Product management has evolved beyond the creation of simple roadmaps and features. In today’s world, where AI is an integral part of every product, the professionals working on such products require a more comprehensive skill set involving product strategy, AI, and the ability to make informed technology decisions.
The Executive Post Graduate Certificate in Building AI Products, Systems & Services by IIT Kharagpur is one such program designed to help professionals meet these demands. Spanning six months in duration, this live online course takes participants through the entire process of creating an AI product, including opportunity discovery, creation of an AI product design, prototyping, creation of AI systems, evaluation of system performance, and business/compliance considerations.
Instead of training individuals for one specific designation, this course helps individuals develop skills relevant to three emerging designations: AI Product Manager, AI Product Owner, and AI Solutions Lead.
AI Product Manager: Owning the "What" and "Why" of AI Products
An AI Product Manager sits at the intersection of user needs, business viability, and AI feasibility, deciding what gets built and why it matters before a single line of code is written.
Frame ambiguous problems using structured tools like the AI Suitability Matrix and the TASQ Checklist to judge whether a use case is even a good fit for AI.
Translate opportunity briefs into AI-native product specifications, including behaviour design and hallucination risk handling.
Make build-vs-buy-vs-prompt calls grounded in feasibility, cost, and regulatory considerations rather than hype.
Own the product narrative from opportunity assessment through go-to-market, balancing user trust with commercial outcomes.
This is the area where the program modules will have a most direct impact. These include AI Product Opportunity Discovery, AI-Native Product Design, and AI Product Economics & Go-to-Market, which will collectively equip the AI PM with the ability to make sound decisions by saying no to some ideas and yes to others.
AI Product Owner: Translating AI Strategy into Buildable Systems
Where a Product Manager sets direction, an AI Product Owner works closer to execution, converting product intent into prototypes, prompts, and system behaviour that engineering and data teams can actually build against.
Transition from a product spec to prototype through rapid validation and active LLM incorporation.
Outline the scope of RAG pipeline design and agentic design flows, including areas where autonomous behavior needs to be curtailed.
Establish and monitor evaluation criteria such that the behavior of AI systems remains predictable as the product scales.
Ensure proper handoff coordination across product, data science, and engineering through ready-for-production-level documentation.
The modules in the program, which are hands-on and include AI Prototyping & Rapid Validation, AI Systems & Agentic Design, and AI Evaluation & Red Teaming, are specifically designed for just this purpose, with each module resulting in an actual deliverable rather than simply a presentation slide deck.
AI Solutions Lead: Making AI Products Safe, Scalable, and Sustainable
An AI Solutions Lead thinks beyond a single product launch, taking responsibility for how AI systems perform, govern themselves, and hold up under real-world pressure once they're live.
Design analytics and experimentation frameworks to track how an AI product performs after release, not just at launch.
Build red-teaming and adversarial testing practices that surface failure modes before customers do.
Set governance, safety, and compliance guardrails so AI systems remain accountable as they scale.
Lead cross-functional response when systems drift or behave unexpectedly, a skill directly tested in the programme's capstone.
This role draws heavily on AI Operations, Safety & Compliance and AI Analytics & Experimentation, and is stress-tested in the capstone's live model-drift crisis injection, where participants defend real operational decisions in front of an IIT Kharagpur faculty panel.
Why This Programme Builds Toward All Three Roles
Most programs about AI concentrate on technology. The program is designed around the actual decision-making process that product leaders of AI have to do – what to create, how to create it and how to manage it properly.
Across the programme, participants create practical deliverables that mirror real AI product work:
Opportunity & Feasibility of AI — finding important uses for AI and testing their feasibility
Specification of AI Product — describing the behavior of the product, the user experience, requirements for trust and risks specific to AI
Working AI Prototype — progressing from abstract ideas to concrete working examples of AI applications
Design of RAG Systems & Agentic Systems — knowledge about architecture and design of AI systems
Evaluation of AI Outputs — assessment of quality, reliability, and performance of AI outputs
Business Case & Marketing Strategy for AI — connecting AI solutions with pricing and business results
At the end of the programme, participants will know not only what an AI Product Manager, an AI Product Owner, and an AI Solutions Lead do in terms of theory—but also will create the very artifacts that AI Product Managers, etc.
Why Choose IIT Kharagpur for AI Product Leadership?
Choosing an AI product programme is not only about learning the latest tools; it is about building the judgement needed to make effective AI decisions. IIT Kharagpur brings a combination of academic depth, engineering expertise, and industry relevance.
Engineer excellence legacy: Founded in 1951, IIT Kharagpur is the oldest IIT and one of the best institutions of engineering in India.
Experience in computing and AI research: The institution has had vast experience in computing, artificial intelligence, machine learning, and systems.
Teaching by faculty: The program has been structured and taught by faculty members at IIT Kharagpur, bringing in academic excellence into AI product development.
Concepts-oriented: Rather than just looking at changes in AI tools, the program covers fundamental topics of AI like system design, system evaluation, governance, etc.
Industry perspective: The program not only includes fundamentals but also product strategy to help professionals in understanding how to apply the technology.
Institutional credibility: By completing a program in IIT Kharagpur, one earns credentials from a well-respected engineering institution of India.
Conclusion
AI is reinventing the concept of product management, ownership, and leadership, and the roles of AI Product Manager, AI Product Owner, and AI Solutions Lead are now at the heart of this paradigm shift. The IIT Kharagpur Executive Post Graduate Certificate Program in Building AI Products, Systems & Services is carefully crafted to help product managers become competent for all three in six months through frameworks, prototyping, and a faculty-defended capstone project. This programme presents a direct route for those from the product and technology backgrounds who want to be product leaders in the world of AI products.