Everyone in India is Learning AI, But Who Will Build the Arc…
Analytics India Magazine (Ankush Das)
India’s appetite for AI is undeniable. Affordable courses, enterprise adoption and professionals eager to boost productivity have made AI literacy a mainstream trend. Yet, beneath the enthusiasm lies a question; one we may already have the answer to.
Is India building a generation of professional AI creators or merely producing AI-literate users?
Rohit Sharma, president of consumer business at upGrad, drew the distinction in a conversation with AIM. “As far as India is concerned, there is strong progress on AI adoption, for sure.”
However, he acknowledged that if India had to categorise itself, it would likely fall more into the AI user category than that of the creator or architect.
3 Layers of Strategic Thinking-Aided Learning
Sharma breaks down AI skilling into three levels. At the foundation is AI literacy, where individuals learn how to use AI to perform their jobs more efficiently.
This is currently where most Indian professionals stand. He described it as the “base level”, where the question is “how can I use it today to become better at my job tomorrow?”
To address this need, upGrad launched a course with Microsoft three months ago.
The course, Sharma claimed, attracted one lakh paid sign-ups—an uptake that took even the company by surprise. The response confirmed the hunger for foundational knowledge.
The second layer involves job-linked reskilling, tailoring AI for specific domains like finance, healthcare or manufacturing. “I think we are somewhere in the phase of between one and two right now,” he added.
The third and most challenging layer is advanced specialisation, where engineers, data scientists and others focus on creating and fine-tuning models. He stressed that India may need to invest more heavily at this stage.
Sharma also highlighted the need for both prompt engineers and strategic AI thinkers.
While prompt engineering is now the baseline skill for white-collar professionals to boost productivity, a smaller specialised cohort must advance as AI architects—building, fine-tuning and ethically governing models suited to Indian contexts and future challenges.
The Race to Stay Relevant With AI
The pace of technological change has turned upskilling into a moving target. Five years ago, upGrad revised 20% of its data science curriculum annually.
Today, a third of the material is revised within months. Sharma noted that courses even eight or nine months old risk becoming somewhat redundant as frameworks and tools may evolve too quickly to stay relevant.
This constant reinvention reflects the challenge of keeping professionals relevant in an industry where tools like generative AI and MLOps can change meaning within a year.
For working professionals, the demand for frequent reskilling and upskilling has intensified. He emphasised that beyond hard skills like data science and machine learning, the ability to acquire new knowledge is crucial. The rapid evolution of generative AI principles in the last six months exemplifies the importance of continuous learning for everyone.
To adapt, upGrad taps a dynamic ecosystem of experts, both within India and outside. They work with them individually, consult with them, and try to understand what they are seeing, implementing, and what is working or not.
The company then converts use cases and case studies into learning materials for their students, a process that was once conducted once every six months but has now become a monthly exercise.
Rohit Sharma highlighted upGrad’s focus on integrating AI directly into learning. The company is piloting a one-on-one AI tutor that acts as a personalised study buddy, to be rolled out across programmes soon. Alongside, AI-powered grading will deliver precise feedback on student work, especially coding, making large-scale learning more effective and adaptive.
Sharma told AIM that the ‘mAI-ask’ bot has been a noteworthy step towards learner support.
“After months of testing and iteration, it went live in January and is now active across several programs, offering contextual, real-time assistance that bridges the gap between our learners and academic support,” he said.
He shared that in May, upGrad’s ‘mAI-ask’ handled several hundred daily queries—60% academic and 40% non-academic—independently resolving 90% of them and only escalating the rest to mentors. The model blends AI efficiency with human guidance for scale, quality and learner confidence.
upGrad sees two clear upskilling trends. Early to mid-career professionals are driving the demand for certifications, with over 1.6 lakh enrolments in the current financial year and one lakh in the ‘U&AI’ certification by Microsoft and the National Skill Development Corporation alone. Meanwhile, senior professionals are fuelling the demand for online Doctor of Business Administration programmes in generative AI.
Corporate skilling, too, has surged 100% in six to eight months, driven by CXOs and employees alike.
Asked whether upGrad plans to add any financial aid to accelerate the course consumption like competitors such as Coursera, Sharma told AIM, “That’s not in our immediate plans”.
Looking ahead, he remarked, “I think the next six months will be interesting.”
Building Beyond the Baseline
Sharma was clear that both baseline skills and higher-order expertise are essential for preparing professionals.
While upGrad bets on Microsoft tie-ups and AI-driven learning, rivals like Coursera, Simplilearn and Great Learning chase the same space through affordability, global partnerships or certifications.
For India, the risk may not be in the lack of enthusiasm but in staying stuck at the first two levels of literacy and reskilling, without producing enough architects who can shape AI itself. Upskilling may be the bridge; turning a generation of AI users into strategic thinkers and creators is what the country may eventually need.
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