGPT, Microsoft 365 Copilot, Claude, Gemini, NotebookLM, agent and automation platforms such as n8n and Copilot Studio. |
| How long? | Half-day leadership briefings, 1- or 2-day workshops, or multi-week programmes with weekly labs. |
| Where? | On-site at your offices across India and the UAE, or live online for teams anywhere. |
| Cost? | Quoted per engagement, after a short brief: group size, sessions, customisation and travel change the number. |
It is the most common story in corporate AI. The tools arrive, a webinar runs, usage climbs for a fortnight and then quietly flattens. The problem is rarely the technology. It is how people were trained to use it.
| What you see | What is really going on | What the training changes |
|---|---|---|
| Licences bought, little use | People were given access and a feature tour, but never shown where AI fits in their own week | Each group rebuilds two or three of its own recurring tasks with AI in the room |
| Usage spikes, then fades | One awareness session, then nothing to reinforce the habit | Follow-up clinics at 30, 60 and 90 days, plus a shared prompt library |
| Staff use personal AI accounts | No clear rules, or rules nobody has read | A plain-language AI usage policy taught inside every session |
| Leaders unsure what to fund | Pilots chosen by enthusiasm, not by value | A leadership briefing that ranks use cases and agrees a 90-day plan |
| Same session for every team | Finance and sales have very different work | Function tracks built on each team’s own files and KPIs |
| No evidence for the board | Success measured by attendance | A day-zero baseline and a behaviour check agreed before training starts |
The fix: fewer features, more of people’s own work. An analyst who finishes her real monthly report with AI, under your data rules, does it again next month unprompted. Across a team, the time saved compounds.
Most organisations combine three or four into one roadmap, each rebuilt around your people, tools and data rules.
Where AI moves your numbers, what to fund and what to refuse, how to read an AI business case, risk and accountability, and a 90-day adoption plan agreed in the room.
Typical format: half-day closed-room briefing
Managers learn to spot AI-ready work in their team, coach people through it, review AI output and keep quality high, because adoption follows the manager.
Typical format: 1 day, plus a manager clinic
Finance, HR, sales, marketing, legal and operations, each on its own KPIs, templates and workflows, with industry depth for BFSI, pharma, manufacturing and aviation.
Typical format: 1–2 days per function
Prompting and context, research, writing, analysis and safe use of company data, in the tool every employee already has. The foundation every other track builds on.
Typical format: half-day or 1 day in waves
Hiring, onboarding, policy assistants and HR analytics, plus how the L&D team itself designs, builds and measures training faster with AI.
Typical format: 1 day workshop
RAG and knowledge apps, AI-assisted coding with Claude Code, GitHub Copilot and Cursor, evaluations, guardrails and deployment for teams who ship software.
Typical format: 2 days or multi-week labs
Design agents that watch inboxes, move data and finish multi-step tasks, with n8n, Make, Zapier, Copilot Studio and MCP, and with a human sign-off built in.
Typical format: 2 days, then build sprints
A small group from each department learns to run clinics, maintain the prompt library and spot the next use case, so the programme keeps going after the trainer leaves.
Typical format: monthly sessions for a quarter
Share your team size, the AI tools you already license and the work that should change. Hitesh’s team will send a programme outline by audience, the formats that fit and a quote. Prefer to talk first? Book a free call.
Train people in the tool they will open on Monday morning. A brilliant session in a tool your IT team has not approved produces enthusiasm, then nothing, or company data in personal accounts.
| Tool | Best fit in a company | What teams practise | Go deeper |
|---|---|---|---|
| ChatGPT | Organisations on ChatGPT Business or Enterprise workspaces | Projects for recurring work, deep research, data analysis on uploaded files, drafting and review | ChatGPT training |
| Microsoft 365 Copilot | Companies running Outlook, Teams, Word, Excel and PowerPoint | Meeting recaps in Teams, Excel analysis, first drafts in Word, decks from documents, Copilot Chat | Copilot training |
| Claude | Teams with long documents, careful writing and analysis | Projects with reference files, long-report analysis, Cowork and agentic workflows | Claude AI course |
| Google Gemini | Companies on Google Workspace | Gemini in Gmail, Docs and Sheets, Gems, and source-grounded notebooks | Gemini training |
| AI agents and n8n | Operations, sales ops and IT teams automating multi-step work | Agent design, triggers, API and MCP connections, n8n, Make, Zapier and Copilot Studio flows with human approval steps | Agentic AI training |
| Claude Code and coding assistants | Engineering and data teams | AI-assisted coding, refactoring, tests and documentation, with review rules | Claude Code training |
Product names and plans change often. We confirm current features against each vendor’s official documentation when we design your programme, and we sell or resell none of these tools.
A typical employee programme follows these nine modules, adapted for each audience and built on your own material.
| Module | What people learn to do |
|---|---|
| 1. How AI tools work | What large language models are good and bad at, why they make things up, and which tool suits which job |
| 2. Prompting and context | Give role, task, context, examples and format; attach the right files; iterate instead of starting over |
| 3. Safe use of company data | Your AI usage policy in practice: what never goes in, approved accounts, checking outputs before they leave the building |
| 4. Writing and communication | Emails, proposals, policies and summaries in your house style, reviewed for accuracy and tone |
| 5. Research and analysis | Summarise long reports, compare documents, analyse spreadsheets and explain the numbers in plain language |
| 6. Presentations and reports | Turn a document into a deck outline, build a monthly report faster, draft charts and speaker notes |
| 7. Reusable assistants | Projects, Gems, agents and prompt templates the team shares, so good work becomes repeatable |
| 8. Automation and agents | Where a multi-step task can run on its own, where a person must approve, and how to start small |
| 9. Your 30-day plan | Each person leaves with two workflows to use next week and a way to show what changed |
| Format | Best for | Sample agenda |
|---|---|---|
| Half-day (3–4 hours) | Leadership briefings; a first session for all staff | Where AI pays off in your business · live demos on your own documents · risks and data rules · choosing three priority use cases · next 90 days |
| 1 day (6–7 hours) | Function teams and managers | Morning: tools, prompting and safe use, then two hands-on labs on the team’s own files · Afternoon: analysis and reporting lab, building a shared assistant, personal 30-day plan |
| 2 days | Deeper function tracks, agents and builder teams | Day 1 as above · Day 2: reusable assistants, automation and agent design, a team build of one real workflow, review and show-and-tell |
| Multi-week (4–12 weeks) | Company-wide rollouts and champion networks | A kick-off workshop, then weekly or fortnightly 2-hour labs, office hours for questions, and clinics at 30, 60 and 90 days |
This is the core of Hitesh’s method. Participants bring live work, complete it with AI in the room while he checks prompts and outputs, and leave with workflows they use the next morning.
| Their own work | What they do in the session | What they keep |
|---|---|---|
| Emails | A sales manager drafts replies to three real (anonymised) client emails, sets tone and constraints, then checks every claim before sending | A reply template and a checklist for client-facing AI drafts |
| Reports | An operations lead uploads last month’s report and this month’s raw notes, and asks for a first draft in the same structure, with gaps flagged | A reusable report assistant set up in the company’s approved tool |
| Spreadsheets | A finance analyst asks AI to explain variances in a masked budget sheet, write the formulas and suggest the three questions the CFO will ask | A tested prompt for monthly variance commentary |
| Decks | An HR business partner turns a policy document into a ten-slide briefing for line managers, with speaker notes and a short quiz | A deck outline and a method to repeat for every policy update |
Illustrative exercises, not promised results. Sensitive files are masked or replaced with synthetic copies first. The point is a repeatable way to do a weekly task, not one output.
Every engagement, from one briefing to a company-wide rollout, follows four stages that turn a training day into lasting change.
A call and a short questionnaire: who is in the room, which tools are approved, your data policies and the workflows that eat the most hours. We agree what “working” will look like.
A written outline built on your real documents and tools, with every exercise named, the agenda for each format and the data rules for the session. You approve it before delivery.
Hands-on labs, on-site or live online, where people rebuild their own reports, decks, analyses and processes. Hitesh checks prompts and outputs as they work.
Clinics at 30, 60 and 90 days, a shared prompt library and a champion network, plus a written summary of what each group built and what to train next.
Every programme teaches your AI rules inside the exercises, not on a compliance slide.
| Question | What we settle with your IT and legal teams |
|---|---|
| Which accounts? | Company workspaces with admin controls, not personal sign-ups. Training happens in the accounts people will keep using. |
| What data may go in? | A short list of what never goes into any AI tool, such as personal data of staff or customers, client confidential material, salaries, health data and unreleased results. |
| How are outputs checked? | Who reviews AI-generated content before it reaches a client, a regulator or the public. |
| Training files? | Masked or synthetic copies, under your NDA. |
A general overview for planning, not legal advice. Laws, rules and timelines change; your legal and compliance teams should confirm what applies to you.
Be wary of anyone who promises a fixed percentage before they have seen your work. Real impact depends on your tasks, your tools and your managers, so measure it against your own baseline.
| What to check | When | How |
|---|---|---|
| Baseline | Before training | Pick two or three tasks per team and record how long they take, how often AI is used and where quality slips |
| Capability | End of session | A practical exercise on a real task, reviewed against a simple rubric, not a recall quiz |
| Usage | 30 and 60 days | Usage reports from your AI platform where the plan provides them, plus a two-question pulse survey |
| Behaviour | 60 and 90 days | Manager check-ins: which tasks now run differently, and what is still stuck |
| Business result | 90 days onwards | The baseline tasks measured again: cycle time, rework, turnaround, fewer repeat questions |
Attendance and smile sheets do not show that work changed; a baseline agreed in discovery does. For documented engagements, see the anonymised AI training case studies, including a telecom team’s Claude rollout and a phased programme for 1,000 airline employees.
Most organisations combine several. The question is which turns licences into daily work.
| Option | Good for | Watch out for | Practice on own work? |
|---|---|---|---|
| Vendor launch webinars | Feature awareness when a tool goes live | Shows features, not your workflows; one tool only | Rarely |
| Self-paced e-learning library | Basic concepts at scale, low cost per head | Low completion; nobody checks real outputs | No |
| Internal champions only | Ongoing peer support and local examples | Champions need training themselves and time in their week | Sometimes |
| Large training company programme | Very large rollouts across many locations at once | Ask who actually trains, and whether exercises are generic | Varies |
| Hands-on corporate training with Hitesh Motwani | Leadership alignment plus function-by-function adoption | Built for live, hands-on groups rather than recorded content | Yes, in every session |
Running a vendor selection? Our review of corporate AI training providers and companies compares ten options. For how learning teams use AI inside training itself, read the guide to generative AI in corporate training.
Hitesh Motwani, Mumbai and Dubai
Hitesh Motwani has spent 17+ years in corporate training rooms. His sessions are built on one idea: people change how they work when they practise on their own work. Teams leave with finished outputs and workflows they use the next morning, and the time saved compounds across the organisation, so it executes faster.
Expertise in LLMs, AI agents, prompt engineering and automation; leadership-focused AI training for founders and CXOs; vendor-neutral, reselling no tools.
“Hitesh’s Claude AI session was the most practical AI training our leadership team has attended. They walked out with actual workflows they could use the next morning, not just slides.”
“We had run three AI trainings before this. It was the first one where people were still using what they learned a quarter later, and the first where I had adoption numbers for my board deck.”
“Hitesh Motwani’s AI tools and ChatGPT training was a game-changer. Hitesh’s passion and simplified approach made the sessions engaging. … Hitesh is an exceptional trainer.”
“Hitesh’s depth of understanding on how the generative AI space is changing and how to write perfect prompts was awesome.”
Hands-on AI workshop with a corporate team in India
CMO workshop, IIM Bangalore
Corporate training, CapitaLand, Bengaluru
Corporate training with SME and B2B teams, Delhi
Choose by audience and by how much hands-on time each group needs.
| Delivery | Where | Notes |
|---|---|---|
| On-site | Your offices across India and the UAE, including Mumbai and Dubai | Best for hands-on labs and leadership sessions; travel quoted with the engagement |
| Live online | Worldwide, on your time zone | Interactive cohorts for distributed teams, with the same labs and clinics |
| Blended | On-site kick-off, then online labs and clinics | Common for multi-week rollouts across several cities |
Sessions in English or Hindi. Engagements run under your NDA. City and country programmes are listed on the AI training locations page.
The questions HR, L&D and leadership teams ask most before they commission a programme. Have one that is not here? Send it and you will get an honest answer.
It is training that teaches employees to use AI tools such as ChatGPT, Microsoft Copilot, Claude and Gemini in their daily work, safely and within company rules. Good programmes are planned by audience and built on people’s real tasks, not generic demos.
How AI tools work and where they fail, prompting with context, safe use of company data, writing, research and analysis, presentations and reports, reusable assistants, an introduction to automation and agents, and a personal plan for the next 30 days. See the sample curriculum.
A leadership briefing takes half a day. Function teams usually need one or two days. Building lasting habits across a company takes four to twelve weeks, with labs and follow-up clinics at 30, 60 and 90 days.
It depends on group size, number of sessions, customisation and travel, so Hitesh quotes per engagement. Send a short brief through the form and you will receive a written outline and quote.
The tools your company has already approved and licensed. Microsoft 365 companies usually start with Copilot, Google Workspace companies with Gemini, and many organisations add ChatGPT or Claude for specific teams. See programmes by tool.
No. Leadership, manager, function and all-staff programmes need no coding. Only the builder, agent and engineering tracks go into code, APIs and automation platforms.
Train each team on its own recurring tasks rather than features, make the data rules clear, involve managers, and follow up at 30, 60 and 90 days.
Yes, if you use company accounts with admin controls, keep personal and confidential data out of exercises unless your policy allows it, and mask sample files. Every programme teaches your AI usage policy inside the exercises. See governance.
In a short, closed-room session focused on decisions: where AI moves the numbers, what to fund, risks and accountability, and a 90-day adoption plan. More on the AI training for leaders programme.
Record a baseline for two or three tasks per team before training, then check capability at the end of the session, usage at 30 and 60 days, and the same tasks again at 90 days.
Both. Hitesh delivers on-site at offices across India and the UAE, including Mumbai and Dubai, and live online for teams worldwide. Many rollouts combine an on-site kick-off with online labs.
This page covers company programmes. Individuals can join a live batch of the AI Accelerator Program, with Claude Mastery, Generative AI Mastery and AI Agents tracks.
A corporate AI trainer with 17+ years in training and the author of Generative AI 360°. He has trained 200,000+ professionals across 16+ countries, and his corporate clients include Google, Microsoft and Tata Group. More on the about page.
Specialised pages for each audience, tool and decision.
Tell us which group comes first, the tools they use and what they deliver each week. You will get a written outline, named exercises and a clear quote.
On-site across India and the UAE · Live online worldwide · English and Hindi
Choose a slot that suits you. The call is free, takes about fifteen minutes and there is no obligation.
Calendar not loading? Open the booking page.
Tell us which groups come first, which tools they use and what they deliver each week. You will get a written outline, an agenda for each format and a clear quote.