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SINGAPORE – Media OutReach Newswire – 24 February 2026 – In the wake of Budget 2026 and Prime Minister Lawrence Wong’s announcement of a National AI Council to accelerate mission-driven artificial intelligence deployment, EtonHouse International Education Group has collaborated with OpenAI to roll out ChatGPT Edu across its global education network, establishing a secure, enterprise-grade AI workspace designed to strengthen governance, operational excellence and institutional capability.

The implementation spans the Group’s schools and education brands, including EBridge Pre-School, an Anchor Operator, extending AI integration beyond classroom experimentation into enterprise-wide infrastructure supporting operations, marketing and admissions, finance, human resources, school administration and technology development.

While education was not named among the initial priority sectors identified under Singapore’s national AI strategy, EtonHouse views schools as foundational to building long-term AI capability and literacy across society.

Governance-led AI deployment

The rollout has been structured around enterprise governance principles. Access is managed through role-based access controls, single sign-on authentication and automated provisioning, ensuring that AI tools and information remain aligned to defined job responsibilities and permission boundaries.

ChatGPT Edu operates within a centrally managed internal workspace governed by consistent policies across the Group. External sharing and third-party integrations are enabled only where explicitly approved and aligned with business requirements, reinforcing a secure and compliant AI environment.

This governance-first approach reflects a deliberate shift from isolated experimentation to structured, scalable adoption.

From classroom innovation to enterprise infrastructure

EtonHouse previously developed Lumina, its proprietary AI-powered lesson planning platform. The deployment of ChatGPT Edu represents the next phase of integration, extending advanced artificial intelligence capabilities into enterprise functions.

Within the secure workspace, teams can upload documents for structured analysis, generate comparative reports, conduct scenario modelling and retrieve institutional knowledge more efficiently. Technology teams are also leveraging Codex, OpenAI’s agentic coding tool, to enhance development workflows, supporting code drafting, review and testing while maintaining human oversight and established engineering standards.

The Group is concurrently developing internal AI assistants and structured workflows within defined governance parameters to streamline routine processes and standardise how knowledge is accessed and applied across departments.

Augmentation, not replacement

EtonHouse emphasises that artificial intelligence is being implemented as an augmentation layer rather than a substitute for professional judgement.

“Artificial intelligence is not a shortcut or a replacement technology. It is a learning infrastructure,” said Mr Ng Yi-Xian, Group CEO of EtonHouse International Education Group. “We are developing tools that help students learn more confidently, support teachers to plan and differentiate more effectively, and equip HQ teams to serve schools faster and with higher quality. AI should amplify good practice, not replace it, so we are building the governance and capability to deploy it responsibly at scale.”

The rollout will be supported by structured staff training alongside OpenAI experts clear usage guidelines and ongoing oversight to ensure transparency, responsible usage and alignment with internal policies and regulatory obligations.

“As Singapore advances its national AI ambitions, many institutions are working to bridge the gap between rapidly advancing AI technologies and their ability to deploy them effectively and responsibly. EtonHouse’s rollout of ChatGPT Edu shows how forward-thinking education organisations can translate AI into practical, trusted enterprise-wide systems that empower teams today, while building confidence for the long-term.” added Oliver Jay, Managing Director, International at OpenAI.

Education’s role in Singapore’s AI future

Budget 2026 outlined the formation of a National AI Council to guide coordinated deployment across priority sectors including advanced manufacturing, connectivity, finance and healthcare.

EtonHouse’s implementation reflects how education institutions can apply similar principles of governance, security and enterprise readiness, positioning schools not only as adopters of technology but as contributors to Singapore’s broader AI capability building.

With this move, EtonHouse signals a transition from exploratory AI usage to secure, scalable integration across its global network, reinforcing its commitment to innovation anchored in institutional discipline and responsible deployment.

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About EtonHouse International Education Group

In 2015, the EtonHouse Community Fund (ECF) was established, dedicated to enhancing the lives of underserved children and youth through education.

The Eton Academy was launched in 2020, providing English, Maths, and Science academic programmes for Nursery 1 to Primary 6 in centres across the island. Building on this success, The Eton Academy expanded in 2025 with the introduction of Elevate After School Care, offering primary school children a holistic, well-rounded after-school experience that complements their academic development.

EtonHouse International Education Group remains unwavering in its commitment to shaping futures and making a meaningful impact on the world through education.

Tata Group, Tata Consultancy Services and OpenAI unveiled a landmark strategic partnership that aims to redefine the landscape of artificial intelligence deployment across enterprise, infrastructure and workforce development. With a multi-year agreement signed at a major AI summit in New Delhi, the collaboration is centred on building out AI infrastructure in India, rolling out Enterprise ChatGPT to thousands of employees and co-creating industry-tailored AI solutions.

Under the pact, TCS’ HyperVault unit will lead the development of large-scale AI-ready data centres, starting with an initial capacity of about 100 megawatts of power and a roadmap to scale to 1 gigawatt. OpenAI is anticipated to become the first anchor customer for this infrastructure, supporting advanced AI computation and inference workloads within the country.

Central to the partnership is the deployment of Enterprise ChatGPT across Tata Group companies, designed to enhance productivity and accelerate innovation within one of India’s largest conglomerates. Thousands of employees are set to receive access to the enterprise version of the generative AI platform, enabling broader internal adoption of AI tools for knowledge work and decision support.

Beyond productivity tools, the alliance will explore the development of “agentic” AI solutions that combine OpenAI’s cutting-edge models with TCS’ industry knowledge and engineering capabilities. This approach aims to address complex sector-specific challenges across fields such as manufacturing, financial services and healthcare, rather than offering generic AI applications.

OpenAI’s CEO Sam Altman positioned the collaboration as part of a larger initiative to expand the company’s footprint and capabilities in emerging markets like India, where demand for AI services and local data processing is accelerating. He emphasised the need for robust infrastructure and local partnerships to scale AI responsibly and securely.

Tata Sons Chairman N. Chandrasekaran described the partnership as a cornerstone in the group’s wider AI strategy, underscoring its potential to strengthen both domestic capacity and global competitiveness. The agreement aligns with TCS’ ambition to become a leading AI-driven technology services provider on the world stage, building on its existing HyperVault platform and ongoing investments in state-of-the-art data centres.

Financial markets reacted positively to the announcement, with TCS shares rising after the news broke, reflecting investor confidence in the company’s expanded role in AI infrastructure build-out and its position as a strategic partner to global AI developers.

The infrastructure element of the partnership places a strong emphasis on scalability and sustainability. TCS’ HyperVault facilities are designed to support liquid-cooled, high-density data environments that can handle the demanding computational needs of generative AI models, while also integrating with major cloud regions for broader interoperability.

A social impact component is woven into the alliance through plans to collaborate with the OpenAI Foundation to deliver AI training programmes for youth and underserved communities, equipping individuals with skills to engage with emerging technologies responsibly. The initiative aims to develop a pipeline of talent capable of contributing to the wider AI ecosystem.

This partnership comes amid a broader surge in investment and strategic alignments between global AI firms and Indian technology leaders, as the country seeks to position itself as a competitive hub for innovation and data infrastructure. Industry observers note that similar efforts by other major tech players to localise AI capabilities reflect a global trend towards data residency, regulatory compliance and sovereign control over critical AI workloads.

Critics caution that the rapid expansion of AI infrastructure must be balanced with robust governance frameworks to address concerns around data security, ethical use and labour market disruption. Analysts argue that while the partnership promises substantial gains in efficiency and capability, clear policies and oversight mechanisms will be crucial to ensure equitable benefits across society.

Producer prices in the Republic of Korea rose for a fifth straight month in January, driven by firmer semiconductor prices and higher agricultural costs, according to central bank data that point to lingering pipeline inflation pressures in Asia’s fourth-largest economy.

Figures released by the Bank of Korea showed the producer price index increased on both a monthly and annual basis, extending a run of gains that began in early autumn. Officials attributed the latest rise largely to a rebound in memory chip prices and elevated food-related costs, reflecting supply constraints and weather-related disruptions.

Semiconductors, a cornerstone of the country’s export-led economy, played a decisive role. Prices for key memory products, including DRAM and NAND flash, strengthened as global demand for data centres and artificial intelligence applications continued to absorb inventories. After a prolonged downturn that weighed on manufacturing output through 2023, chipmakers have benefited from tighter supply and renewed investment in high-performance computing, pushing upstream prices higher.

Industry analysts say the upturn in chip prices has filtered through supply chains, lifting overall producer prices even as energy costs have remained comparatively stable. Manufacturing accounts for a substantial share of Korea’s producer basket, meaning swings in technology components can exert an outsized influence on headline figures.

Agricultural products also recorded notable gains. Unfavourable weather conditions and higher input costs contributed to increases in fruit, vegetable and livestock prices. Food-related producer costs are closely watched because they can pass through to consumer prices with a lag, particularly in a country where household spending on fresh produce forms a visible part of the inflation basket.

The latest data suggest cost pressures remain uneven across sectors. While energy prices have moderated from peaks seen after geopolitical disruptions in global oil and gas markets, certain industrial materials and processed foods have shown persistent firmness. Service-sector producer prices, including transport and logistics, have also edged higher, reflecting wage adjustments and operating expenses.

Economists note that sustained increases in producer prices can eventually feed into consumer inflation, although the transmission is neither automatic nor immediate. Consumer price growth has eased from multi-year highs reached in 2022, but remains sensitive to food and housing costs. The central bank has kept its benchmark interest rate at a restrictive level since early 2023 in a bid to anchor inflation expectations and support financial stability.

Policy deliberations in Seoul have balanced the need to contain price pressures against concerns over slowing domestic demand and household debt. Export performance has improved alongside the semiconductor recovery, yet construction activity and private consumption have shown mixed signals. A continued rise in producer prices may complicate the timing of any monetary easing, particularly if global commodity prices remain volatile.

The global context adds another layer of uncertainty. Demand for advanced chips linked to artificial intelligence has bolstered Korea’s trade outlook, but cyclical risks persist in other manufacturing segments, including petrochemicals and steel. At the same time, agricultural markets remain exposed to climate variability, which can amplify price swings and affect food security.

Market participants are closely monitoring whether the current producer price trend represents a stabilisation after last year’s weakness or the beginning of a more entrenched cost cycle. Some analysts argue that the semiconductor rebound is structural, underpinned by sustained capital expenditure in cloud infrastructure and next-generation devices. Others caution that technology demand can be volatile, and that inventory adjustments may re-emerge later in the year.

For policymakers, the composition of producer price growth is as important as the headline number. Increases concentrated in export-oriented sectors may bolster corporate earnings and investment, whereas broad-based gains across consumer-linked industries could signal renewed inflationary momentum. The central bank has indicated it will continue to assess data on prices, wages and growth before making any shift in its policy stance.

Businesses, meanwhile, face decisions on whether to absorb higher input costs or pass them on to customers. Large technology firms may have greater pricing power in global markets, but small and medium-sized enterprises, particularly in food processing and retail supply chains, operate on thinner margins.

By Nantoo Banerjee The global AI impact summit 2026 in Delhi, last week, couldn’t have come at a more appropriate time when the world continues to be somewhat skeptical about adoption of Artificial Intelligence (AI), its limitations and potential consequences. Thanks to the pioneering effort by firms such as Nvidia, Microsoft, Google, Amazon, Meta and […]

The article India Should Adopt ‘Trustworthy’ AI Tools To Stay Safe And Transparent appeared first on Latest India news, analysis and reports on Newspack by India Press Agency).

Global technology groups including Microsoft, Amazon and Google have pledged billions of dollars to expand cloud and AI infrastructure across the country, betting on strong digital adoption, a vast developer base and policy support from New Delhi. At the same time, domestic conglomerates such as Reliance Industries and the Adani Group have unveiled plans to scale up capacity, signalling an arms race to capture the next phase of AI growth.

The surge is centred on established data centre hubs such as Mumbai, Hyderabad, Chennai and the National Capital Region. Industry estimates place India’s operational data centre capacity at more than 900 megawatts, with projections that this could double within a few years as hyperscale facilities come online. Much of the new supply is being designed for AI workloads, which require more powerful processors and higher rack densities than traditional cloud computing.

Microsoft has committed to expanding its Azure footprint in multiple regions, while Amazon Web Services continues to invest in its Mumbai and Hyderabad zones. Google Cloud has also deepened its presence, citing demand from financial services, healthcare and government clients. Nvidia, whose graphics processing units underpin many AI systems, has strengthened partnerships with Indian firms to support sovereign AI initiatives and localised computing.

Officials argue that this wave of investment will support economic growth, digital inclusion and advanced research. India’s data protection framework and semiconductor incentives have been positioned as part of a broader strategy to create a resilient digital ecosystem. The government has also outlined ambitions to develop domestic AI models trained on local languages and datasets, increasing the need for high-performance computing infrastructure within national borders.

Yet environmental experts warn that the geography of expansion raises difficult trade-offs. Mumbai and Chennai, two of the country’s largest data centre clusters, face periodic water shortages and are vulnerable to climate-related risks, including extreme heat and flooding. Hyderabad, another key hub, has experienced mounting pressure on groundwater resources amid rapid urbanisation.

AI data centres are particularly resource-intensive. Training large language models can consume vast amounts of electricity, and the cooling systems required to maintain optimal temperatures often rely on significant volumes of water. While operators increasingly use advanced cooling technologies and pursue renewable energy procurement, critics question whether efficiency gains can keep pace with the scale of expansion.

According to industry analysts, AI-optimised facilities can draw substantially more power per rack than conventional data centres. India’s peak power demand has been rising steadily, touching record highs during heatwaves. Coal continues to account for a large share of electricity generation, although solar and wind capacity have expanded rapidly. The tension between decarbonisation goals and surging digital energy needs is becoming more pronounced.

Water usage is another flashpoint. Traditional evaporative cooling systems can require millions of litres annually for large facilities, though some operators are shifting to air-cooled or liquid immersion systems to reduce dependence on freshwater. Companies state that they are investing in water recycling, rainwater harvesting and wastewater treatment, particularly in regions classified as water-stressed.

Environmental groups argue that even with mitigation measures, cumulative impacts could strain local communities. Urban residents in Chennai and parts of Maharashtra have already experienced water rationing during drought periods. The prospect of energy-hungry AI campuses expanding in these same areas has prompted calls for stricter environmental assessments and greater transparency around resource use.

Corporate leaders counter that hyperscale operators often have stronger sustainability commitments than smaller, on-premise data centres. Many global firms have pledged to run on 100 per cent renewable energy and to become water positive within the decade. In India, power purchase agreements for solar and wind farms are increasingly tied to data centre projects, supporting the build-out of clean energy capacity.

Policy makers face a delicate balancing act. Digital infrastructure is viewed as critical to competitiveness, especially as countries race to develop generative AI capabilities. India’s large pool of engineers and its expanding start-up ecosystem make it an attractive base for AI research and deployment. Delaying capacity expansion could risk ceding ground to regional rivals in Southeast Asia or the Middle East, where governments are also courting hyperscale investment.

At the same time, climate resilience is rising on the national agenda. The country has set ambitious renewable energy targets and emphasised sustainable development in international forums. Integrating AI growth with environmental safeguards will test regulatory frameworks at both central and state levels.

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About Lumen

Lumen is unleashing the world’s digital potential. We ignite business growth by connecting people, data, and applications – quickly, securely, and effortlessly. As the trusted network for AI, Lumen uses the scale of our network to help companies realise AI’s full potential. From metro connectivity to long-haul data transport to our edge cloud, security, managed service, and digital platform capabilities, we meet our customers’ needs today and as they build for tomorrow.