AI rarely enters a company through a grand strategy. More often, one team starts using it for research, reporting, customer support, or another everyday task. Once that experiment works, managers face a bigger question: should the idea remain a small productivity tool, or does it deserve a place in a wider business process?
That is where leadership becomes more demanding. Managers do not need to build the models themselves, but they do need to ask sensible questions about data, cost, risk, oversight, and how much responsibility should be handed to automated systems.
The five programs below approach that transition at different levels, from hands-on GenAI adoption to enterprise AI strategy and leadership.
5 AI Courses for Managers
| # | Program & Provider | Duration | Fee | Best Aligned With |
| 1 | Executive Certificate Programme in AI and Generative AI for Managers – SPJIMR | 5 months | ₹1,65,000 + GST | GenAI systems, RAG, Agentic AI, responsible scaling |
| 2 | Leadership with AI – ISB Online | 20 weeks | ₹2,39,000 + GST | Enterprise AI strategy, GenAI, Agentic AI leadership |
| 3 | Executive Program in AI for Business Leaders – SPJIMR | 7 months | ₹2,70,000 + GST | AI strategy, decision science, governance, transformation |
| 4 | PG Certificate Programme in AI & Gen AI for Managers – IIM Nagpur | 8 months | ₹2,00,000 + taxes | AI adoption, ML, GenAI, cross-functional leadership |
| 5 | Executive Programme in Generative and Agentic AI for Business Applications – IIM Indore | 24 weeks | ₹1,60,000 + GST | GenAI workflows, Agentic AI, automation, governance |
1. Executive Certificate ProgramProgram in AI and Generative AI for Managers – SPJIMR
The Generative AI for Managers program starts with the kinds of questions a manager is likely to face when GenAI moves beyond casual experimentation. It introduces prompting and AI fundamentals first, then gets into RAG, model customization, Agentic AI, economics, deployment choices, and the controls needed when these systems become part of actual work.
Delivery & Duration: The five-month program is online. Participants work through recorded faculty material, join weekly mentored sessions, and attend SPJIMR faculty masterclasses during the learning journey.
Credentials: Successful completion earns a certificate from SPJIMR. Participants also receive Executive Alumni Status subject to the program requirements.
Program Highlights: RAG and semantic search sit alongside small language model fine-tuning, GenAI economics, build-vs-buy choices, and Agentic AI architecture. The later material covers human review, monitoring, lifecycle decisions, India-focused regulation, and Responsible AI.
Outcomes: The practical work moves from building a local RAG chatbot to thinking about how to monitor such a system in a production-like setting. The final stage asks participants to put together an enterprise Responsible AI framework covering governance, risk, and implementation.
Why should you choose this course?
The curriculum connects adoption with operating discipline. Managers examine ROI, monitoring, failure controls, compliance, and lifecycle management rather than stopping at GenAI experimentation.
The projects become progressively more managerial. Technical exposure leads into deployment oversight and an enterprise governance capstone.
2. Leadership with AI – ISB Online
ISB Online treats AI as a leadership issue, not just a technology topic. The course brings together AI and ML basics with GenAI, Agentic AI, digital transformation, and questions around how companies change when AI becomes part of normal decision-making.
Delivery & Duration: The program runs for 20 weeks. A typical week requires about 4 to 6 hours across recorded faculty lessons, case work, assignments, expert masterclasses, and capstone activity.
Credentials: Leadership with AI certificate from ISB Online, plus ISB Online Alumni Status upon successful completion.
Program Highlights: Topics range from enterprise AI roadmaps and machine learning to reinforcement learning, GenAI applications, Agentic AI, data monetization, operating models, workforce planning, business-model innovation, ethics, and responsible adoption.
Outcomes: By the end of the program, participants should be better prepared to spot worthwhile AI opportunities, compare investment choices, plan adoption, and manage the organizational changes that come with bringing AI into regular business operations.
Why should you choose this course?
It is aimed at people who already carry business responsibility. The discussion focuses less on basic AI literacy and more on how experienced managers make choices about adoption, investment, and change.
Agentic AI sits inside a wider leadership framework. Autonomous systems are considered alongside organizational design, responsible AI, and enterprise transformation.
3. Executive Program in AI for Business Leaders – SPJIMR
This AI for leaders program targets professionals working with AI at a broader organizational level. It starts with business transformation and data foundations, then works through machine learning and GenAI before reaching intelligent automation, Agentic AI, governance, and enterprise strategy.
Delivery & Duration: Seven months in a blended format. The experience includes live SPJIMR faculty sessions, executive masterclasses, project work, and an on-campus immersion in Mumbai.
Credentials: Participants who complete the program receive a Certificate of Completion along with SPJIMR Executive Alumni Status.
Program Highlights: The curriculum includes enterprise data architecture, forecasting and risk modeling, LLMs, intelligent automation, multi-agent systems, agent orchestration, AI portfolio choices, ROI realization, workforce transformation, Responsible AI, and industry-focused tracks.
Outcomes: The emphasis is on making better AI decisions at scale. Participants work on identifying worthwhile opportunities, judging automation proposals, planning agent-enabled workflows with human oversight, and turning individual initiatives into a broader enterprise AI plan.
Why should you choose this course?
It moves naturally from analytics into leadership responsibility. Data, ML, GenAI, and Agentic AI are tied to portfolio choices, investment decisions, and organizational change.
The projects require executive judgment. Participants evaluate business impact, governance requirements, and solution design rather than simply demonstrating tools.
4. PG Certificate Program in AI & Gen AI for Managers – IIM Nagpur
IIM Nagpur gives managers enough technical grounding to understand what sits behind an AI proposal without expecting them to become engineers. Statistical methods and machine learning are part of the course, but the discussion keeps returning to business applications, strategy, risk, and adoption.
Delivery & Duration: The eight-month program is delivered mainly through live weekend sessions. It includes 105 learning hours and a two-day campus immersion.
Credentials: Those who complete the requirements receive the PG Certificate Programme in AI & Gen AI for Managers from IIM Nagpur.
Program Highlights: Statistical methods, supervised and unsupervised learning, deep learning, GenAI tools, AI-supported decision-making, and applications across finance, HR, marketing, and supply chain all feature in the curriculum. Strategy, project selection, risk, governance, and scaling are covered as well.
Outcomes: Managers come away better equipped to judge proposed AI investments, choose projects that fit business priorities, work across functions during implementation, and think more clearly about how value and ROI should be measured.
Why should you choose this course?
Machine learning is included without turning the program into an engineering course.
Its cross-functional coverage is useful for managers whose AI responsibilities cut across several business teams.
5. Executive Programme in Generative and Agentic AI for Business Applications – IIM Indore
IIM Indore puts the emphasis on what changes once GenAI becomes part of a business workflow. Prompting and functional GenAI applications come first. From there, the course moves into AI agents, Agentic RAG, automation, governance, and the strategic questions raised by more autonomous systems.
Delivery & Duration: The program runs online for 24 weeks, with roughly 4 to 6 hours of work expected each week. Recorded faculty content is supported by live sessions, industry interaction, and a capstone.
Credentials: Successful participants receive a Certificate of Successful Completion from IIM Indore.
Program Highlights: The learning covers the GenAI stack, prompt engineering, Agentic AI architecture, multi-agent systems, Agentic RAG, human-in-the-loop workflows, autonomous finance and supply-chain applications, AI strategy, transformation, governance, ethics, and risk.
Outcomes: Participants work on deciding where automation makes sense, how to assess feasibility and ROI, and what an adoption roadmap should look like. They also consider how GenAI and agent-based workflows can be tied to outcomes the business can actually measure.
Why should you choose this course?
Agentic AI is treated as a question of workflow design, not simply a new technology. Managers consider where autonomy is useful and where a person still needs to make the call.
The capstone connects technology with impact, requiring participants to frame an AI solution around an actual business problem.
Conclusion
Once AI starts affecting real processes, leadership questions follow quickly. Someone has to decide what deserves investment, which risks are acceptable, who remains accountable, and whether the organization is genuinely ready to change the way work gets done.
The right AI for managers program depends on that responsibility. Some professionals may need practical GenAI adoption skills first. Others may already be responsible for investment, governance, workforce planning, or enterprise transformation and need deeper preparation in strategy, Agentic AI, and organizational change.