{"id":10167,"date":"2026-10-02T18:24:48","date_gmt":"2026-10-02T18:24:48","guid":{"rendered":"https:\/\/iilm.edu\/blog\/?p=10167"},"modified":"2026-10-03T18:30:47","modified_gmt":"2026-10-03T18:30:47","slug":"blog-mandatory-ai-project-iilm-graduates-explained","status":"publish","type":"post","link":"https:\/\/iilm.edu\/blog\/blog-mandatory-ai-project-iilm-graduates-explained\/","title":{"rendered":"Why Every IILM Graduate Now Completes a Mandatory AI Project (and What That Looks Like)"},"content":{"rendered":"

Quick Answer:<\/b> Since 2026, IILM University has made an AI project compulsory for every graduating student, across management, engineering, law, and design, rather than treating AI as an optional add on. MBA students pair this with a mandatory “AI for Managers” course and a Microsoft Azure AI Fundamentals certification. BBA students work with 70+ integrated GPT tools. B.Tech students complete industry briefed AI\/ML projects with partners like IBM and Microsoft. The goal is that no one leaves IILM without demonstrable, portfolio ready AI experience they can show an employer on day one.<\/span><\/p>\n

If you are evaluating IILM, comparing it against other universities, or simply trying to understand what “AI integrated curriculum” means in practice rather than in a prospectus, this article breaks down the policy in detail: what counts as an AI project, why the requirement exists now, how it plays out differently across programmes, and what it should mean for how you choose (or hire from) a university.<\/span><\/p>\n

What “Mandatory AI Project” Actually Means at IILM<\/b><\/h2>\n

A mandatory AI project is different from an AI elective in three concrete ways. It is credit bearing, meaning it affects your degree and not just a certificate you can choose to skip. It is assessed by faculty, and often by an industry mentor as well. And it is required of every student in every school, not just those who opt into a data science or analytics track.<\/span><\/p>\n

At IILM, this now applies across management, law, engineering, and design programmes, with every graduating student expected to complete an AI project before receiving their degree. The university describes this as a structural shift rather than a pilot programme, meaning it is built into semester requirements and grading, not offered as an optional workshop on the side. IILM’s own admissions material states plainly that from day one, every student works with AI tools across management, law, engineering, and design, and that every graduating student completes a mandatory AI project, positioning this as how the university now operates rather than an experiment it is running.<\/span><\/p>\n

How This Differs From “AI Is Available If You Want It”<\/b><\/h3>\n

Most Indian universities today let students use AI tools informally, for research, writing help, or coding assistance, without building any requirement around it. IILM’s approach is different in kind rather than in degree. According to the university’s own published material on its MBA curriculum, AI is not offered as an elective or as a supplementary certification that students can opt into; it is a required, structural component of the programme. That distinction between required and optional is really the whole story here, and it is why the policy is worth unpacking programme by programme rather than taking the headline claim at face value.<\/span><\/p>\n

Who This Applies To<\/b><\/h3>\n

The mandate spans IILM’s five campuses (Gurugram, Greater Noida, Lodhi Road in Delhi, Jaipur, and Lucknow) and cuts across schools rather than being confined to a single flagship programme. That matters because a policy that only touches one popular course is easy to announce and hard to verify. A policy that applies uniformly across a BBA in Aviation Management, an MBA in Marketing, and a B.Tech in Cybersecurity is a bigger institutional commitment, and it is the version IILM says it has implemented.<\/span><\/p>\n

Why IILM Made This Mandatory, Not Optional<\/b><\/h2>\n

Three forces are pushing Indian higher education toward this kind of mandate, and IILM’s move sits squarely inside all three. None of these forces are unique to one university, but together they explain why “mandatory AI project” is becoming a real category rather than a marketing phrase.<\/span><\/p>\n

1. Policy Pressure From NEP 2020 and the IndiaAI Mission<\/b><\/h3>\n

The National Education Policy 2020 calls for integrating emerging technologies such as artificial intelligence into education from schools through higher education, in order to build computational thinking and digital literacy among students, as outlined by India’s Ministry of Education. The government has backed this policy direction with actual funding rather than leaving it as an aspiration. The 2026 to 2027 Union Budget allocated \u20b9500 crore for a new Centre of Excellence in AI for Education and an additional \u20b91,000 crore for the IndiaAI Mission, on top of the mission’s original outlay when it was approved by the Cabinet in March 2024. The<\/span> IndiaAI Mission<\/span><\/a> itself is implemented by an independent business division under the Ministry of Electronics and Information Technology, and one of its explicit pillars, IndiaAI FutureSkills, is aimed at building a talent pipeline through industry aligned curricula, which is precisely the space a mandatory university AI project sits in.<\/span><\/p>\n

2. Employer Demand Is Already Here, Not “Coming Soon”<\/b><\/h3>\n

A widely cited 2025 India Skills Report finding notes that most entry level roles now require AI linked skills, and that freshers with AI skills earn roughly 56% more than peers without them. Separately, an Economic Survey 2024 to 2025 analysis found that only about 8.25% of Indian graduates hold jobs that actually match their academic qualifications, a skills mismatch problem that project based, assessed AI requirements are explicitly designed to close, since they force every graduate through at least one applied, verifiable piece of AI work rather than leaving it to chance. This is also the logic behind IILM pairing its MBA AI project with an external, checkable credential rather than an internal grade alone, a point covered in more depth in our guide to the<\/span> best AI tools for MBA and BBA students in India<\/span><\/a>.<\/span><\/p>\n

3. Peer Institutions Are Moving Too<\/b><\/h3>\n

A 2025 FICCI EY Parthenon survey of 30 leading Indian higher education institutions found that over 60% now let students use AI tools, about 57% have formal AI policies, and roughly 40% run AI chatbots for student support. Institutions such as IIT Mandi have gone further by formalising a<\/span> UGC aligned AI Minor<\/span><\/a> recorded directly on a student’s official transcript, while AICTE has separately pushed AI electives across engineering colleges as part of its broader technology agenda. In that context, a mandatory, assessed AI project, rather than merely optional access to AI tools, is IILM positioning itself ahead of a curve that most of the sector is only beginning to move along.<\/span><\/p>\n

What the AI Project Looks Like, Programme by Programme<\/b><\/h2>\n

The specifics vary by school, but the underlying design is consistent across all of them: real tools rather than theoretical coverage, a defined and assessed deliverable, and in most cases an external mentor, certifying body, or industry partner attached to the outcome.<\/span><\/p>\n\n\n\n\n\n\n\n
Programme<\/b><\/td>\nWhat Is Mandatory<\/b><\/td>\nSupporting Infrastructure<\/b><\/td>\n<\/tr>\n
MBA \/ PGDM<\/span><\/td>\nAI project plus “AI for Managers” (2 credit core course, Semester 3)<\/span><\/td>\nMicrosoft Azure AI Fundamentals certification for every graduating MBA student; four in house GPT tools<\/span><\/td>\n<\/tr>\n
BBA<\/span><\/td>\nAI project; AI available as a full specialisation track<\/span><\/td>\n70+ GPTs integrated across learning; blockchain verified credentials; stackable AI micro credentials<\/span><\/td>\n<\/tr>\n
B.Tech CSE<\/span><\/td>\nIndustry briefed AI\/ML project, mandatory internships each academic year<\/span><\/td>\nReal project briefs from IBM, NEC, and Microsoft from Semester 1<\/span><\/td>\n<\/tr>\n
Law, Design, other schools<\/span><\/td>\nAI project embedded into capstone or practicum work<\/span><\/td>\nCross school access to GPT tools and case libraries<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

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The MBA Track, in More Detail<\/b><\/h3>\n

For MBA students specifically, the AI project sits alongside two other fixed requirements rather than standing alone. The first is the “AI for Managers” course, which IILM describes as covering practical AI tool application in business decision making, AI assisted analysis, and the strategic use of AI tools in management contexts, rather than a general awareness module. The second is the Microsoft Azure AI Fundamentals certification, standard across all core and sectoral MBA specialisations, so that every graduating MBA student holds this externally recognised credential in addition to their degree. You can verify what the certification itself actually covers on<\/span> Microsoft’s official AI 900 certification page<\/span><\/a>, which is useful context if you want to judge how substantial the credential is rather than taking the marketing description at face value.<\/span><\/p>\n

Four proprietary tools, Business Strategy GPT, Case Methods GPT, Aptitude Training GPT, and Course Helper GPT, are built directly into how students work through cases, rather than being offered as optional add ons students can ignore. Students can also layer additional AI adjacent credentials on top of the mandatory project: KPMG’s Machine Learning certification, HCL Tech’s Industry Project in Analytics, and EY’s HR Analytics certification all involve supervised, industry assisted AI analysis work. Several of IILM’s recruiting partners, including Deloitte, BlackRock, EY, L’Or\u00e9al, and KPMG, are actively screening for exactly this kind of AI tool proficiency in 2026 hiring cycles, according to IILM’s own placement facing material. For a deeper dive into how this fits the broader MBA curriculum, see our detailed breakdown of<\/span> AI and technology integration in the MBA programme<\/span><\/a>.<\/span><\/p>\n

The BBA Track, in More Detail<\/b><\/h3>\n

On the undergraduate management side, IILM offers a dedicated BBA (Hons.) in Artificial Intelligence, which blends business management with courses covering machine learning fundamentals, big data and cloud computing, natural language processing, generative AI, AI in marketing and customer analytics, and privacy, ethics, and regulation in AI. Students outside this specific specialisation are not exempt from the wider mandate either. Across the general BBA programme, roughly 80% of courses are described as blended with IILM’s in house GPT tools, and every graduating BBA student, regardless of specialisation, still completes the mandatory AI project. Students can also stack industry partnered micro credentials in areas like data science, blockchain, and fintech alongside their core degree, letting them build a more personalised AI adjacent portfolio than the mandatory project alone would provide.<\/span><\/p>\n

The B.Tech Track<\/b><\/h3>\n

For engineering students, “mandatory AI project” typically means a semester length, industry mentored build rather than a short classroom assignment. The distinguishing factor of a genuinely industry integrated programme is that these projects are credit bearing and mandatory, not optional, so every graduate has real, verifiable work to show, rather than only the small subset of highly motivated students who would have sought one out anyway. IILM’s B.Tech CSE track pairs this with named industry mentors and IBM Digital Badge credentials verified through Credly, and offers a dedicated B.Tech in Artificial Intelligence with labs and coursework spanning machine learning, computer vision, natural language processing, and robotics. If you are specifically weighing this route, our guides on<\/span> B.Tech CSE placements<\/span><\/a> and<\/span> what real industry projects should look like<\/span><\/a> go deeper into outcomes and how to evaluate this kind of claim at any college, not just IILM.<\/span><\/p>\n

Law, Design, and Other Schools<\/b><\/h3>\n

Non technical schools are the part of this policy most prospective students overlook, and also the part that most clearly distinguishes a genuine cross university mandate from a technology department initiative. Law and design students are not expected to build machine learning models from scratch. Instead, their AI projects are typically folded into existing capstone or practicum requirements, applying AI assisted research, drafting, or design tools to a real brief within their own discipline. This is a meaningfully lighter technical bar than the B.Tech track, but it is still assessed and still mandatory, which is the detail that makes the policy genuinely institution wide rather than confined to STEM programmes.<\/span><\/p>\n

Beyond the Project: The Supporting Ecosystem<\/b><\/h2>\n

A single mandatory project only works if there is real infrastructure holding it up. IILM’s version rests on a few pillars that are worth checking independently rather than accepting on trust:<\/span><\/p>\n