Karnataka Chief Minister DK Shivakumar announced plans to establish India's first government-driven artificial intelligence (AI) University at the inauguration of Google I/O Connect India 2026 in Bengaluru. The proposed university will be developed on a 100-acre campus in Bengaluru, with regional campuses planned in Kalaburagi, Belagavi, Hubballi-Dharwad, Mangaluru and Mysuru. The accompanying AI hub will function as an incubation centre for startups, companies and academic institutions. Shivakumar also announced that Karnataka would unveil a "Karnataka AI policy" to attract investment, build a globally competitive AI ecosystem and support AI startups. The state plans to introduce AI education from Class VI onwards to equip students with foundational AI skills, while two next-generation green data centres are planned to bolster the state's digital infrastructure.
The Nasscom report warns that India risks building a technology workforce that is AI-reliant rather than AI-native if the industry and academia fail to preserve deep engineering expertise. While over 90% of the country's early-career tech professionals are already adopting artificial intelligence, the apex industry body cautioned that the decline of routine coding work must not lead to a drop in fundamental technical skills. Only 23% qualify as AI-native, while roughly two-thirds are AI-proficient, suggesting that the next challenge is accelerating the transition from AI proficiency to AI nativeness. The report emphasizes that AI demonstrably improves productivity and learning speed, but is also automating the routine tasks through which junior engineers traditionally built their foundational knowledge. Consequently, organisations and educational institutions will need to "deliberately recreate opportunities" for engineers to develop independent judgement and orchestration skills that were previously gained through hands-on experience.
According to a Nasscom report, approximately 90% of India's early-career technology talent is either artificial intelligence (AI)-native or AI-proficient, highlighting a critical component in enterprise AI adoption. The study assesses AI-native capability across 11 dimensions, including AI reliance, fluency, orchestration, creation, judgement, cognitive independence, technical grounding, learning, foundational capability, AI-augmented productivity, and responsible AI use. The inaugural edition of Nasscom's report, launched on July 13, 2026, introduces a structured industry benchmark to assess AI capabilities among early-career tech professionals with up to three years of experience, including final-year engineering students. As per Nasscom, India is uniquely positioned to emerge as a global hub for AI-native technology talent, but warns that AI skills penetration is not the same as being AI-native.
According to the Nasscom report, being AI-native is defined by the ability to collaborate productively with AI, critically evaluate and challenge AI-generated outputs, build and orchestrate AI-powered solutions, and retain independent reasoning and engineering judgement when AI falls short. The report cautions that this capability extends beyond certifications, tool usage, and familiarity with prompting techniques, focusing instead on how effectively talent collaborates with AI, solves real-world problems, builds AI-enabled solutions responsibly, exercises independent judgement while retaining strong technical foundations, and avoids excessive reliance on AI. As per Sangeeta Gupta, Senior Vice President and Chief Strategy Officer at Nasscom, "AI skills penetration is not the same as being AI-native".
To address the gap between AI adoption and AI nativeness, Nasscom urges academia and industry to move beyond traditional coding instruction. The industry body recommends that academia must move beyond coding to strengthen engineering judgement, domain learning and reimagine assessment methods, while industry must redesign to build foundational capabilities, deepen mentorship, create opportunities for independent problem-solving, embed AI verification into workflows and continuously upskill early-career talent. For the IT industry, the transition will require hiring assessments to shift from testing basic coding knowledge to evaluating comprehensive AI-native capabilities, and companies must redesign capability building to include AI-augmented foundational learning, simulation-based exercises, and multi-layered mentorship to encourage independent problem-solving among early-career talent. The report highlights significant headroom to deepen this talent base by strengthening engineering judgement and technical depth.
