Executive Programme in Artificial Intelligence and Generative AI for Managers
Lead AI-driven business transformation
About the programme
The Executive Certificate Programme in Artificial Intelligence and Generative AI for Managers is a 5-month online programme designed for early-to-mid managers, business heads, strategy leaders, entrepreneurs, and consultants leading AI-driven transformation. Designed by SPJIMR faculty, the programme is delivered through a blend of pre-recorded faculty sessions, weekly live mentored learning sessions led by industry practitioners, monthly live masterclasses by SPJIMR faculty, assessments, and hands-on projects. It combines strategic insight with practical execution and doesn’t require candidates to have prior coding knowledge.
The curriculum is designed to equip learners with the skills to lead the transition from a traditional ‘+AI’ to an ‘AI+’ operating model. It covers high-impact, real-world themes, including Generative AI and LLMs, advanced prompting techniques, RAG systems, embeddings and semantic search, Agentic AI workflows, AI economics and ROI, production readiness, and responsible AI governance. The content is aligned with India’s regulatory and digital ecosystem. With a strong case study-led approach, learners complete structured mini-projects and capstones, supported by practical assessments that reinforce key concepts and enable real-world application. Upon successful completion, learners will earn a Certificate of Completion from SPJIMR.
Reputation
SPJIMR is consistently in the top 10 of Indian B-school rankings, and is establishing a global reputation as a school dedicated to fostering responsible innovation that benefits society.
Immersive learning
Engage in weekly mentored learning sessions with industry practitioners and monthly masterclasses by leading SPJIMR faculty.
No prior coding knowledge required
Designed for managers and business leaders seeking to understand and apply AI without requiring prior programming experience.
Flexible learning for working professionals
A fully online format designed to enable professionals to learn alongside their work commitments.
Industry-relevant curriculum
Covers emerging enterprise AI topics including GenAI, LLMs, RAG systems, AI economics, governance, and production deployment.
Build an AI project portfolio
Through hands-on projects and practical use cases, develop a portfolio that showcases your ability to apply AI in real-world business scenarios.
Programme objectives
Equip business leaders with the strategic knowledge and practical frameworks required to adopt, evaluate, and scale AI and Generative AI initiatives within their organisations.
Programme outcomes
On successful completion of the programme, the learners will be able to –
Formulate AI strategy
Formulate AI strategy using the automate–optimise–predict framework and enable AI+ operating model transformation.
Design and evaluate generative AI systems
Design and evaluate Generative AI systems, including LLMs, prompting techniques, embeddings, semantic search, RAG, and fine-tuning approaches.
Build robust AI business cases
Build robust AI business cases through ROI modelling, token economics, cost estimation, and clearly defined value metrics
Architect agentic AI workflows
Architect Agentic AI workflows incorporating tool use, permissions, human-in-the-loop controls, and failure management mechanisms.
Scale AI initiatives
Scale AI initiatives from pilot to production using structured monitoring, evaluation frameworks, and lifecycle governance.
Implement responsible AI frameworks
Implement Responsible AI frameworks addressing fairness, compliance, privacy, explainability, and regulatory alignment in India.
Participant profile: Who is it best suited for
This programme is designed for professionals who want to understand and apply AI strategically within their organisations.
Ideal participants include:
Early-to-mid managers driving digital or AI transformation initiatives
Business leaders and strategy professionals responsible for innovation and growth
Entrepreneurs and founders exploring AI-enabled business models
Consultants and advisors supporting organisations in technology adoption
Product and technology leaders working on AI-enabled products and platforms
Academic credibility
Prof. Abhishek Kumar Jha
Programme director Assistant Professor, Information Management and Analytics, SPJIMR
Prof. Jha’s research focus lies at the intersection of artificial intelligence, natural language processing, information privacy, and behavioural science.
Associate Professor, Information Management and Analytics, SPJIMR
Prof. Desai brings 27+ years of experience building greenfield technology-driven financial services businesses in the Middle East, Africa, and South Asia.
The curriculum, designed by the faculty of S P Jain Institute of Management and Research, Great Learning, and leading industry practitioners, is taught by the best-in-class professors and practising industry mentors.
It is divided into four modules and is delivered through a blend of pre-recorded lectures, weekly live mentored learning sessions led by industry practitioners, monthly live faculty masterclasses, assessments, and hands-on projects.
Module 1: Foundations of AI and GenAI for managers
This module builds a strong conceptual foundation and shared vocabulary around Artificial Intelligence and Generative AI. Grounded in the AI Value Creators framework, it introduces the shift from “+AI” (AI as a feature) to “AI+” (AI as the operating model). Learners develop managerial literacy in AI, decision-making confidence, and the ability to identify high-value AI opportunities within business functions without requiring technical expertise. The module also introduces core GenAI concepts and demonstrates how AI tools can be applied to everyday business tasks.
Topics covered
AI and Machine Learning foundations for managerial decision making
Why AI now: from rule-based systems to modern GenAI
GenAI fundamentals, prompting, and everyday business use cases
Chatbots as business systems: scope, rollout, and trust basics
Module 2: AI strategy, ROI, and core building blocks of AI systems
This module connects business value with technical feasibility, helping learners understand how organisations evaluate, design, and scale AI initiatives. Learners evaluate build vs buy decisions and explore frameworks for AI strategy, investment decisions, ROI measurement, and competitive advantage through AI adoption. Learners also explore the core technical components that power enterprise-grade AI systems, including embeddings, semantic search, vector databases, and Retrieval-Augmented Generation (RAG). By combining strategic frameworks with system-level understanding, this module helps managers make informed decisions about build vs buy approaches, implementation strategy, and enterprise scalability.
Topics covered
From +AI to AI+: strategy and competitive advantage
Embeddings and semantic search: how systems represent meaning
Value creation and economics: ROI, cost, and measurement for GenAI
RAG systems and enterprise chatbots: grounded answers at scale
Execution and scaling: teams, data readiness, and operating model
Module 3: Advanced GenAI systems and agentic workflows
This module develops deeper capability in customisation, automation, and advanced Generative AI system design. Moving beyond basic AI applications, learners explore how modern AI systems are designed to retrieve knowledge, perform multi-step reasoning, and interact with tools to complete complex tasks rather than simply generate responses. The module introduces fine-tuning strategies, small language models, and agentic workflows, enabling learners to understand how organisations build AI systems that go beyond generating responses to taking actions within business processes. The focus is on reliability, evaluation frameworks, safe autonomy, and production readiness.
Topics covered
Fine-tuning and small language models: customisation choices and trade-offs
Agentic AI workflows: tool use, process redesign, and evaluation
Agent design in practice: permissions, failure modes, and controls
Production readiness: monitoring, quality evaluation, and lifecycle management
Module 4: Functional applications, India context and responsible scaling
This module focuses on domain-specific adoption of AI capabilities through real-world business applications across functions such as marketing, finance, operations, and human resources. Learners explore how organisations use AI to drive productivity, insights, experimentation, and decision support across different business domains. The module also examines AI adoption within India’s regulatory, infrastructure, and policy ecosystem, covering topics such as India Stack, the DPDP Act, and AI governance frameworks. Learners design use cases that create measurable value, manage risk, and scale responsibly. The module concludes with a governance capstone that integrates responsible AI into an enterprise operating model.
Topics covered
Marketing and growth with GenAI: content, insights, and experimentation
Finance and risk: fraud detection, forecasting, and decision support
Operations and people decisions: productivity, quality, and adoption design
India and BFSI focus: India Stack, DPDP Act, and regulated GenAI
Responsible AI and governance: controls, compliance, and enterprise scale
*Note – The above curriculum and tools are under the purview of the academic team and subject to change to ensure alignment with evolving industry requirements.
Practice-focused learning
The programme is taught through a case-study methodology, focusing on business scenarios that illustrate AI implementation across industries.
Image generator review
AI content moderation
Ads on AI platforms
AI shopping agents
Agentic AI and commerce
AI in HR and organisation building
AI models cost disruption
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*Note – Case studies are under the purview of the academic team and subject to change to ensure alignment with evolving industry requirements.
Hands-on exercises and mini projects
Structured activities to apply concepts using AI tools and frameworks.
The programme features module-level group projects. Module projects are domain-flexible and evaluated on business framing, technical implementation, and responsible design, not just on coding skills.
As part of the programme, learners will complete a series of mini-projects to reinforce practical learning and application.
Some of the sample projects are:
Project 01
Local RAG chatbot
Build a fully local RAG system for a domain-specific document set, such as an HR policy manual, product catalogue, regulatory FAQ, and so on. The system must handle 20+ realistic queries, return grounded answers with source citations.
Project 02
Production-simulated AI system
Extend the previously developed RAG chatbot into a production-simulated deployment: adding a logging layer, a quality evaluation rubric (automated plus human), a monitoring dashboard, and a 30-day maintenance plan
Capstone project
Enterprise responsible AI framework
This capstone project focuses on designing a comprehensive Responsible AI Framework that covers use-case inventory and risk classification, governance structure and roles, data governance requirements, model evaluation standards, an incident response plan, a stakeholder communication plan, and a 12-month implementation roadmap.
*Note – The above projects are under the purview of the academic team and subject to change to ensure alignment with evolving industry requirements.
Technical tools covered
Participants will gain exposure to tools and frameworks used in modern AI and Generative AI ecosystems.
Tools and technologies covered
Prompting and exploration tools
Claude.ai
Copilot
Copilot Studio
Google AI Studio
ChatGPT
Notebook LM
Privacy, compliance, and RAG development tools
LM Studio
Langchain
Deployment and interface tools
Hugging Face Model Hub
*Note – Tools are subject to change. Equivalent tools or frameworks may be substituted based on availability, compatibility, or advancements in the field.
Certificate
On successful completion of the programme, participants will get the following certificate.
Join the programme
Eligibility
Candidates should hold a Bachelor’s or Master’s degree and a minimum of 1 year of work experience.
S. P. Jain Institute of Management & Research (SPJIMR) has partnered with Great Learning to offer the Executive Certificate Programme in Artificial Intelligence and Generative AI for Managers. Great Learning is a leading global ed-tech company for professional and higher education, serving over 14 million learners across 170+ countries, with 500 million+ learning hours delivered, a 91% course completion rate, and a 4.8/5 learner rating, supported by 8,200+ industry mentors.
Great Learning manages enrolments and delivers end-to-end learner support, programme management, and industry-led mentorship. The programme draws on SPJIMR’s academic rigour and practice-oriented approach, combining faculty-led insights with real-world application to enable professionals to drive AI-led business transformation.
