akrishnarao

Tag: technology

  • India Produces CEOs — So Why Not World-Class Universities?

    India’s higher education system stands at a strange crossroads. It is one of the largest in the world, enrolling more than 40 million students across over a thousand universities and tens of thousands of colleges. Yet, despite this vast scale, no Indian university has entered the top 100 of the QS World University Rankings 2026. The contrast is stark: institutions like the Massachusetts Institute of Technology, Imperial College London, Stanford University, University of Oxford and Harvard University continue to dominate the top positions, while India’s highest-ranked institution remains outside the elite bracket. This is not merely a matter of prestige; it reflects deeper structural weaknesses in research, academic culture, governance and integrity.

    For years, India has witnessed what the Yashpal Committee described as the “mushrooming” of higher educational institutions. The rapid proliferation of private and deemed universities has created an uneven landscape where expansion often precedes quality assurance. While private investment in education is not inherently problematic, the monetisation of degrees and dilution of regulatory scrutiny have led to a system increasingly driven by numbers—student intake, campus size, publication count—rather than substance.

    The obsession with quantity over quality is particularly visible in research. Faculty appraisals, accreditation metrics and institutional branding frequently rely on publication counts. Predictably, this has encouraged the growth of predatory journals, paper mills and unethical authorship practices. India produces a large volume of research output, yet much of it goes unindexed, uncited and unnoticed globally. Academic reputation cannot be manufactured through inflated numbers. It emerges from sustained, rigorous scholarship, peer recognition and intellectual honesty.

    The events at the 2026 India AI Impact Summit exposed this malaise in dramatic fashion. Galgotias University, a private university based in Greater Noida, showcased a robotic dog named “Orion” and presented it as an in-house innovation developed by its Centre of Excellence. Observers quickly identified the machine as a commercially available Chinese-made Unitree Go2 robot. What was claimed as indigenous innovation turned out to be a rebranded product. Following public backlash, the university was asked to vacate its stall. The episode was not just an embarrassment for the institution; it was emblematic of a deeper crisis in academic integrity.

    This was not merely a case of miscommunication. It reflected a troubling culture of spectacle over substance—where exhibitionism substitutes for research, and branding replaces originality. Even more concerning was that the university holds formal recognition and accreditation. The incident therefore raised uncomfortable questions about regulatory oversight and the credibility of quality assurance mechanisms. If institutions can publicly misrepresent commercial products as research achievements, what does that imply about internal review processes, faculty evaluation systems and research verification standards?

    Such episodes damage more than a single university’s reputation. They undermine confidence in the broader academic ecosystem and cast doubt on the authenticity of innovation emerging from India’s campuses. In a global environment where credibility is paramount, even isolated incidents can have disproportionate consequences.

    The crisis extends beyond private universities. Public institutions, including Delhi University and Jawaharlal Nehru University, often struggle with faculty shortages, regulatory micromanagement and constraints on academic autonomy. Academic excellence thrives on intellectual freedom—the freedom to question, dissent, experiment and critique. Without a protected “Socratic space,” universities risk becoming instruments of conformity rather than engines of innovation.

    The government’s recent push under the National Education Policy 2020 to internationalise higher education, including inviting foreign universities to establish campuses in India, is presented as a corrective measure. The logic is that global competition will raise standards and retain students who otherwise go abroad. While the entry of foreign institutions may offer new opportunities, it cannot substitute for systemic reform. Reputation cannot be imported. Research culture cannot be franchised. Institutional excellence requires long-term investment in faculty, laboratories, research funding and governance transparency.

    India’s research expenditure remains below 1% of GDP, far lower than that of leading knowledge economies. Faculty–student ratios remain unfavourable in many institutions due to mass enrolment without proportional recruitment. Graduate unemployment signals a misalignment between curriculum and employability. International students hesitate to choose India because of inconsistent quality, bureaucratic hurdles and limited post-study opportunities. These are structural challenges that branding exercises or regulatory tweaks cannot solve.

    The fundamental issue is not international rankings; it is credibility. Global citations, academic reputation and foreign student enrolment are outcomes—not starting points. They reflect the underlying health of an academic system. When plagiarism is normalised, when publication quantity outweighs research quality, when political conformity eclipses intellectual autonomy, and when institutions chase spectacle instead of scholarship, rankings merely mirror the reality.

    Yet the paradox persists. India has outstanding institutions like the Indian Institutes of Technology, Jawaharlal Nehru University, the Indian School of Business and the Delhi School of Economics. It has produced global leaders such as Satya Nadella and Sundar Pichai. If such excellence exists, why does the overall system still struggle to match the standards of leading universities abroad?

    The answer lies not in individual brilliance but in systemic structure. India has islands of excellence, not a uniformly strong academic ocean. Elite institutions admit the top fraction of students through fiercely competitive examinations. They function well because they select exceptional talent, attract relatively stronger faculty and receive better visibility and funding. But the broader ecosystem—thousands of universities and colleges—does not operate at that level. Global standards are determined by depth across tiers, not by a handful of elite outliers.

    The global success of figures like Nadella and Pichai reflects the strength of Indian talent. But their achievements were shaped by exposure to advanced research ecosystems, institutional autonomy and well-funded innovation environments abroad. Brilliant individuals can emerge from imperfect systems. Sustainable global academic reputation, however, requires robust institutions—equipped with research funding, intellectual freedom, ethical discipline and long-term vision.

    The Galgotias episode should therefore be read as a warning, not an anomaly. It illustrates what happens when numbers overshadow knowledge and image overshadows inquiry. If India aspires to become a genuine global education hub by 2047, as policy frameworks suggest, it must first address the foundations. Quality must precede quantity. Autonomy must accompany accountability. Research must value impact over volume. And merit must prevail over spectacle.

    There is no shortcut to academic reputation. It cannot be engineered through branding or borrowed prestige. It must be built patiently, through integrity, intellectual courage and sustained investment. Only then will India’s vast educational system match the brilliance of its people.

  • From Visakhapatnam to the World: India’s High-Stakes AI Gamble

    At the AI Impact Summit in New Delhi, Prime Minister Narendra Modi unveiled what he called the M.A.N.A.V. vision for artificial intelligence — moral, accountable, national, accessible and valid. It was a speech rich in symbolism and strategic intent. India, he argued, does not fear AI; it sees opportunity. It does not seek dominance; it seeks democratization. It does not want technological colonialism; it wants sovereignty with inclusivity.

    On stage were leaders such as Emmanuel Macron and Luiz Inácio Lula da Silva, alongside technology executives including Sundar Pichai and Sam Altman. The optics were deliberate. India was positioning itself as the democratic voice in an AI world increasingly defined by American corporate power and Chinese state-driven industrial strategy.

    Pichai, in particular, added a layer of emotional symbolism. Recalling his student days, he said he often took the Coromandel Express from Chennai to IIT Kharagpur, passing through Visakhapatnam — then “a quiet and modest coastal city brimming with potential.” “I never imagined Visakhapatnam would become a global AI hub,” he said. Today, he announced, Google’s full-stack AI hub in that very city as part of its $15 billion investment in India — housing gigawatt-scale compute and a new international sub sea cable gateway would deliver jobs and cutting-edge AI capabilities across the country.

    The message was powerful: global capital validating India’s AI rise. Yet the summit also exposed the widening gap between hype and structural reality.

    India today is one of the largest AI user markets in the world. Its 1.4 billion citizens rely deeply on digital infrastructure provided by foreign platforms — primarily Google, Microsoft and Meta. It is difficult to imagine the economic and social paralysis that would follow if YouTube, Android services, cloud infrastructure or major social media platforms were suddenly withdrawn. India is among their largest markets, generating billions in advertising, subscription and data-driven revenues. Yet the core technological layers — GPUs, advanced semiconductors, frontier models — remain largely outside Indian ownership.

    This dependency has prompted calls for more aggressive policy responses. One suggestion gaining quiet traction is the idea of a stronger digital tax regime. If India does not own the GPUs, the chips or the core models, the argument goes, it must at least capture a fair share of the value generated from its data and user base. A digital tax could be framed not as protectionism, but as reinvestment capital — a mechanism to fund domestic compute clusters, semiconductor initiatives and sovereign research programs.

    The contrast with China is frequently invoked in this debate. Beijing did not allow American search engines and social networks to dominate its domestic market during the first wave of the internet revolution. It built domestic equivalents and protected them through regulatory firewalls. In the current AI wave, China has again pursued vertical integration — investing in rare earth supply chains, semiconductor fabrication, data centers and foundational AI research. Companies such as Unitree Robotics, whose Unitree Go2 robotic dog was controversially displayed at the summit expo under the label “Orion,” represent not merely startups but components of a broader industrial strategy.

    India’s model has been different — open markets, global integration, and a focus on services and SaaS. But SaaS dominance in a pre-AI era may not guarantee relevance in a post-AI world. As generative AI begins to automate coding, workflow management and enterprise solutions, many application-layer companies face margin compression. Unlike China with ByteDance’s TikTok or the United States with YouTube, India does not possess a globally dominant consumer tech brand at comparable scale. Its strength has been backend services, not platform ownership. If AI collapses the value of application wrappers built atop foreign models, India’s current comparative advantage could narrow significantly.

    Another structural vulnerability is brain drain. A disproportionate number of leading AI researchers and engineers of Indian origin work in American firms and research labs. While this diaspora influence enhances India’s soft power, it also reflects a domestic ecosystem that has not yet retained frontier talent at scale. When the core breakthroughs happen in Silicon Valley rather than Bengaluru, sovereignty becomes aspirational rather than operational.

    These tensions surfaced dramatically in the controversy surrounding the summit expo. The Opposition Leader Rahul Gandhi described the event as a “disorganised PR spectacle,” accusing the government of allowing Indian data to be showcased while Chinese hardware was presented as domestic innovation. He argued that instead of leveraging India’s talent and data power, the government had reduced AI to optics, even inviting mockery from foreign media. Whether exaggerated or not, the symbolism was politically potent: in a domain framed around sovereignty, authenticity matters.

    Yet dismissing the summit entirely as spectacle would also be simplistic. India does possess foundational assets that few nations can match: scale, digital public infrastructure, a vast multilingual dataset, and geopolitical positioning between the United States and China. Aadhaar-linked systems, UPI’s payments architecture and digital governance layers create a test-bed environment for AI deployment at population scale. Few democracies can integrate AI into welfare delivery, financial inclusion and public services as rapidly.

    The central question, then, is not whether India is leading AI today. It clearly does not control the foundational layers at the scale of the United States or China. Nor does it have the industrial depth that Beijing built over decades through coordinated state policy. The real question is whether India can convert its demographic scale and digital footprint into long-term technological autonomy.

    Modi’s MANAV framework articulates a moral and strategic ambition — sovereignty without isolation, democratization without dependency. Pichai’s Visakhapatnam announcement underscores both the promise and the paradox: global investment flowing in, yet foundational infrastructure still foreign-owned. Sovereignty in AI is measured not by summit declarations, but by ownership of compute, chips, research and platforms. If India remains reliant on American cloud infrastructure and imported GPUs, the rhetoric of independence will face credibility tests. If domestic initiatives — semiconductor manufacturing, sovereign language models, and public-private R&D collaborations — scale meaningfully, the narrative could solidify into substance.

    Hype is not inherently deceptive; it is often a political tool to mobilize investment and confidence. But hype must be matched with institutional follow-through. A digital tax regime, serious capital infusion into domestic compute, retention of AI talent, and creation of globally competitive consumer platforms would signal that the ambition is structural, not symbolic.

    India stands at an inflection point. It can continue as the world’s largest AI user market — influential, visible and profitable for foreign firms — or it can leverage this moment to deepen industrial capacity and strategic autonomy. The MANAV speech set the tone. The coming decade will determine whether it becomes a blueprint for sovereignty or a chapter in political theatre.