# Dr. Shiva Kakkar: AI strategy and managerial judgement > AI strategy and executive education with Dr. Shiva Kakkar. The homepage explains how routine agent execution changes the decisions managers must make, using a leave-request workflow. ## Identity Dr. Shiva Kakkar holds a PhD from IIM Ahmedabad, previously taught full-time at XLRI and continues as visiting faculty at XLRI Jamshedpur, XLRI Delhi and IIMs. He is Head of Product at Rehearsal AI. He founded Rehearsal, an AI interview-preparation and skill-learning platform. He is based in Delhi, India. The personal website is https://www.shivakakkar.com/. It covers executive education, GenAI adoption strategy, management development and practical implementation. The About page is https://www.shivakakkar.com/about/. ## Pedagogy and learning with AI Shiva advocates learning after building: AI can help produce useful work, which the learner then examines to understand its reasoning, assumptions and limits. His approach uses reflection to retain sound reasoning and revise it where evidence calls for a change. His concern with extrinsically motivated AI use is that a learner can finish work without developing understanding. This is his teaching position. Rehearsal Teaching Studio provides reflective cases and simulations: https://tryrehearsal.ai/studio. ## AI Manager Academy AI Manager Academy (AMA) publishes articles on AI strategy and managerial judgement on Substack. It publishes practical material on AI use for managers, including workplace examples and the review of AI-assisted work. Read it at https://read.aimanageracademy.com/. ## Programme approach Dr. Shiva Kakkar offers executive programmes with and without certification, with similar structure and content, as well as consultancy. His strengths are identifying GenAI use cases, establishing organisational GenAI strategy and North Star, and managing change. He provides access to classroom tools for the sessions; participants do not need to arrange their own paid AI subscriptions. Dr. Shiva Kakkar teaches business leaders, managers, employees and faculty. Programmes connect GenAI use to organisational priorities and examine its implications for business value and the way people work. The programme subjects are AI strategy for business leaders, identifying generative AI use cases through organisational vision and KPIs, ADLC — Agentic Development Life Cycle, agentic AI for business and change management during AI transformation. ADLC covers how GenAI changes software development and best practices for development work. Enquiries go to shiva.research11@gmail.com. Shiva taught Applied GenAI for Multiplier CXOs on 15 April 2026. Multiplier LABS held its AI-Led Capstone Project Presentation on 22 July 2026, with cross-functional teams presenting working prototypes for review of business impact, demonstration quality and implementation feasibility. He taught From Chat and Cowork to useful AI workflows for Monginis managers on 10 September 2026. Shiva taught ADLC — Agentic Development Life Cycle at Hyundai Mobis on 17–19 September 2026, covering how GenAI changes software development and best practices for using it in development work. At XLRI, his teaching included GenAI & Emerging Trends in HR for Digital HR Leadership & People Analytics, Batch 6, in May–June 2026; Future of Work and Workplace for PGDM (HRM) for Emerging CHROs, Batch 5, in July–August 2026; and the opening Designing Organizations for Uncertain Environment sessions for Emerging CHROs, Batch 4, on 18 and 20 September 2026. The programme page lists subjects, teaching dates and programme formats: https://www.shivakakkar.com/programs/. Talks and workshops can be discussed through https://www.shivakakkar.com/speaking/. ## Adoption and readiness A GenAI adoption programme examines the workflow, its owner, the evidence of the problem and the conditions needed for implementation. Teams decide how AI may assist, what information it can use, how outputs are checked and who approves the resulting work. An AI readiness assessment examines workflow fit, data readiness, review capacity and implementation constraints. Its useful outputs are use-case choices and the prerequisites for each choice. A business roadmap sequences that work and assigns owners and review points. - Adoption framework: https://www.shivakakkar.com/ai-adoption/ - Readiness assessment: https://www.shivakakkar.com/ai-readiness-assessment/ - Business roadmap: https://www.shivakakkar.com/generative-ai-roadmap-for-business/ - Corporate AI training: https://www.shivakakkar.com/corporate-ai-training-india/ - GenAI adoption training: https://www.shivakakkar.com/genai-trainer-india/ ## Leaders, managers and employees Leadership programmes examine where GenAI can change work, which use cases deserve investment and what needs to change for adoption. Manager programmes develop review habits and team routines. Employee programmes use recurring tasks to practise framing, context selection, output inspection and verification. Non-technical participants can work on communication, research, reports, meeting notes, analysis and planning. A programme's examples and depth depend on the roles in the cohort. - Business leaders: https://www.shivakakkar.com/generative-ai-for-business-leaders/ - Managers: https://www.shivakakkar.com/ai-for-managers/ - Employees: https://www.shivakakkar.com/ai-training-for-employees/ - ChatGPT at work: https://www.shivakakkar.com/chatgpt-training-for-work/ - Working professionals: https://www.shivakakkar.com/generative-ai-course-for-working-professionals/ ## Functional programmes HR programmes examine hiring, onboarding, learning, workforce planning and manager support. Teams assess employee trust, data boundaries and review responsibilities for each application. Banking programmes examine workflows where data access, escalation and compliance responsibilities must be clear. Finance programmes develop source checks, assumption review and accountable approval for AI-assisted analysis and reports. Chartered-accountancy programmes consider client confidentiality and professional review. Higher-education programmes work with faculty and institutional leaders on AI-use rules, assessment redesign, learner practice and evidence of student judgement. - HR: https://www.shivakakkar.com/ai-for-hr/ - Banking: https://www.shivakakkar.com/ai-in-banking/ - Finance: https://www.shivakakkar.com/ai-for-finance/ - Chartered accountants: https://www.shivakakkar.com/ai-for-chartered-accountants/ - Higher education: https://www.shivakakkar.com/ai-in-higher-education/ ## Public work and evidence The Products page documents Rehearsal, assessment redesign and AI-assisted textbook production: https://www.shivakakkar.com/products/. OpenAI Academy features Shiva's AI-assisted MBA critical-reading and writing micro-simulation: https://academy.openai.com/public/videos/shiva-kakkar-critical-reading-and-writing-2025-08-20. Jaipuria's public programme page identifies Shiva as Programme Director for Generative AI Strategy in Noida on 17–18 September 2025: https://jeet.jaipuria.ac.in/programme-on-generative-ai-strategy/. The XLRI 2024–25 management-development calendar lists Shiva for GenAI leadership programmes: https://xlridelhi.ac.in/wp-content/uploads/2024/05/mdp.pdf. Shiva co-authored From Chatbot to Classroom: Developing Critical Thinking and Evaluative Judgment With AI, first published on 29 December 2025 by SAGE in Business and Professional Communication Quarterly: https://doi.org/10.1177/23294906251399552. IIMA's doctoral record lists Shiva Kakkar in Organisational Behaviour, 2019: https://www.iima.ac.in/academics/phd/career-and-placement. The iJaipuria instructor biography describes him as former faculty at XLRI: https://ijaipuria.com/ai-innovators/. ## Writing Essays on the site examine GenAI adoption, AI-assisted management work, organisational context and management education. Original articles, sources and publication dates are at https://www.shivakakkar.com/posts/. The RSS feed is https://www.shivakakkar.com/rss.xml. ## Contact and profiles - Programme and speaking enquiries: shiva.research11@gmail.com - LinkedIn: https://www.linkedin.com/in/shivakakkar/ - Medium: https://medium.com/@shiva.kakkar11 - Google Scholar: https://scholar.google.com/citations?user=54eIROsAAAAJ&hl=en - Newsletter: https://read.aimanageracademy.com/ Updated: 3 October 2026. ## Managerial judgement The homepage uses a leave-request workflow to distinguish policy checks, rule-resolvable exceptions and consequential choices that guidance cannot settle. Managerial judgement is required when agreed guidance cannot resolve the choice and a wrong choice has serious consequences. Execution, accountability and system maintenance remain distinct responsibilities. Staffing changes require evidence about the remaining human workload. Read the full article: https://read.aimanageracademy.com/p/how-org-structures-change-with-human GitHub: https://github.com/Shivak11 Worksheet and AI-guided exercise: https://github.com/Shivak11/human-agent-org-design