Рубрика: AI

The Karnataka government is weighing steps to rein in the rapid expansion of computer science (CS) and allied engineering seats across the state, amid growing concerns that an unchecked supply of graduates in the stream could worsen unemployment among young engineers.

Speaking in the legislative council on December 16, Karnataka higher education minister M C Sudhakar acknowledged that engineering education in the state has become heavily skewed towards CS-related disciplines.

Karnataka currently has 229 engineering colleges, including 27 government engineering colleges. Together, they offer around 1.53 lakh engineering seats, the government said in response to a question raised by BJP MLC Dhananjaya Sarji.

A closer look at the distribution shows sharp imbalances, Sarji stressed.

While 27 private universities alone account for nearly 33,000 engineering seats, government engineering colleges together offer only 6,495 seats.

Even within these government institutions, only about 10% of seats are in CS-related branches, he flagged.

In contrast, Sarji highlighted that some private universities have concentrated a disproportionate number of seats in a single discipline.

In one such university, out of 4,320 engineering seats, as many as 4,020 are in computer science and related branches, he said, seeking a response from the government.

Sudhakar said the government agrees that such concentration is becoming a problem. He pointed out that while medical colleges operate under strict caps, with limits such as 250 seats per institution, engineering colleges currently do not have similar restrictions.

Referring to AICTE norms, Sudhakar said institutions have justified the expansion by citing student demand. The minister noted that concerns over excessive engineering seats are not new, recalling that the Telangana government had flagged such a trend.

Karnataka, he said, is now in the process of rationalising seat allocations, especially where a single discipline dominates intake numbers.

According to Sudhakar, out of the total 1.53 lakh engineering seats in the state, nearly one lakh are now in computer science and related fields. This, he warned, could lead to an unemployment crisis as “everyone is doing computer science”.

Using a stark analogy, the minister said the current system risks becoming one where “big fish eat small fish”, signalling that aggressive expansion by a few institutions could crowd out balance and long-term sustainability in engineering education.

Reacting to the announcement, Krishna Kumar Gowda, general secretary of Greater Bengaluru IT Companies & Industries Association (GBITCIA), acknowledged the government’s concern, saying a seat mix heavily skewed towards computer science is unsustainable for students and the broader economy.

He noted that Bengaluru and Karnataka remain leading global tech and GCC hubs, with strong future demand for computer science, AI, and data talent. Any cap, he said, must be data-driven, calibrated, and regularly reviewed to avoid future talent shortages or pushing students to other states.

“The issue is not that Karnataka has ‘too many’ computer engineers, but that CS seat growth has outpaced demand in some branches and placement capacity. Rationalisation that restores balance while protecting tech leadership is welcome,” Gowda said.

He stressed that simply reducing seats will not solve unemployment. Industry, he said, needs strong fundamentals, updated curricula, internships, and closer campus–industry collaboration to make graduates job-ready. Gowda also suggested structured consultation between the government, VTU, AICTE, and industry bodies, and a differential approach, capping low-quality programmes while allowing monitored growth in high-demand areas such as AI, robotics, and machine learning, including in tier-2 and tier-3 locations.

A few months ago, CPS Prakash, former principal of Dayananda Sagar College of Engineering, had issued a similar warning in a LinkedIn post, stating that many engineering colleges in Karnataka were adding computer science and allied branches without adequate planning. Most programmes lack trained faculty, feature outdated syllabi, and often duplicate the core CS curriculum, producing thousands of graduates with similar, misaligned skills, he had observed.

“The rapid adoption of AI is further reducing demand for human workers in tech, creating a looming mismatch between supply and demand,” Prakash wrote, adding that colleges may struggle to justify the proliferation of computer-related branches, risking high unemployment and a generation of graduates with obsolete skills, a crisis that administrators and regulators have failed to anticipate.

Neeti Sharma, CEO of TeamLease Digital, said the proposal to reduce computer science seats in Karnataka needs careful consideration. Technology, she said, is no longer limited to the IT sector, and computer science graduates are not hired only by IT companies.

While IT firms increasingly recruit from multiple engineering streams, Sharma noted that sectors such as manufacturing, BFSI, healthcare, retail, and logistics are undergoing digital transformation and actively hiring tech talent. The recent slowdown in IT hiring, she said, reflects greater selectivity rather than shrinking demand for technology skills.

“The real concern that needs to be addressed is employability, not the number of students,” Sharma said, adding that instead of cutting seats, the focus should be on improving curriculum quality, practical exposure, and industry relevance across streams.

Karnataka became India’s tech capital by building a strong and diverse talent pipeline, she said, cautioning that reducing computer science seats could weaken that advantage over time.

“The answer lies in better skills and outcomes, not fewer technology graduates.”

The head of the computer science department at a private university, on condition of anonymity, said the government’s proposal should not be seen merely as an overflow of computer science seats, but in the context of evolving global demand for technology skills.

“AI is now central across sectors, not just IT,” the HoD said, adding that opportunities exist in areas such as healthcare, construction, manufacturing and infrastructure through automation and robotics. Rather than cutting seats, they said policymakers should focus on blending AI and machine learning with core engineering disciplines to create broader employment avenues.

They also flagged the concentration of seats in a few private institutions, calling for stronger regulatory oversight.

“Approvals for intake increases and new programmes already require clearance from the Karnataka State Higher Education Council. The issue lies in enforcement,” he said.

Warning against arbitrary caps, the HoD said students determined to study AI and robotics would simply move to other states if opportunities shrink in Karnataka.

“That would hurt admissions and weaken the state’s talent pipeline. The focus should be on curriculum reform and quality, not seat reduction,” he added.

Viraj Singh Randhawa, a third-year engineering student at Manipal Institute of Technology, said he is not in favour of the proposed plan, arguing that demand for computer science remains strong.

He said imposing a cap on computer science seats should not extend to private institutions and, if implemented at all, be limited to government colleges.

Randhawa added that if the government moves to cap computer science intake, it should simultaneously increase seats in allied disciplines such as AI, data science and cybersecurity.

If expanding intake in these areas is not feasible, he said the state should consider increasing the number of engineering colleges, before imposing any cap on computer science seats.

The post Will Capping CS-Related Engg Seats in Karnataka Resolve Employment Concerns? appeared first on Analytics India Magazine.

As demand for large language models and real-time AI applications accelerates, the constraint is no longer just chips or capital, but electricity. Across the country, data centre operators are prioritising access to power over geography, snapping up any parcel of land that can support energy-hungry compute. Questions of connectivity and architecture are dealt with later.

This scramble is quietly reshaping how AI systems will be built and deployed. Instead of a few massive data centres clustered in predictable hubs, AI capacity is spreading across smaller, distributed locations, from modular facilities to telecom sites and enterprise edges.

This global push to scale AI has created what Shekar Ayyar, CEO of hyperscale networking software firm Arrcus, described as “a literal land grab.” Companies are acquiring any parcel of land that comes with assured electricity, and worrying about the rest later.

Ayyar said that these consolidated points do not have enough power to support all AI requirements. This scramble, he argued, is reshaping how AI infrastructure will be built. Instead of a few massive, centralised data centres, AI capacity is spreading across modular facilities, cell towers, and enterprise edges.

That shift is pushing networking, often treated as plumbing, back to the centre of the AI conversation.

Why Networking Lags Behind Compute

Ayyar traces the current inflection point to his years at VMware, where he saw computing move from fixed, purpose-built servers to virtualised, software-defined infrastructure. “In the network industry, that opportunity is happening right now,” he said.

“Networking is still about two, three decades behind where the compute transformation happened.”

Most enterprise and telecom networks still rely on rigid hardware boxes bought for specific functions from large vendors. That model, Ayyar argued, is incompatible with the pace of AI-led change.

“You cannot put a rigid infrastructure and hope that it will serve your purpose for the next decade or two,” he said, adding, “You have to have a software-driven infrastructure.” Arrcus positions itself as a horizontal software layer that can run across different types of networking hardware, allowing operators to adapt their networks as applications change.

Ayyar suggested that Arrcus can be applied across landscapes like a paintbrush to support all the needed applications, drawing an analogy to VMware’s early pitch.

The Innovator’s Dilemma

That approach also shapes how Arrcus sees competition. Incumbent vendors, Ayyar said, are constrained by their existing business models.

“It’s one of these innovator’s dilemma problems,” he said. “These are large, publicly traded companies. They just can’t go and say, we’re moving all that into a software-driven model architecture.”

While other startups are also working on disaggregated networks, Ayyar argued that Arrcus differentiates itself through the breadth of its production deployments, from low-end switching to high-end routing, across telecom, data centre, and enterprise environments.

The company also works across semiconductor ecosystems rather than tying itself to one.

Referring to partners such as Broadcom and NVIDIA, he said, “Our strength is that we work with both companies and frankly, other companies too.”

Opportunities in India & the IPO

The land grab narrative also ties into why Arrcus is doubling down on India. Historically, India served primarily as a technology development base. Ayyar believes that has changed.

“This is a very opportunistic time for anybody that has technology that will be instrumental in the creation, deployment and consumption of AI,” he said, adding that India is now both a producer and consumer of next-generation infrastructure.

He compared the moment to the early IT boom. “It is paramount for people to determine what’s the right skill set, and what’s the right talent pool, and what the right capability set is that needs to be built in a large population like India,” he said.

Arrcus plans to double its India headcount, expand beyond a single centre in Bengaluru, and push India towards contributing “at least sort of 10% of our total overall global book”.

The company currently works with 15–20 large customers globally and is shifting from a largely direct sales model to one driven by partnerships, including one with Fujitsu. Arrcus has formed a strategic partnership with Fujitsu to build next-generation network infrastructure for AI.

Its investor list includes Lightspeed, General Catalyst, SoftBank, Aramco, NVIDIA, Hitachi, Fujitsu and Samsung. “These are not just investors,” Ayyar said. “They should actually help us with go-to-market.”

That growth trajectory is setting the stage for a public listing, which Ayyar expects to be ready by 2027, he said.

The post This Firm Wants to be the ‘Next Big Disruptor’ in Networking appeared first on Analytics India Magazine.

Taiwanese electronics manufacturer Hon Hai Precision Industry (Foxconn) hired nearly 30,000 workers at its new iPhone assembly facility near Bengaluru over the last nine months, marking one of the fastest factory ramp-ups ever seen in India, according to a report by The Economic Times.

The move underscores Apple’s strategy to diversify its manufacturing footprint beyond China, with India emerging as a key hub.

Located in Devanahalli on a 300-acre campus, the facility began test production in April/May this year with iPhone 16 models and is now assembling the latest iPhone 17 Pro Max devices, the report said. More than 80% of the output is being exported, reinforcing India’s growing role in Apple’s global manufacturing network.

The plant’s workforce is notable for its demographic profile, with around 80% women, most of them first-time workers aged between 19 and 24. Foxconn has constructed six large dormitories to house employees, several of which are already operational, with more under development. At peak capacity next year, the facility is expected to employ up to 50,000 people.

With further expansion planned, the Devanahalli campus is projected to house more women workers at a single location than any other government or private establishment in the country. Employees have migrated from neighbouring states, and the site is expected to evolve into a mini township with residential, medical, educational, and recreational infrastructure.

Workers receive free accommodation, subsidised meals, and earn an average monthly salary of about ₹18,000—among the highest for women in blue-collar manufacturing roles.

Foxconn is investing close to ₹20,000 crore in the project, which is set to become India’s largest factory by employment and production capacity once fully operational. The plant is expected to eventually host up to a dozen iPhone assembly lines, compared with around four currently, and will surpass Foxconn’s existing iPhone facility in Tamil Nadu.

The expansion has been supported by India’s production-linked incentive (PLI) scheme for large-scale electronics manufacturing, launched in 2021, as Apple steadily shifts a larger share of iPhone manufacturing to India amid geopolitical uncertainties. All iPhone 17 models are now assembled in India and exported globally.

Apple’s India operations are backed by a supply chain of nearly 45 companies across component manufacturing, sub-assembly, and logistics. New recruits at the Devanahalli plant undergo six weeks of on-the-job training before joining production, as Apple and its partners work to build skills and deepen the local manufacturing ecosystem.While India is positioning itself as an all-rounder in manufacturing with campaigns like ‘Made In India’, it’s also projecting itself as an alternative to China. Bengaluru itself, also known as the Silicon Valley of India, has been using this to its advantage.

The post Foxconn hires 30,000 workers at Bengaluru iPhone plant in record ramp-up: Report appeared first on Analytics India Magazine.

The Karnataka government has moved to deepen its role in startup financing by encouraging state public sector enterprises (PSEs) to invest in government-backed venture capital funds, such as Karnataka Information Technology Venture Capital Fund (KITVEN). The government aims to unlock more patient capital for deep tech and frontier startups.

Announcing the move, Karnataka’s minister for electronics, IT/BT and biotechnology Priyank Kharge said the decision was aimed at strengthening institutional support for innovation, while expanding the pool of long-term capital available to early-stage companies.

“Karnataka government has taken an important step to deepen institutional support for startups and deep tech innovation,” Kharge said in a statement.

However, experts see the policy as an extension, rather than a fundamental shift in the state’s approach to startup funding.

Sankarshan Basu, professor of finance at IIM Bangalore, said the initiative does not amount to the state transforming its public enterprises into venture capitalists.

“The idea of Karnataka to encourage the state public sector enterprises to invest in government-backed venture capital fund – KITVEN – is probably not a direct shift from passive state support to active financial participation,” Basu said.

Focus on Innovation Growth Story

Kharge said that state PSEs would now be encouraged to invest in funds like KITVEN, which has been backing startups across IT, biotechnology, semiconductors, AVGC and other emerging sectors for over two decades.

According to the minister, KITVEN currently has a cumulative corpus of nearly ₹190 crore, with investments across 55 startups and exits that have delivered “strong returns.”

He highlighted dedicated vehicles, such as KITVEN Fund 5 and the Beyond Bengaluru Cluster Seed Fund, which are designed to channel capital into emerging startup hubs outside Bengaluru.

“This move will unlock long-term capital for early-stage companies working in deep tech and other frontier technologies, while also allowing profitable PSUs to participate in Karnataka’s innovation growth story,” Kharge said.

Prof. Basu, instead, described it as a complementary move, noting that “given the nature and scale of the investments required, no one channel will be adequate.”

‘One More Formal Avenue’

Basu added that public-sector participation in innovation funding was not new in principle.

“It has always been a vehicle of investment with adequate appetite and expertise to invest in new and innovative activities, making this one more formal avenue for the same,” he said.

From the venture capital community, views are cautiously optimistic, with emphasis on governance and operational autonomy.

Vishnu Das, principal at deep tech-focused venture firm Celesta, said access to PSE capital could strengthen KITVEN’s ability to back high-risk, early-stage companies, provided it comes without restrictive conditions.

“Having worked with KITVEN and seen how they operate, I think having access to PSE capital is a good thing,” Das said, adding that KITVEN has shown willingness to “take first cheque risks for companies especially in deep tech.”

However, he cautioned that the terms attached to such capital would be critical.

Safeguards Would be Essential

“It’s critical that these PSEs have reasonable expectations with respect to returns, exit timelines, etc. Moreover, they should not be involved in the investment decision-making, which should be left to the IC and investment team of KITVEN,” Das said, warning that excessive governance and administrative burdens could undermine early-stage investing speed.

Das also pointed to structural constraints within public-sector entities. “In my experience, PSEs have the ability, but not the risk appetite and decision-making speed,” he said, citing accountability pressures associated with deploying taxpayer capital.

Despite these challenges, Das said PSE participation could help crowd in private capital rather than distort early-stage markets. Beyond funding, he noted, PSEs could serve as large-scale test beds and early customers for deep tech startups—an advantage he described as “more valuable than capital.”

To make the model work, Das said safeguards would be essential, including minimal additional administrative burden, no overreach in investment committee processes, and limited constraints on which technologies or companies can be funded. He pointed to the Centre’s Research, Development and Innovation (RDI) framework as a reference for intent, if not a direct template.

As Karnataka seeks to scale its startup ecosystem beyond Bengaluru, and into capital-intensive sectors like semiconductors and deep tech, the success of this initiative may hinge less on the availability of public money and more on how independently and efficiently it is deployed.
Government data shows that the Karnataka Innovation and Technology Venture Fund’s latest vehicle, KITVEN Fund-5, is a SEBI-registered Category I Alternative Investment Fund with a target corpus of ₹100 crore, focused on backing startups in disruptive technologies such as artificial intelligence, machine learning, MedTech and electric vehicles.

Investments are typically made at initial cheque sizes of ₹2–3 crore per company, and the fund also prioritises ventures from tier-2/3 cities and women entrepreneurs.

Global Shift Towards Public-Private Capital

Responding to the government’s decision, Mir Amjad Husain, chief innovation officer at The National Institute of Engineering, Mysuru, said in his Linkedin post that the decision would catalyse long‑term growth and create valuable opportunities for the ecosystem.

Industry observers say that government-linked capital playing a role in venture capital is well established globally and in India, even if Karnataka’s specific PSU-to-VC model is locally novel.

In parts of Europe, government-backed entities like the European Investment Fund, Bpifrance and KfW Capital are among the most active limited partners in venture funds, boosting tech and deep tech ventures.

China’s state-owned VC firms such as Fortune Venture Capital and Shanghai Venture Capital Company have been investing commercially for decades. Beijing recently announced a national venture capital guidance fund to catalyse private investment in frontier technologies.

In India, central mechanisms such as SIDBI’s fund of funds for startups (FFS) have deployed over ₹9,400 crore by mid-2022 into alternative investment funds. Deep tech sector leaders have publicly called for stronger institutional LP participation to scale domestic venture capital.

These trends reflect a broad shift toward blended public-private capital models in innovation financing around the world.

The post Why Karnataka Should Tread with Caution While Encouraging PSUs to Fund Startups appeared first on Analytics India Magazine.

In 2025, AI became the defining force across technology sectors, driving new investments, reshaping business models and shifting how organisations build, deploy and scale digital systems. The impact was visible across Indian IT, global startups, Big Tech and global capability centres (GCCs), which recalibrated their plans to accelerate adoption.

Indian IT

This year marked a structural pivot for Indian IT, driven less by optimism and more by measurable AI adoption across enterprises. A joint EY-CII report showed that 47% of Indian enterprises now run multiple GenAI use-cases in production.

This surge changed the $264-billion Indian IT industry, pushing companies to update their services with more automation, cloud tools and enterprise AI.

TCS led the transition with a headline-making $6.5-billion commitment to AI-ready data centres, the first large-scale infrastructure bet by any Indian IT giant.

The IT company reached $1.5 billion in annualised revenue from AI-related services. CEO K Krithivasan told analysts at the company’s Analyst Day 2025 event that this shift from digital to AI is a “huge opportunity” and a “civilizational change” in how enterprises operate.

Infosys, Wipro and HCLTech followed suit by embedding GenAI across delivery lines, from modernisation and cybersecurity to industry-specific platforms.

Infosys secured a landmark $1.6 billion contract from the UK’s National Health Service Business Services Authority, signed in October. Another highlight was HCLTech’s partnership with OpenAI to drive enterprise AI.

Quarterly results showed that AI and cloud projects helped the big IT firms grow steadily, even though they hired fewer people and focused more on bringing in specialists with domain and AI skills.

AI Startups

According to a report by Second Talent, AI startups raised more than $89 billion this year, accounting for 34% of all venture capital, while a separate report by CB Insights shows that they are on track to secure more than half of total annual VC funding for the first time in 2025.

OpenAI announced in March that it raised $40 billion in a funding round, making it the largest private tech funding round ever. The company launched GPT 5.2 and a dedicated Sora app. Meanwhile, ChatGPT turned three in November.

Big funding rounds such as Anysphere’s $2.3 billion and Mistral’s €1.7 billion made it clear that investors now prefer companies building core infrastructure and developer tools instead of flashy AI ideas.

Anthropic added to the momentum with a massive $13 billion Series F round that valued the company at $183 billion. Databricks, the data and AI leader, closed a $4 billion Series L round. This move pushed its valuation past $134 billion.

Anthropic pushed deeper into coding-led AI with the launch of Claude Opus 4.5. Even early-stage players saw remarkable traction, with the Stockholm-based startup Lovable raising $330 million in a Series B funding round at a $6.6 billion valuation.

Big Tech

Big Tech spent this year in an all-out sprint to secure leadership in AI, announcing massive investments in both infrastructure and next-generation models.

Google expects full-year 2025 capital expenditures between $91 billion and $93 billion, Meta allocated between $64 billion and $72 billion, with plans for further increases, and Microsoft spent about $80 billion on AI cloud workloads and data centres.

Amazon led with an estimated $100 billion to $125 billion investment focused on AI capabilities and cloud infrastructure. The cloud giant announced plans to pour up to $50 billion into expanding AI and supercomputing systems for US government customers on AWS.

Meanwhile, Oracle struck one of the biggest cloud-computing deals on record, securing a $300 billion contract with OpenAI that will run for five years from 2027.

At the same time, India is witnessing a boom in data centres. Industry projections suggest the demand is real. India’s data centre demand is expected to surge from 1.3 GW in FY2025 to between 4.7 GW and 5.7 GW by FY2030, attracting a significant influx of investment from both domestic and global players.

Amazon has committed to investing over $35 billion in India by 2030, while Microsoft has pledged $17.5 billion over the next four years to expand its cloud and AI infrastructure in the country.

On the model front, Google pushed aggressively with Gemini, rolling out Gemini 2.0, 2.5 and eventually Gemini 3.0, alongside new AI-native tools such as Antigravity and deeper integration across Cloud and Workspace. The company spent the year clawing back dominance with a calmer, more mature AI strategy. This year, Nano Banana Pro was the company’s most popular image generation model.

Microsoft strengthened its lead in enterprise AI by creating a unified CoreAI engineering group and embedding AI across its cloud, developer stack and productivity platforms. The company also introduced its in-house speech model, MAI-Voice-1, and began public testing of its large language model MAI-1-preview, signalling its ambition to build specialised AI systems.

NVIDIA remained the sector’s growth engine as demand for its chips surged, boosting its valuation toward the $5-trillion mark. At the same time, AMD gained ground with new AI accelerators positioned to challenge its dominance.

GCCs

GCCs had a standout year as multinational companies increasingly turned their India hubs into centres of innovation rather than routine back-office operations. India now hosts more than 1,700 GCCs, with over 100 new centres added in the past two years, according to a Zinnov report.

The firms doubled down on engineering, AI, product development and data-led decision-making. A sharp shift towards AI was visible everywhere. According to a report by EY, about 58% of GCCs reported active investment in agentic AI, while more than 80% placed generative AI on their near-term roadmap.

Alongside IT and engineering, GCCs are now applying AI across customer service, finance, cybersecurity, operations and analytics, supported by dedicated innovation teams and internal AI centres of excellence.

Major GCC hubs include Bengaluru, Hyderabad, Pune, Chennai, Mumbai and the NCR. The industry is expected to grow to $105 billion by 2030, with nearly 2,400 centres employing more than 2.8 million people, further reinforcing India’s position as a leading destination for global enterprise operations.

Talent needs have shifted as well, with companies prioritising data science, cloud engineering, AI/ML and domain expertise over traditional back-office roles.

The post AI in 2025: A Complete Breakdown of Trends in Indian IT, Startups, GCCs and Big Tech appeared first on Analytics India Magazine.

India’s edtech boom may have fizzled out, but in its wake, it left domestic talent equipped to build digital learning ecosystems. India is now becoming the global innovation backbone for education technology, catering to GCCs on the hunt for talent pools in research, curriculum development, faculty training, and the digitisation of offline programmes.

Recently, Curriculum Associates, a leading US-based edtech company, expanded its India centre in Bengaluru. Since its launch in 2024, the centre has grown from 30 to nearly 250 employees. The office at Prestige Tech Park now spans 40,000 sq ft—up from the previous 17,000 sq ft—and can accommodate 315 employees.

The idea behind the expansion is to engage Bengaluru’s skilled engineering and AI talent and contribute directly to Curriculum Associates’ global product roadmap. As AI reshapes education globally, its India teams are solving some of the most pressing challenges facing educators, including personalised learning, teacher workload, and accessibility.

Speaking with AIM, Kelly Sia, CEO of Curriculum Associates, said the company has an ambitious goal of helping every student reach grade-level learning. “We’re a mission-driven organisation, currently serving 17 million students and over a million educators across the US,” she said.

With two-thirds of fourth graders in the US currently below reading proficiency, according to the National Assessment of Educational Progress, the challenge is significant.

That’s where the India team comes in, with the country to account for 15% of Curriculum Associates’ global workforce. While the team was initially focused on business development when the company entered two years ago, the Bengaluru centre has since expanded into product, marketing, operations, and engineering.

“All our teams from Bengaluru are involved in some of our major product roadmap decisions,” mentioned Rajeev Kapoor, VP, Curriculum Associates, India.

i-Ready and the Role of India Teams

At the heart of this contribution is deep engineering and AI-led innovation. The India team is driving critical features across i-Ready, a K-8 online platform for math and reading, including “the engineering work to enable the next generation evaluation of students leveraging CA’s bespoke Voice AI tools,” Kapoor mentioned. These tools help assess student learning at scale.

“It has taken years of research and close collaboration with educators to ensure i-Ready delivers strong results while meeting the needs of students and teachers,” Kapoor added.

An example of this work is an AI-enabled literacy task currently in the alpha stage, designed to help educators assess students more efficiently and reduce the burden of one-on-one evaluation. The Bengaluru team will now advance the literacy task from alpha to beta in 2026, ahead of a planned full-scale launch.

Beyond assessment, the Bengaluru team has also built the eReader, a digital application that “provides a digital version of textbooks for students and teachers, which emulates a physical textbook,” Sia added.

The teams work on universal tools for test automation and code deployment, ensuring the platform remains scalable, reliable, and future-ready.

Another key initiative is i-Ready Studio (iStudio), an educator-focused hub designed to streamline professional learning and support teachers with AI-driven insights. The platform “complements i-Ready Connect by linking teacher growth with student success through personalised tools and certifications,” Kapoor added.

India teams are also leveraging AI to automate electronic documents, making them more accessible to teachers and school leaders. This work acts as a companion to the accessibility (a11y) initiatives for student-facing software, in line with Curriculum Associates’ commitment to inclusive education.

The impact of this work is already measurable. India-built features support Curriculum Associates’ Big Hairy Audacious Goal of reaching 25 million students, while continuing to serve the existing US base.

Beyond tools, the company also ensure sales, training, shipping, and service capabilities can scale alongside product innovation.

A key challenge is ensuring that technology built offshore deeply understands local classroom realities. Curriculum Associates addresses this through deliberate immersion and training.

“We build SMEs (subject matter experts) through many in-person and virtual trainings, and enabling travel to the US, where our team members visit schools and shadow professional training sessions,” Kapoor noted. Additionally, all employees are trained in the US education system as part of onboarding, “thus laying a strong foundation of the edtech domain in the US market.

From India to US

However, Curriculum Associates is not yet prepared to enter the Indian edtech market and wants to continue building for the US.

Kapoor explained, “Entering a new market requires substantial research and careful work to ensure the instructional approach, support, and implementation are truly aligned to local needs. We’re not closing the door to future opportunities in India, but any expansion would be a longer-term decision made with considerable care.”

While the Indian edtech landscape, currently valued at $7.5 billion, is projected to grow to $29 billion by 2030, according to IAMAI and Grant Thornton Bharat, it has had its share of ups and downs.

The sector saw a sharp surge in funding during the pandemic, followed by a significant slowdown as students returned to offline learning and edtechs struggled to sustain demand. According to Tracxn, over 2,100 edtech startups in India shut shop over the past five years, as many over-indexed on aggressive customer acquisition and built business models heavily dependent on venture capital rather than long-term institutional buyers.

The US has now become a more attractive edtech market. Many edtech leaders, including Scaler Academy, Emeritus, and Simplilearn, strengthened their international footprint, with a primary focus on the US, capitalising on the demand for upskilling in AI, tech, and test prep.

Moreover, GCCs now provide what many Indian startups lacked during the boom years—patient capital, clear product-market fit, enterprise customers, and long-term technology bets.

Curriculum Associates is just one example of learning ecosystems being built in India and taught in America. From Voice AI, driven assessments to educator-centric AI hubs, the work being done in Bengaluru is shaping classrooms thousands of miles away.

The post Outsourcing Learning: Designed in Bengaluru, Taught in America appeared first on Analytics India Magazine.

Major US technology companies, including Google, Apple, and Microsoft, have advised some employees on work visas not to travel outside the United States, citing unusually long delays in visa re-entry processing, Business Insider reported.

According to the report, immigration law firms representing Google, Apple, Microsoft, and ServiceNow warned employees who need visa stamping for US re-entry that embassy appointment delays could stretch up to 12 months. Employees were told that international travel could result in being stranded outside the US for extended periods.

A memo from BAL Immigration Law, which represents Google, said some US embassies and consulates are facing “significant visa stamping appointment delays,” and recommended that affected employees avoid travel to reduce the risk of prolonged stays abroad.

Google’s legal counsel said the disruptions are impacting several visa categories, including H-1B, H-4, F, J and M visas.

Apple’s immigration counsel, Fragomen, issued similar guidance, advising employees without a valid H-1B visa stamp to postpone travel where possible.

Microsoft asked employees stuck outside the US due to rescheduled appointments to report their status internally, while also urging those still in the country to reconsider international travel plans.

ServiceNow, meanwhile, told affected staff to coordinate with managers if they exceed the company’s standard work-from-anywhere limits because of visa delays, the report noted.

The delays are linked to expanded social-media screening requirements introduced as part of US visa processing, which apply to H-1B workers, their dependents, and certain student and exchange visitor categories, the report said.

The US Department of State confirmed to Business Insider that it is conducting enhanced “online presence reviews” for applicants, which has contributed to appointment backlogs at embassies in multiple countries, including India.

The situation highlights growing uncertainty around the H-1B visa programme, a critical channel for hiring skilled foreign workers in the US tech sector.

The post Google, Apple, Microsoft Warn H-1B Workers Against Leaving US Amid Visa Delays appeared first on Analytics India Magazine.

In March last year, the launch of the IndiaAI Mission drew a lot of attention at the global stage. Aimed to create a robust AI ecosystem in the country by building sovereign large language models (LLMs), the mission has had its share of hits and misses. Twelve companies, including Sarvam AI, BharatGen, and Fractal Analytics, were selected to develop foundational models tailored to India’s linguistic and regional diversity, with the government backing them with grants, subsidised GPU credits, and other forms of support.

As the mission and the government gear up for the India AI Impact Summit scheduled for February 2026, IndiaAI Mission CEO Abhishek Singh projected confidence in the country’s AI ecosystem.

“The mission has progressed most desirably, and the team is now gearing up for product launches and inference at scale,” he told AIM in an exclusive conversation.

Addressing the mission’s earlier plan to launch the first LLM by November this year, Singh said, “Making the compute infrastructure operational itself took six months, and only after that could we start training the models. I don’t think there is any cause for concern regarding models coming up. Both Sarvam AI and BharatGen will launch their models before the India AI Impact Summit.”

He also hinted at a voice-based LLM being developed for cybercrime, calling it the first such application to be built in India, though he did not share further details.

Expressing overall satisfaction with the mission’s progress, Singh said he would have preferred to move faster on setting up a fund of funds for startups. In the Union Budget 2025-26, the government had allocated an outlay of ₹2,000 crore out of the planned ₹10,372-crore budget over five years, with plans to double that to ₹20,000 crore.

Statutory Licensing Framework

Welcoming the Department for Promotion of Industry and Internal Trade’s proposed statutory licensing framework for AI training, Singh said such a framework would strike a balance between the need for AI models to access copyrighted data for training and the requirement of mandatory licensing.

“Ideally, revenues should be shared with those who hold copyrights and royalties, but the real challenge will be estimating who gets what. It will definitely face implementation challenges,” he warned.

He clarified that since the proposal is still in the draft stage, further refinements are likely.

On experts repeatedly mooting for the need for a data protection law, he said, “We recently published our AI governance guidelines, and I believe the current legal provisions are sufficient to handle the risks AI poses. AI is just another technology, and it’s never wise to regulate technology itself,” Singh said.

The seven core ethical principles—or “sutras”—guiding India’s AI strategy focus on trust, people-first design, innovation over restraint, fairness and equity, accountability, explainability by design, and safety and resilience. To support implementation, the government is developing tools for bias mitigation, ethical AI certification, stress testing, and machine learning audits.

“The right way to limit potential harm caused by AI is to regulate use cases and applications. For deepfakes, there are already provisions under the Bharatiya Nyaya Sanhita and the IT Act,” he added.

Facing Challenges

One of the key challenges the mission faced was GPU procurement. “Setting up the GPUs required private investment of nearly ₹20,000 crore. That kind of investment takes time to materialise,” Singh noted. High-end GPUs also require data centres with advanced cooling capabilities, which typically take 12–18 months to build.

On the talent front, Singh pointed to a growing skills crunch. “There are very few people qualified to train large AI models, and most are absorbed by Big Tech, offering exorbitant salaries. Many startups under the IndiaAI Mission struggle to find the right talent, and retaining skilled professionals remains a major challenge,” he said.

Working on Actuals

Responding to criticism that the mission has not yet shown a tangible impact due to limited GPU usage in the absence of large-scale research projects, Singh said it was too early to conclude.

“In a country like India, even if 100 million people start using these services, we will need hundreds of thousands of GPUs. Once the models are launched, the next phase will be large-scale inferencing,” he said.

As of August, the IndiaAI Mission invested in over 38,000 GPUs.

He also dismissed comparisons that portray India’s $1.2-billion AI investment as insignificant compared to the US’s $500-billion Stargate initiative or China’s $137 billion spend. “Stargate is backed by OpenAI, SoftBank, Oracle, and Abu Dhabi’s MGX. In China, it’s difficult to distinguish between public and private funding. India’s $1 billion, by contrast, is purely government funding and cannot be compared directly,” he said.

Singh acknowledged that China spends heavily on R&D—around 3% of GDP, compared to India’s 0.7%—while also pointing out the vast difference in economic scale.

India’s AI Needs

Acknowledging the AI hype, Singh said the IndiaAI Mission is not chasing that narrative. “We are focused on building use cases and models that meet India’s requirements. For that, we don’t need extremely large models. A 70-billion-parameter model trained on Indian data can deliver strong outcomes,” he said.

The government, he added, is following a use-case-led roadmap to guide how AI is deployed and for what purpose.

“Whenever a new technology emerges, questions about survival and sustainability arise. But the speed at which AI has been adopted shows it is here to stay. Companies that build products with real value will survive,” Singh said.

Making Money

Though confident that AI companies will eventually turn profitable, Singh predicted that monetisation will take time. “This is true for almost every new technology. Initially, companies focus on user acquisition by offering free or low-cost services and burning capital. Over time, products that create real value survive, and people are willing to pay for them just as Microsoft Office evolved into a paid subscription,” he said.

India’s approach to building AI—particularly voice-based applications—will be distinct from the rest of the world, shaped by the country’s scale and diversity.

“India has the opportunity to show the world, especially the Global South, how AI can move beyond hype, achieve mass adoption, and generate real revenue, much like what we achieved with digital public infrastructure,” Singh said, signing off.

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