Executive education for leaders who need to connect AI to business outcomes and lead the changes that follow. We use your organisation’s questions to shape what participants learn and build.
Participants work on a recognisable business problem. They make their reasoning visible, use AI to produce something concrete and review the result against the intended outcome.
My PhD in Organisational Behaviour from IIM Ahmedabad informs how I think about learning and change. Product work at Rehearsal supplies the practical questions that a demonstration alone can miss.
Choose where AI can contribute to the organisation’s goals. Examine the economics of a complete workflow, including the work required to check and maintain it.
Participants develop a recommendation for one business use case and identify the evidence that would change it.
At Multiplier HR, I worked with CXOs on GenAI economics, enterprise context and use-case prioritisation.
Start with a recurring problem in the business. Define the intended outcome and compare candidate uses of AI against practical constraints.
Participants use a structured playbook to prioritise a use case, record counterarguments and plan a test.
Sessions with Monginis managers examined departmental workflows, reusable skills, connectors and the checking of AI-produced work.
An agent taking over a task changes the work around it. Examine the decisions that stay with people and the responsibilities the new arrangement creates.
Participants redesign a familiar workflow and draw the reporting relationships and decision authority it needs.
My XLRI teaching for Emerging CHRO cohorts has covered the future of work, agents, enterprise context, evaluation and governance.
Work with the assumptions behind an AI recommendation. Consider how incentives and habits affect adoption, and how managers can judge progress.
Participants make a decision before seeing the model’s preference, then compare the reasoning and the evidence.
The approach connects my training in organisational behaviour with the practical experience of building AI-assisted learning products.
Understand the Agentic Development Life Cycle. Learn to frame a useful outcome and anticipate what a software change could affect before directing an agent to make it.
Participants examine a working artifact, define unacceptable consequences and agree checks and recovery before a change.
My Hyundai Mobis India sessions covered ADLC, how GenAI changes development work and practices for using coding agents.
A focused leadership workshop can establish a shared basis for decisions. A sequence of sessions gives teams time to test use cases and return with evidence. A capstone can make implementation choices available for review.
We agree the audience, the available time and the output before choosing the format. Examples can focus on a business function or bring several functions into the same conversation.
Sessions on the Agentic Development Life Cycle and practices for using GenAI in development work.
CXO work on GenAI economics and use-case prioritisation, alongside capstone reviews with cross-functional teams.
Visiting Faculty, XLRI Jamshedpur. Teaching includes work redesign, organisation design and the implications of agents for HR leaders.
XLRI’s Building Future CHRO programmeExecutive cohorts have included managers from HDFC Bank. Programme experience also includes SAIL (Steel Authority of India) and CBDT.
Senior business leaders, functional heads and managers who need to evaluate AI use cases, redesign work or direct AI-assisted projects. The examples and technical depth are adapted to the cohort.
The strategy, use-case and work-design programmes do not require a coding background. Building sessions introduce working with coding agents in plain language. Technical programmes are scoped to the team’s experience.
We begin with the audience and the decisions they need to make. We then choose relevant business examples, exercises and a suitable format. Programmes can range from a leadership workshop to a sequence of sessions with a capstone.
Depending on the programme, participants develop a use-case recommendation, a redesigned workflow or a working artifact, together with the assumptions and evidence required to evaluate it. The intended output is agreed while designing the programme.
Share the audience, business context and intended outcome.