Dr. Shiva Kakkar

GenAI programmes for CXOs, managers and teams

Programmes that turn GenAI interest into work the organisation can review.

I work with CXOs, CHROs, L&D teams, managers, employees, and faculty groups when the question is no longer whether GenAI matters. The question is where to start, which use cases are ready, and what must change after the session.

The format may be a CXO conversation, a manager cohort, an employee re-training effort, a faculty workshop, or an adoption sprint. The common thread is simple: the cohort leaves with decisions and artifacts, not only awareness.

Discuss a programme

Programme formats I do

Programme formats I do.

The same organisation may need a diagnostic before training, a lab before a longer build, or a build track after a pilot. I use formats as containers for decisions, practice, evidence, and follow-through.

AI starting-point diagnostic

Half-day or one-day working session CXOs, CHROs, Deans, L&D heads, and AI councils

For teams that know GenAI matters but are still choosing the first serious move from tool excitement, vendor pitches, or scattered internal experiments.

What happens inside
Inside the work
  • Map the decisions, workflows, policies, and knowledge sources the AI effort would touch.
  • Separate convenience tasks from work where speed, defensibility, quality, or coordination actually matters.
  • Score use cases for value, feasibility, risk, ownership, and the evidence needed after the first test.
Output A ranked starting-point map: one first-priority workflow, boundary conditions, evidence to collect, and a 30-day next action.
Why this format exists The diagnostic comes before training because the wrong first use case makes even a good workshop feel like theatre.

1-3 day AI leadership or faculty lab

Short intensive programme CXO cohorts, HR leaders, business heads, faculty groups

For senior cohorts that need enough shared judgment to sponsor AI work without pretending that every leader must become a technologist.

What happens inside
Inside the work
  • Work through live examples from strategy, HR, finance, teaching, assessment, communication, and customer work.
  • Ask participants to commit to a judgment before showing AI output, so the gap becomes visible instead of being hidden by a polished answer.
  • Translate each promising use case into owner, context, review rule, risk boundary, and follow-up decision.
Output A leadership use-case portfolio, review rubric, and first version of an AI-assisted workflow or learning artifact.
Why this format exists The lab is not an AI tour. It is a way to make senior judgment sharper around workflow, context, evidence, and accountability.

Employee and manager practice cohort

Modular cohort for a function or role family Managers, employees, functional teams, high-potential cohorts

For organisations that want everyday work to change: writing, research, analysis, review, communication, reporting, and decision preparation.

What happens inside
Inside the work
  • Start from real work samples, not artificial prompt drills.
  • Build practice loops where employees draft, inspect, verify, and revise with AI.
  • Train managers to review the evidence trail: source use, assumptions, risk, alternatives, and final human judgment.
Output A role-specific task library, verification habits, manager review rules, and examples of acceptable AI-assisted work.
Why this format exists The goal is not to create prompt collectors. The goal is to help people produce work that a manager can trust and improve.

3-6 month AI capability build

Cohort build with office hours and capstones AI champions, leadership cohorts, L&D academies, schools and universities

For institutions that do not want a one-off workshop to carry the whole adoption burden.

What happens inside
Inside the work
  • Run cohorts through assignments, office hours, use-case clinics, and capstone reviews.
  • Move from individual confidence to shared operating habits: what to automate, what to inspect, and what to refuse.
  • Use leadership reviews to decide which prototypes deserve budget, policy support, or workflow redesign.
Output AI champions, capstone prototypes, adoption rhythm, leadership review notes, and a prototype-to-practice roadmap.
Why this format exists Capability compounds only when the organisation sees practice evidence between sessions, not just attendance at sessions.

Consulting plus build track

Focused engagement after a diagnostic or lab Teams with a chosen workflow and a real implementation appetite

For organisations ready to move from training into context engineering, workflow automation, pilot planning, or selected implementation support.

What happens inside
Inside the work
  • Inventory what the AI system should see, trust, remember, ignore, and refuse.
  • Design the workflow, human review points, data boundaries, and proof trail before rushing into a tool.
  • Support prototypes, vendor conversations, internal pilot planning, and governance rhythms where useful.
Output Context inventory, pilot design, review architecture, workflow prototype, and a practical production roadmap.
Why this format exists This is where training connects to implementation. The hard part is usually not the model; it is the context and review system around it.

Higher-ed AI adoption track

Faculty lab, institution build, or assessment redesign sprint Universities, B-schools, faculty teams, programme offices

For institutions where AI has already entered through students, faculty, and administrators, but policy has outrun practical capability.

What happens inside
Inside the work
  • Redesign assignments around judgment traces, oral defense, source discipline, and AI-use disclosure.
  • Help faculty build learning artifacts instead of only listening to lectures about tools.
  • Map AI use across research, teaching, assessment, administration, and student support.
Output AI-native assessment designs, faculty-built artifacts, academic-integrity choices, and an institution adoption map.
Why this format exists The faculty-builder lens matters here. The proof is not a talk about AI; it is a teaching object faculty can actually use.

Useful starting points

Choose the entry point closest to the problem.

These pages go deeper into specific buyer needs. The decision standard stays the same: choose work with value, a safe boundary, reviewable output, and a named owner.

Corporate AI training in India

For L&D, HR, and procurement teams comparing enterprise GenAI training partners.

 AI training for employees

For organisations that want everyday work to change, not just tool familiarity.

 ChatGPT training for work

For employee cohorts that need practical AI habits around office work, privacy, and review.

 GenAI course for working professionals

For managers and professionals who need AI fluency without a developer bootcamp.

 AI adoption framework

For leaders who want the method behind workflow choice, readiness, and manager review.

 GenAI for business leaders

For executives and senior managers who need judgment, governance, and use-case strategy.

 AI in higher education

For universities and B-schools redesigning faculty practice, assessment, and student AI use.

Common questions

How to choose the right format.

Which programme format should we start with?

If the starting point is unclear, begin with the diagnostic. If leaders already agree on the first few workflows, use a 1-3 day lab. If adoption must change everyday work, run an employee and manager practice cohort. If the organisation needs champions, capstones, and review over time, use the 3-6 month capability build.

Is this prompt engineering training?

Prompting appears inside the work, but it is not the centre. The centre is workflow choice, context quality, review habits, source discipline, risk boundaries, and the question of who owns the final judgment.

What makes the programmes practical?

Participants work on familiar tasks and commit to a judgment before AI reveals a better or different path. The output is not only awareness. It is a map, rubric, prototype, task library, assessment design, or follow-up plan someone can inspect later.

Can the same method work for HR, finance, banking, or higher education?

The examples must change by domain, but the discipline is stable: choose work that matters, assemble legitimate context, define the review rule, make evidence visible, and decide what changes after the session.

Custom cohorts

When the programme has to fit your operating context.

Share the audience, function, cohort size, and the business problem behind the GenAI effort. The right format may be a CXO conversation, a manager workshop, an employee cohort, a readiness diagnostic, or a short adoption sprint built around a specific workflow.

Email Dr. Shiva Kakkar

Common formats: 1-5 days, on-site or hybrid, for focused cohorts.