Learning Gap = Earning Gap: Mismatch in AI curriculum and industry needs fuels talent shortage, pay divide

AI Curriculum vs Industry Needs: Skill Gap Creates Pay Divide in India’s Tech Workforce

As artificial intelligence (AI) reshapes industries at a blistering pace, the gap between what educational institutions teach and what the job market demands is growing ever more visible—and costly. Experts warn that this misalignment is not just hampering innovation but creating a stark divide in compensation between AI-trained professionals and their traditionally skilled counterparts.

At the heart of the problem is the rapid evolution of AI technologies—so fast, in fact, that many academic institutions are struggling to keep up. “Honestly, it feels like current AI curriculums are constantly playing catch-up,” says Vishal Sharma, Co-Founder and CTO of CoHyre.ai. “Universities build strong theoretical foundations, but with new developments happening daily, traditional curriculums can’t keep pace.”

Vikas Aggarwal, Partner, Government and Public Sector at EY India, echoes this view, noting that while India has made strides in promoting AI education, “the curriculum-to-industry alignment remains inconsistent.” He adds, “Many academic programs still lean heavily on theory, but the industry needs professionals who can design, deploy, and scale AI in real-world, often resource-constrained environments.”

Learning That Meets Real-World Demand
From a technology-provider standpoint, Muneer Ahmad, Vice-President of AV Business at ViewSonic India, believes the solution lies in making AI education more application-oriented. “While schools and platforms are starting to include AI, we urgently need more experiential learning,” he says. “Students shouldn’t just learn about AI—they should be able to confidently apply it.”

Aggarwal identifies key gaps in areas such as data engineering for AI, AI product lifecycle management, and AI ethics, particularly in public sector scenarios. “Explainability and accountability are critical in such use-cases,” he notes, adding that demand is especially strong for professionals who can localize solutions to Indian contexts, such as multilingual NLP or agricultural analytics.

The Most In-Demand Skill? Adaptability
While job titles like Machine Learning Engineer, Prompt Engineer, and AI Architect are on the rise, Sharma stresses that adaptability outweighs labels. “The most in-demand professionals are those who can quickly grasp new tools and turn ideas into working prototypes,” he says. Ahmad, too, believes that fostering this agility early through hands-on education is key to bridging the talent divide.

Portfolios Over Pedigrees
Hiring practices are also evolving. “Companies want demonstrable working models and business impact,” Sharma explains. “GitHub portfolios, real-world projects, and results matter more than degrees.” Aggarwal adds that both government RFPs and private hiring are increasingly valuing live projects, hackathon wins, and internships over traditional academic pedigree.

The AI Pay Premium Is Real
According to industry estimates and online job portals, professionals with advanced AI skills now earn 40–60% more than their peers in traditional IT roles. Sharma backs this with internal examples: “We’ve seen employees using AI produce the output of entire teams. Companies are willing to pay a premium for that kind of amplified productivity.”

Who Should Close the Gap?
Experts agree that bridging the AI skill gap requires a shared effort. “It’s not just academia or industry alone—it’s everyone’s responsibility,” says Sharma. “Individuals must stay relevant through continuous learning, and institutions need to work hand-in-hand with businesses.”

Aggarwal suggests a collaborative innovation ecosystem as the way forward: “Academic institutions must embed emerging tech into core curriculums, and industry must co-create agile skilling pathways. The future lies in models where learning, upskilling, and deployment happen in tandem.”

As AI becomes more than just a buzzword—powering everything from agriculture to analytics—the divide between academic preparation and job readiness threatens to widen. The experts are clear: To thrive in the AI age, education must evolve. And those who adapt, earn. Those who don’t, risk falling behind.