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Code4Mzansi highlights the growing strength of South Africa’s developer ecosystem and the role of youth-led innovation in shaping the country’s digital future

JOHANNESBURG, SOUTH AFRICA – Media OutReach Newswire – 26 May 2026 – South Africa’s emerging developers are building close to the ground, with many of the strongest solutions at the inaugural Huawei Code4Mzansi finals focused on systems people use every day: township retail, healthcare, energy, agriculture, payments and the creative economy.

The competition was held in partnership with the Department of Small Business Development. “The Code4Mzansi competition is not just a celebration of achievement, it is a launchpad for the future,” said Minister Stella Ndabeni, whose department co-hosted the event and delivered the closing address.

The finals revealed a clear shift from building abstract digital products to practical tools that help small businesses trade better, communities access services more easily, and local industries solve problems faster.

Four finalist teams focused directly on the township economy, with solutions covering food safety verification for spaza shops, offline point-of-sale systems built for load-shedding, WhatsApp-native marketplaces for informal retailers, and community credit systems for SASSA grant recipients.

Others addressed AI-driven healthcare access, electricity theft detection, smart agriculture, financial infrastructure for the creator economy, and AI-generated African music.

Held at Huawei Office Park in Woodmead, the finals brought together more than 100 attendees, including government representatives, academic partners, industry leaders and media.

“The quality of the finalist solutions demonstrated the potential of local innovation to respond to real market needs,” said Steven Chen, Cloud CEO of Huawei Technologies South Africa.

Academic partners included the University of Pretoria, the University of Johannesburg, the University of the Witwatersrand and the University of Cape Town.

“Small businesses are the backbone of our economy, and technology is their greatest accelerator. The participants here today are future entrepreneurs who will drive South Africa’s digital economy forward,” said Professor Thokozani Shongwe, Vice Dean of Postgraduate Studies, Research and Internationalisation at the University of Johannesburg’s Faculty of Engineering and the Built Environment.

Industry partner rain also attended. Leon Nortje, Principal and Senior Architect at rain, said the competition offered a strong view of the country’s emerging technology pipeline.

“It is always good to see new projects and new teams working on solutions that are valuable and industry-related. We will be looking out for potential new employees,” said Nortje.

The winners

The finalists competed for a prize pool of R800,000. MAAT by SIMVAK was named the overall grand winner and received the Business Value Award, taking home R300,000. The platform addresses food safety and regulatory compliance in South Africa’s informal retail sector through AI agents, real-time product recall alerts, and counterfeit detection for the spaza shop ecosystem.

“The spaza network is the supply chain for most South African households,” said SIMVAK founder Shingirayi Mandebvu.

HealthHive by FTCK received second prize in the Business Value Award category, taking home R200,000, for its AI telemedicine platform that matches patients with the right medical practitioners based on their symptoms.

Auraa received the Grand Innovation Award for its AI music engine built to generate authentic African sound. The platform has been associated with an album that has crossed one million streams.

The Future Star Award went to e-Khadi, a community credit and stokvel platform giving SASSA grant recipients access to essentials at their local spaza shops, supported by AI-assisted credit scoring and fraud detection.

The People’s Choice Award, voted by the public on Huawei’s social media channels, went to DevRift, a semi-finalist in the competition, who took home R100,000.

Minister Ndabeni delivered the closing address, positioning Code4Mzansi within the government’s agenda for youth entrepreneurship, small business development and digital inclusion.

“Our task is to ensure that innovation does not remain a moment of applause, but becomes a pathway to enterprise creation, digital inclusion, and sustainable growth,” she said.

“Thank you to Huawei for being a perfect partner on the journey that we are travelling, and of course, those that matter most, the developers who dared to compete,” she said.

Code4Mzansi forms part of the global Huawei Cloud Developer Competition. In its inaugural edition, South Africa attracted more participants than any other country: 1,041 across 353 teams, including 176 enterprise teams, resulting in the highest enterprise participation rate among all competing markets. Twenty semi-finalists were selected before the top nine advanced to the final.

For the finalists, the work is just beginning. As Minister Ndabeni said, “Go home today proud. But tomorrow, wake up, build again.”

Hashtag: #Huawei #Code4Mzansi #SouthAfrica

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About Huawei

Founded in 1987, Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices. With 213,000 employees operating in over 170 countries, we serve more than three billion people worldwide.

Huawei is committed to bringing digital to every person, home, and organisation for a fully connected, intelligent world. In 2025, Huawei generated CNY880.9 billion in revenue, reinvesting 21.8% (CNY192.3 billion) into R&D, with about 53.7% of its employees working in R&D. As a private company fully owned by its employees, Huawei focuses on customer-centric innovation and open collaboration to create lasting value and drive technological breakthroughs globally.

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Global enterprise AI expenditure is expected to reach about $940 billion in 2026 and climb to roughly $2.1 trillion by 2029, reflecting a shift from experimental deployments to large-scale use across manufacturing, finance, logistics, health care, energy and public services. China is emerging as one of the fastest-expanding markets within that cycle, helped by heavy infrastructure spending, state-backed industrial policy and a corporate race to build domestic alternatives to foreign chips, models and cloud platforms.

The acceleration is no longer confined to model development. China’s AI buildout is moving across the full technology stack, from data centres and accelerators to enterprise software, robotics and agentic systems capable of handling complex workflow tasks. The first phase of the investment wave was dominated by computing power, foundational models and large infrastructure projects. The next phase is being shaped by applied AI, intelligent services and automation across production lines, offices and consumer platforms.

That transition is putting pressure on global rivals. US technology groups still lead in advanced chips, frontier models and hyperscale cloud capacity, but China’s market has advantages in deployment speed, manufacturing depth and policy coordination. Companies including Alibaba, Tencent, Baidu, Huawei and ByteDance are expanding AI services while also trying to reduce dependence on restricted US semiconductor supplies. Alibaba has unveiled a new AI chip through its T-Head unit and is directing tens of billions of dollars into cloud and AI infrastructure over several years. Huawei’s Ascend processors have become central to China’s domestic accelerator strategy as export controls limit access to top-tier Nvidia products.

Infrastructure remains the foundation of the race. Worldwide AI infrastructure spending is on course to exceed $1 trillion by 2029, with accelerated servers accounting for the overwhelming share. China remains the second-largest AI infrastructure market after the US, even though export restrictions have created supply constraints for high-end accelerators. Those restrictions have encouraged domestic chip design, local server ecosystems and more efficient deployment models for inference, where many commercial AI applications run after models have been trained.

China’s data centre expansion is also moving into more specialised formats. AI workloads demand dense computing power, stable electricity supply and advanced cooling, all of which are raising costs and straining grids. Projects near Shanghai and other technology hubs are testing alternative energy and cooling systems, including offshore and renewable-powered facilities. These efforts reflect a broader attempt to manage the energy burden of AI while supporting national ambitions in cloud services, industrial software and smart manufacturing.

Robotics is becoming a central pillar of the spending wave. China already has the world’s largest industrial robot base and is pushing into embodied intelligence, where AI systems are integrated into machines that operate in factories, warehouses, homes and public spaces. Forecasts for China’s robotics market point to rapid expansion over the next five years, with demand coming from electric vehicles, electronics, logistics and elder care. The combination of AI models, sensors, batteries and manufacturing scale gives domestic firms a route to compete internationally beyond software alone.

Policy support is reinforcing corporate investment. Beijing’s “AI Plus” strategy, issued in 2025, aims to embed artificial intelligence across the economy by expanding access to data, compute and talent while promoting open-source ecosystems and industrial adoption. Local governments have added funding programmes, innovation parks and procurement support, creating competition among cities such as Beijing, Shanghai, Shenzhen and Hangzhou. That model can accelerate deployment, though it also raises the risk of duplicated capacity, uneven standards and projects driven more by subsidy incentives than commercial demand.

The competitive picture remains mixed. China leads in AI publication volume, citations, patent output and industrial robot installations, while the US continues to produce more frontier models and higher-impact patents. The performance gap between leading US and Chinese models has narrowed, aided by open-source releases and engineering efficiency from Chinese labs. DeepSeek’s breakthrough earlier in the cycle demonstrated that capable systems could be produced with fewer resources than previously assumed, intensifying debate over whether raw spending alone will determine leadership.

By Nitya Chakraborty With the U.S. President Donald Trump himself downgrading the status of the four nation Quadrilateral Security Dialogue (QUAD), why is Indian government spending so much of its precious time on QUAD meetings? It is sheer wastage of time for the Prime Minister Narendra Modi as also Foreign Minister Dr. S Jaishankar. US […]

The article Trump Has Downgraded Status Of QUAD-India Should Not Waste Time On It appeared first on Latest India news, analysis and reports on Newspack by India Press Agency).

The agreement was signed on Tuesday during the Quad foreign ministers’ meeting in New Delhi, where External Affairs Minister S Jaishankar and US Secretary of State Marco Rubio held talks covering economic security, energy resilience and Indo-Pacific cooperation. The pact gives both countries a structured route to work together across the full minerals value chain, from exploration and extraction to refining and downstream industrial use.

Critical minerals and rare earth elements have become central to the global contest over clean-energy technologies, semiconductors, electric vehicles, defence systems, communications equipment and advanced manufacturing. For New Delhi, the agreement offers access to US capital, technology partnerships and supply-chain coordination at a time when domestic demand for lithium, cobalt, nickel, graphite, copper and rare earth magnets is expected to rise sharply.

China’s dominance remains the main strategic driver behind the pact. Beijing controls a large share of global rare earth refining and magnet production, giving it leverage over industries that depend on high-performance permanent magnets, battery inputs and specialised industrial materials. Export restrictions and licensing measures imposed by China on select critical minerals have added urgency to efforts by major economies to diversify sourcing and processing.

New Delhi’s gains could come in several layers. The first is supply security. India’s electronics, defence, renewable energy and electric mobility sectors need stable access to minerals that are often mined in one region and processed in another. A bilateral framework with Washington can help identify viable projects, link producers with manufacturers and create longer-term offtake arrangements that reduce price and availability shocks.

The second benefit lies in processing. India has mineral-bearing resources, a large manufacturing base and expanding demand, but it lacks sufficient refining and separation capacity for several high-value critical minerals. Collaboration with US companies and research institutions could support technology transfer, pilot processing facilities, environmental safeguards and recycling systems. That is particularly important because rare earth value chains are not only about mining; separation, purification and magnet-making often determine strategic control.

A third advantage is financing. Critical mineral projects are capital-intensive, slow to develop and vulnerable to volatile prices. The new framework is expected to encourage coordinated investment, risk-sharing and policy support. For India, this could help attract patient capital into mineral exploration, processing parks, recycling ventures and specialised manufacturing units linked to batteries, magnets and electronics.

The agreement also fits into New Delhi’s wider industrial strategy. The government has launched auctions for critical mineral blocks, expanded exploration and moved to build partnerships with resource-rich countries. State-backed and private companies have shown growing interest in lithium, rare earths and battery materials, while domestic manufacturers are seeking greater localisation of supply chains for electric vehicles, solar power, wind equipment and semiconductors.

Washington’s interest is equally clear. The US wants trusted partners that can help build alternatives to China-centred mineral flows. India offers scale, engineering capacity, a large market and geopolitical alignment through the Quad. A stronger minerals partnership can also support US efforts to diversify clean-energy and defence supply chains beyond a narrow group of suppliers.

The pact follows earlier India-US cooperation in technology, defence, semiconductors and clean energy. It also complements Quad-level initiatives designed to strengthen supply chains and energy security across the Indo-Pacific. Australia brings mining strength, Japan brings advanced materials and manufacturing capacity, the US brings capital and technology, and India brings market scale and industrial ambition.

Challenges remain substantial. New mining and processing projects often face long approval timelines, environmental scrutiny, land acquisition issues and high upfront costs. Rare earth separation involves complex chemistry and waste management concerns. Recycling can reduce dependence on fresh extraction, but collection systems and processing capacity remain underdeveloped. India will also need a skilled workforce, stable regulation and clear pricing signals to convert diplomatic agreements into viable industrial projects.

At the interbank foreign exchange market, the currency opened weaker than Monday’s close of 95.26, losing 17 paise as importers and oil companies stepped up dollar purchases. The fall interrupted a brief recovery in the previous session, when the rupee had gained ground after suspected Reserve Bank of India intervention and softer crude prices lifted sentiment.

Market participants said the rupee’s early weakness reflected a broader risk-off mood across Asia. Oil-sensitive currencies faced selling pressure as traders reassessed the likelihood of a quick diplomatic settlement between Washington and Tehran. The rupee, already vulnerable because of the country’s heavy dependence on imported crude, moved in line with regional peers as energy prices rebounded and the dollar drew support from safe-haven demand.

Brent crude moved sharply higher towards the $100-a-barrel mark after fresh military action involving Iran raised doubts over the durability of peace efforts. Higher oil prices typically increase demand for dollars from refiners and importers, widening pressure on the trade balance and adding to inflation risks. For a country that imports nearly nine-tenths of its crude requirement, each sustained rise in oil prices feeds directly into currency, bond and equity market expectations.

The Reserve Bank of India is expected to remain active in the foreign exchange market to prevent disorderly moves rather than defend a fixed level. State-run banks were seen selling dollars in earlier sessions, a pattern traders often associate with central bank intervention. The central bank has used spot and forward market tools through periods of sharp volatility, drawing on its foreign exchange reserves while seeking to preserve market stability.

Foreign exchange reserves remain substantial by global standards, though they have eased from their February peak amid currency management and valuation changes. The buffer gives policymakers room to smooth volatility, but it does not fully insulate the rupee from external shocks when oil prices, global yields and geopolitical risks move in the same direction.

The rupee’s trajectory now hinges on three immediate variables: the price of crude, the strength of the dollar and the credibility of diplomatic efforts in the Middle East. A sustained climb in oil would complicate the inflation outlook and increase pressure on the current account. A softer dollar or clearer signs of de-escalation could help the rupee recover some lost ground, particularly if portfolio flows stabilise.

Bond markets also reflected caution. The benchmark 10-year yield edged higher as traders priced in the risk that imported inflation could narrow the central bank’s room for policy easing. Money-market rates showed a firmer bias, with swap markets reassessing the path of interest rates ahead of the next monetary policy review.

Equity markets faced a parallel adjustment, with energy-sensitive sectors, import-heavy companies and businesses exposed to foreign currency costs attracting closer scrutiny. Exporters, especially technology and pharmaceutical firms, may gain a translation benefit from a weaker rupee, but broader market sentiment remains tied to oil, capital flows and global risk appetite.

The pressure on the currency comes at a delicate moment for policymakers. Retail inflation has moderated from earlier peaks, but fuel costs and a weaker exchange rate can quickly alter expectations if the move persists. A weaker rupee raises the landed cost of crude, fertilisers, electronics and other imported goods, while also increasing the rupee value of external debt servicing for firms without adequate hedges.

Companies with dollar liabilities are likely to increase hedging activity if volatility persists. Importers generally prefer to cover near-term exposures when oil and the dollar rise together, while exporters may stagger dollar sales in expectation of better rates. This tug of war often intensifies near month-end, when corporate demand for foreign currency rises.

The Securities and Exchange Board of India is examining whether companies that list only debt securities should continue to face disclosure and compliance obligations similar to those imposed on equity-listed companies. The review is part of a wider effort to deepen the corporate bond market, where heavy reliance on private placements, limited retail participation and concentration among highly rated issuers have kept market breadth below policy ambitions.

Chairman Tuhin Kanta Pandey, who took charge of the regulator in March 2025, has signalled that the next phase of reform will focus on making the debt market more usable for issuers and investors without weakening safeguards. A pilot framework for tokenising corporate bonds is expected to be launched within six to nine months, testing whether distributed-ledger technology can improve settlement speed, servicing, traceability and operational efficiency.

The proposed easing would be especially relevant for entities that raise money only through listed non-convertible securities and do not have listed shares. Such issuers have argued that several provisions under the Listing Obligations and Disclosure Requirements framework were designed primarily for equity-market governance, where public shareholders carry voting and ownership rights. Debt investors, by contrast, are focused mainly on credit quality, repayment capacity, covenant compliance and timely interest payments.

The regulatory challenge is to separate investor-useful disclosure from procedural duplication. Quarterly financials, credit-rating updates, default alerts, asset-cover statements, related-party exposure and material event reporting remain central to creditor protection. Requirements linked more closely to equity ownership, board-shareholder dynamics and public float may be reviewed where they impose costs disproportionate to the risks faced by bondholders.

India’s corporate bond market has expanded sharply but remains structurally narrow. Net outstanding corporate bonds rose from ₹17.5 trillion in FY2014-15 to about ₹53.6 trillion in FY2024-25, with fresh issuances touching ₹9.9 trillion during 2024-25. The market accounts for roughly 15-16 per cent of GDP, far below deeper Asian and developed markets, and is still dominated by highly rated financial and public-sector issuers.

Private placements remain the preferred route for large borrowers, while public bond issues account for only a small share of overall issuance. That pattern has kept institutional investors at the centre of the market and limited participation by individuals, smaller corporates and lower-rated issuers. For policymakers, the issue is not simply market size but market diversity, liquidity and the ability of bonds to finance infrastructure, housing, manufacturing and growth-stage companies at competitive rates.

Tokenisation is being positioned as a market-infrastructure experiment rather than a replacement for existing bond-market systems. Under such a model, a bond can be represented as a digital token on a permissioned ledger, with ownership transfers, coupon payments and redemption records updated through automated processes. A well-designed pilot could reduce reconciliation gaps, improve audit trails and allow faster post-trade processing while preserving regulatory oversight.

Global fixed-income markets have been exploring tokenisation for similar reasons. Automation through smart contracts can simplify issuance, settlement and corporate actions, while better record keeping can lower operational risk. The benefits, however, depend on legal clarity, interoperability with depositories and clearing systems, cyber-security standards and clear rules on investor rights if technology vendors, wallets or ledger nodes fail.

Sebi’s review also comes amid wider changes in India’s debt-market architecture. Online bond platforms have been brought under regulation, the request-for-quote platform has gained traction, and policymakers are looking at ways to widen access to international debt products through regulated channels. Municipal bonds are also drawing greater attention as cities seek market funding for infrastructure, adding to the broader shift from bank-led financing towards market-based debt.

Investor protection will remain the central test for any relaxation. Lighter disclosure rules could encourage more issuers to list debt securities, but weaker transparency would raise borrowing costs and damage confidence if defaults rise or credit risks are obscured. The most likely outcome is a calibrated framework that retains credit-critical reporting while reducing requirements that do not materially affect bondholder decisions.

The product, built around a personal AI assistant called Mona, is being positioned as a “local-first” alternative to cloud-based generative AI tools. Rather than routing most tasks through remote servers, MonoClaw runs large language models on a user’s own Apple hardware, with the company saying the approach is designed to keep sensitive memory, session history and credentials under the user’s direct control.

Sentimento Technologies Limited, the Hong Kong engineering studio behind the product, describes MonoClaw as the city’s first managed local AI runtime environment for professional users. Its launch comes as businesses move from experimental chatbot use towards agentic AI systems that can monitor workflows, draft responses, prepare reminders and act on user-approved instructions across multiple workplace channels.

Mona is designed to work as a digital secretary across email, WhatsApp, Telegram and calendar-linked tasks. The system can identify action items in messages, prepare reply drafts, generate morning briefings, track pending approvals, surface relevant documents before meetings and flag deadlines. The company says the product ships with 160 pre-bundled professional skills, covering both business administration and personal task management.

Billy Zuo, co-founder and chief executive of Sentimento Technologies, said the shift from manual software operation to autonomous AI execution marked a wider change in workplace computing. He said many businesses adopting cloud AI still face concerns over data leakage and unpredictable subscription costs, arguing that a local-first model gives companies greater control over sensitive information and spending.

MonoClaw’s pricing reflects that positioning. The permanent software licence is priced at HK$28,888, with an early-bird offer of HK$25,888. Users must also provide compatible Apple hardware, such as a Mac mini M4 or iMac M4, with the Mac mini starting at about HK$6,099. The company handles installation, workflow configuration and validation, with payment structured through a 40 per cent deposit and 60 per cent balance after final delivery and verification.

That model differs from many AI software products that rely on monthly subscriptions, metered token use or cloud-service plans. Sentimento is pitching MonoClaw as a capital investment rather than an operating expense, a message likely to appeal to smaller firms that want clearer budgeting and lower recurring software exposure. The trade-off is a higher upfront cost and a hardware dependency that may limit adoption among users who prefer device-neutral or fully cloud-hosted systems.

Privacy and auditability are central to the product’s commercial pitch. MonoClaw uses local contextual memory, local runtime profiles, secret redaction and explicit approval gates for higher-risk actions. Mona is designed to request confirmation through messaging channels before executing sensitive commands, data changes or external actions. That “human-in-the-loop” structure reflects a broader concern in the AI sector: agents that are powerful enough to automate work also need firm boundaries, logs and user control.

Hong Kong’s technology ecosystem has been moving in the same direction. AI agents, local foundation models and governed automation have become more prominent in policy, research and enterprise discussions, with public and academic initiatives focusing on authorisation, traceability and risk controls. MonoClaw enters this environment as a commercial product for office users rather than a research platform, but its design mirrors the same debate over whether AI agents can be useful without creating new privacy and operational risks.

The launch also underscores a changing competitive field for productivity software. Major global platforms are embedding AI assistants into office suites, browsers, customer-service tools and enterprise resource systems. MonoClaw’s advantage, if it gains traction, will lie in its local deployment, Hong Kong-specific setup and promise of cost predictability. Its challenge will be proving that a local Mac-based assistant can match the reliability, integrations and performance of cloud-backed rivals while remaining simple enough for non-technical users.

Energy and infrastructure concerns add another layer to the product’s appeal. Cloud AI workloads have intensified scrutiny of data-centre electricity demand, cooling requirements and network dependence. MonoClaw argues that routine tasks such as inbox triage, drafting, reminders and meeting preparation can be handled on Apple Silicon at desk level, reducing reliance on remote inference for every interaction. The system can still use filtered cloud subprocesses for selected workloads, meaning its privacy and cost benefits will depend on how users configure and supervise each workflow.

The aircraft, operating the Muscat–Kannur sector on May 15, was preparing for a night departure from Muscat International Airport when it became misaligned during take-off. Instead of tracking along the runway centreline, the aircraft moved along the right-side edge-light area and hit multiple lights before the crew rejected the take-off. The pilot acted after hearing a loud bang and receiving a cockpit alert.

No injuries were reported among passengers or crew. The aircraft stopped on the runway and was disabled after the impact, prompting evacuation and ground response procedures. The Boeing 737-800 has remained grounded in Muscat pending technical inspection, repairs and regulatory clearance.

The occurrence has been classified as an accident by Oman’s Air Accidents Investigation Sector, which has opened a probe into the sequence of events, crew actions, runway conditions, lighting environment and air traffic control communication. The investigation is expected to examine why the aircraft was not aligned with the runway centreline before take-off clearance was acted upon.

Flight IX-712 serves an important expatriate corridor between Oman and Kerala’s Kannur district, which has a large base of workers and families linked to the Gulf. The route is part of Air India Express’s wider West Asia network, where the airline operates high-frequency services catering mainly to price-sensitive passengers, migrant workers and family traffic.

The aircraft involved was a Boeing 737-800, a narrow-body model widely used for short- and medium-haul operations. The type is part of Air India Express’s core fleet and is configured for high-density international services. The 737-800 is regarded as a mature aircraft platform, but runway alignment events remain serious because they can expose aircraft to structural damage, tyre failure, hydraulic loss and runway obstruction risks during the most critical phase of flight.

Runway edge lights are designed to mark the lateral boundary of a runway, while centreline guidance helps crews maintain the correct track during take-off and landing, especially at night or in reduced visibility. Misidentification of lighting cues can become more hazardous during night operations, when visual references are narrower and cockpit workload is high. Investigators will assess whether lighting layout, crew situational awareness, taxi routing, clearance procedures or human factors contributed to the incident.

The hydraulic leak is a key technical concern because aircraft hydraulic systems power essential functions including flight controls, braking, landing gear and steering. A flat tyre during an aborted take-off also raises operational risk, as the aircraft must stop safely while managing heat, braking load and directional control. The crew’s decision to reject take-off after the bang and warning indication prevented the aircraft from becoming airborne with possible system damage.

The incident comes at a time of intensified scrutiny of airline operational discipline, runway safety and crew resource management across global aviation. Regulators have placed growing emphasis on runway incursion prevention, proper line-up procedures, cockpit cross-checking and visual confirmation before take-off. Airports and airlines are also under pressure to strengthen safety reporting systems so that operational errors are identified and corrected before they lead to more serious outcomes.

Air India Express, now operating under the Tata group’s aviation restructuring plan, has been expanding and consolidating its network as part of a broader integration of low-cost operations. The airline has a substantial presence on Gulf routes, where competition is intense and aircraft utilisation remains high. Any grounding of a narrow-body aircraft can disrupt schedules, especially on tightly planned international rotations.

Kannur International Airport has depended heavily on Gulf connectivity since its opening, with Oman, the UAE, Saudi Arabia, Qatar and Bahrain forming core markets for the airport’s passenger flows. Services from Muscat are particularly significant for northern Kerala travellers, who often prefer direct flights over longer road journeys to airports in Kozhikode, Kochi or Mangaluru.

Founded in Singapore over 30 years ago, EtonHouse today operates over 100 schools across eight countries, and is widely recognised for its inquiry-led approach to international education.

The partnership positions EtonHouse as a long-term education partner to Bhutan, focused on listening, learning, and co-creating a school experience that honours Bhutanese culture and strengthens capability within the region. Professional development and education conferences will support collaboration among educators across Bhutan, enabling professional exchange and high-quality practice, contributing to a strong, future-ready pedagogical landscape.

A shared vision for Bhutan’s future education landscape

EtonHouse Bhutan aligns with the Royal Government’s vision to nurture world-class talent through greater access to high-quality international education. The school is designed to develop globally competent learners rooted in Bhutan’s cultural heritage and the principles of Gross National Happiness. This partnership reflects Singapore’s enduring contribution to international education, sharing a model that harmonises academic rigour with Asian values, creativity and innovation, advancing Bhutan’s long-term educational aspirations.

The school will offer a seamless K–12 pathway for over 500 students. In the Early Years, children will experience the EtonHouse Inquire. Think. Learn curriculum inspired by the Reggio Emilia approach. Primary students will engage in the International Primary Curriculum alongside Singapore Mathematics and UK-aligned core subjects, progressing to the Cambridge Lower Secondary, IGCSE and International A Level qualifications from Cambridge. Bhutanese History and Dzongkha remain integral, complemented by a multilingual language programme offering English, Dzongkha and Mandarin, alongside a strong emphasis on STEM, sustainability and holistic wellbeing.

“The Ministry of Education and Skills Development has entered into a landmark partnership with EtonHouse International Education Group to establish an international school in Bhutan, a significant milestone in the nation’s ongoing education reform, guided by His Majesty’s vision for a future-ready and globally competitive education landscape.

The initiative will provide Bhutanese students with access to internationally benchmarked learning opportunities while ensuring the deep integration of local knowledge, culture, and values into the curriculum. It seeks to create a dynamic platform for young Bhutanese to experience world-class education within the country, reducing the need to pursue such opportunities abroad and thereby strengthening Bhutan’s human capital for the future.

Beyond enhancing access to quality education, the partnership aims to strengthen national education capacity and bolster Bhutan’s attractiveness to skilled professionals and international institutions, positioning the Kingdom as an emerging hub for world-class learning,” said Mr Tshewang C. Dorji, Secretary of the Ministry of Education & Skills Development.

“Establishing Bhutan’s first international school marks a defining moment for education in the Kingdom. As a global education group, we bring internationally recognised standards and access to a worldwide learning network that connects students and educators across countries. Through the EtonHouse Global Classroom, students engage with peers across our international network, gaining global perspectives through shared learning and cultural understanding. Our ambition is to build a globally engaged school in Bhutan that expands opportunities and contributes to long-term national development.” said Mr Ng Yi-Xian, Group CEO of the EtonHouse International Education Group.

Creating Opportunities for Students and Advancing Educator Excellence

A dedicated scholarship scheme will provide full tuition sponsorship to up to ten outstanding Bhutanese students, reinforcing the school’s commitment to accessibility and national talent development.

EtonHouse will leverage its membership in the Reggio Children International Network to provide preschool educators in Bhutan with access to internationally recognised Reggio Children expertise, professional learning and regional educator exchange, strengthening teaching practice across the region.

A campus that celebrates Bhutanese identity and global perspective

“The design and curriculum of EtonHouse Bhutan pay homage to Bhutan’s cultural roots while opening doors to the world. Every space has been conceived to inspire curiosity, reflection, and innovation, echoing the nation’s aspiration to educate its youth for both local contribution and global engagement.” said Evelyn Tay, CEO of EtonHouse International Education Group, Singapore and EtonHouse Bhutan International School.

The purpose-built campus reflects a thoughtful fusion of traditional Bhutanese craftsmanship and contemporary collegiate design. Learning environments are designed in calm, neutral tones, reflecting the EtonHouse approach to inquiry-led, child-centered learning.

Students will have access to facilities including:

• Research and Innovation Centre, integrating the Library, STEAM and ICT to support inquiry, experimentation and interdisciplinary learning
• Dedicated Science Laboratories, designed for hands-on learning across Biology, Chemistry and Physics
• Cultural Learning Spaces, honouring Bhutanese History and Dzongkha as integral parts of the curriculum
• Multipurpose Sports Hall, supporting physical development, teamwork and wellbeing
• Dedicated Performing Arts Studio, enabling expression through music, drama and movement
• Reggio-inspired Ateliers, where children explore ideas through the hundred languages of expression, including light, sound, clay, mark-making and natural materials

Next steps

With enrolments opening for Nursery 1 to Year 5 (from 3 to 10 years) and plans to expand progressively to serve students aged up to 18 years, families interested in discovering more about EtonHouse Bhutan International School are warmly invited to attend our Experience Day on 30 May. This special event offers an opportunity to find out more and experience what defines the EtonHouse approach.

For more information, please visit etonhouse.edu.sg/bhutan.

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The issuer is solely responsible for the content of this announcement.

About EtonHouse International Education Group

Founded in 1995 in Singapore, EtonHouse has grown into a global education group with more than 100 schools across eight countries. The Group offers a highly recognised international education pathway from infant care to high school, including the International Baccalaureate, Cambridge, and the Reggio Emilia-inspired approach, all designed to nurture inquiry, creativity, and intercultural understanding. Beyond schools, EtonHouse is deeply committed to community impact through teacher training, philanthropy, and purpose-driven educational initiatives.

To commemorate this milestone, ACPL hosted a gala dinner on 25th of May, where it unveiled its new corporate logo, symbolising the company’s evolution and forward-looking vision. The refreshed logo reflects ACPL’s continued commitment to innovation, operational excellence, and its role in enabling the future of global digital connectivity.

ACPL’s operational strength is anchored by its fleet of purpose-built cable vessels and supporting assets. Today, the company operates three cable ships and one barge — ASEAN Restorer, ASEAN Explorer, ASEAN Protector, and its latest addition, ASEAN Challenger, which was inaugurated in 2024. With the addition of this vessel, ACPL is better positioned to deliver timely and reliable cable operations, supporting the rapidly growing demand for submarine cable infrastructure driven by the continued expansion of global data traffic, cloud services, and digital connectivity.

“Our 40th anniversary is not only a celebration of our past, but a commitment to our future,” said Mr. Yue Meng Fai, Chief Executive Officer of ASEAN Cableship Pte Ltd. “The launch of our new corporate logo reflects our evolution as a company — one that is rooted in a strong heritage while continuously advancing towards the future. We will continue to safeguard our heritage of trusted operations, empower our people as a united team with resolute commitment to quality, enhance our fleet to remain reliable and innovative, and shape our future by leading the transformation of global connectivity in a responsible and sustainable way.”

The anniversary event brought together industry partners, stakeholders and clients to commemorate ACPL’s achievements and to mark the next chapter of its journey. Throughout the year, ACPL will commemorate this milestone through various initiatives that honour its legacy while reinforcing its dedication to responsible operations and long-term value creation.

With 40 years of trusted legacy, ACPL remains committed to connecting the world — resolutely, reliably and responsibly.

Hashtag: #ACPL #ASEANCableship #submarine #marine #shipping #anniversary #logo

https://www.aseancableship.com
https://www.linkedin.com/company/asean-cableship-pte-ltd/

The issuer is solely responsible for the content of this announcement.

ASEAN Cableship Pte Ltd (ACPL)

Established in 1986, ASEAN Cableship Private Limited (ACPL) is a leading provider of submarine cable installation, repair, and maintenance services in the Asia Pacific region. Headquartered in Singapore, ACPL was formed by a consortium of six prominent telecommunications entities from the original ASEAN member countries, reflecting strong regional cooperation across Indonesia, Malaysia, the Philippines, Singapore, and Thailand. ACPL has built a strong reputation as a pioneer in submarine cable repair and maintenance, supporting critical telecommunications infrastructure under the Southeast Asia and Indian Ocean Cable Maintenance Agreement (SEAIOCMA), spanning from Djibouti to Guam and from Taiwan to Australia.

In addition to its repair and maintenance capabilities, ACPL is also an established submarine cable installer and integrator. Its services include main lay submarine cable installation and maintenance, shore-end landing and beach works, project management, offshore and diving support services, Universal Joint consumable supplies and jointing equipment, as well as engineering consultancy, site surveys, and desktop studies. ACPL remains committed to advancing submarine cable system installation and repair, delivering professional and reliable services to meet evolving customer needs and support a sustainable, connected future.

For more information, please visit: https://www.aseancableship.com.

By Nantoo Banerjee India’s economy is navigating severe stress. The impact of Persian Gulf war, high cost of imported crude oil, frequent upward adjustment of retail oil prices, rising commodity rates, soaring transportation costs, weakening Rupee and continuous exit of foreign portfolio investors (FPI) are posing a big challenge to the economy. The government appears […]

The article Rising Prices, Falling Rupee And FPI Exit Pose Big Challenge To Economy appeared first on Latest India news, analysis and reports on Newspack by India Press Agency).

Regulators have moved against Futu Securities International, Tiger Brokers and Longbridge Securities, accusing them of operating securities businesses on the mainland without approval, soliciting domestic clients and processing offshore trading orders in breach of securities, fund and futures rules. The action has disrupted a once-popular route for mainland investors seeking exposure to global technology stocks, Hong Kong initial public offerings and US-listed Chinese companies.

The China Securities Regulatory Commission and other agencies have ordered a two-year rectification programme aimed at closing unauthorised cross-border securities, futures and fund businesses. During the wind-down period, affected mainland clients will be allowed to sell existing holdings and withdraw money, but will not be permitted to make new purchases through the targeted channels.

The clampdown marks a sharp escalation from the regulatory warning issued in late 2022, when online brokers were told to stop opening new accounts for mainland investors and remove trading apps from domestic app stores. Existing clients had largely been allowed to continue trading, preserving a grey-zone channel that gave better-off retail investors access to overseas markets despite China’s capital controls.

Futu has disclosed a proposed penalty of about 1.85 billion yuan, while Tiger Brokers’ parent, UP Fintech Holding, faces penalties and confiscation of illegal income totalling more than 400 million yuan. Longbridge has said it will comply with rectification requirements and that client fund safety is not affected. Regulators have also indicated that illegal gains from related onshore and offshore entities will be confiscated, with final administrative decisions subject to formal procedures.

Market reaction was swift. Shares of Futu and UP Fintech fell sharply in US trading after the enforcement announcement, while pressure spread to parts of the Chinese ADR universe as investors assessed whether reduced mainland retail participation could weigh on offshore-listed stocks. Hong Kong market participants also began reassessing the impact on brokerage flows, custody transfers and IPO distribution.

Citic Securities has estimated that as much as HK$250 billion in assets in Hong Kong could be affected by the crackdown, with Futu accounting for a large portion. The figure underlines the scale of wealth that had moved through offshore brokerage platforms even after Beijing tightened scrutiny of capital outflows and online financial services.

Investors are now exploring alternatives, including moving positions by custodian transfer to licensed Hong Kong banking channels, using accounts with international banks, or relying on approved schemes such as Stock Connect, the Qualified Domestic Institutional Investor programme and Wealth Management Connect. Those channels, however, have limits on eligibility, investment scope, quotas and product access, making them less flexible than the digital brokerage platforms that gained popularity during the pandemic-era boom in US and Hong Kong equities.

Beijing’s concern is not only securities law compliance. The wider policy objective is to control capital outflows, strengthen oversight of retail investment activity and prevent unlicensed overseas institutions from marketing financial products inside the mainland. The campaign also aligns with efforts to support domestic capital markets, where authorities have been trying to stabilise sentiment and encourage household savings to flow into regulated local investment products.

For the brokers, the enforcement action threatens an important part of their client base. Futu and Tiger expanded rapidly by offering low-cost, mobile-first access to overseas securities, appealing to younger and wealthier mainland clients who wanted exposure beyond A-shares. Both companies have been diversifying into Hong Kong, Singapore, Japan, Australia and the United States, but mainland-linked business remains material to investor perceptions of their growth prospects.

The crackdown may also reshape Hong Kong’s role as a financial gateway. Licensed institutions could benefit from account transfers and higher compliance-driven demand, but regulators in the city are expected to scrutinise whether account-opening documents, residency claims and fund-transfer routes meet legal requirements. That could raise operational costs and slow onboarding for brokers and banks serving mainland-related clients.

• At the launch, KPMG also unveiled its Trusted AI Assurance offering that is aligned with relevant international standards and frameworks to mitigate risk and build trust in AI deployment. This gives businesses a clear, credible pathway to scale AI confidently as Singapore reinforces its position as a trusted node in the global community.

SINGAPORE – Media OutReach Newswire – 25 May 2026 – As Singapore deepens its commitment to becoming a world-leading AI hub, the question of how organisations build AI that is trusted — by customers, regulators and international partners — has become as consequential as how fast they build it. Today, KPMG took a significant step in answering that question with the launch of its Trusted Artificial Intelligence Centre of Excellence (AI CoE). Supported by the Singapore Economic Development Board (EDB), the AI CoE is a dedicated capability hub designed to help organisations move beyond AI experimentation and embed AI as a trusted, enterprise-ready asset.

At the same event, KPMG also unveiled its Trusted AI Assurance — a structured, business-focused, evidence-based approach that gives Singapore businesses a rigorous multi-faceted assessment of their AI deployment and a clear pathway to scale confidently. Today’s launch — bringing together government, enterprise and the professional services sector — signals a pivotal shift in the national AI conversation: from speed to scale of adoption where trust is the foundational bedrock of deploying AI.

The Trusted AI CoE was officially launched by Ms Jasmin Lau, Minister of State, Ministry of Digital Development and Information & Ministry of Education, alongside Mr Jermaine Loy, Managing Director of the Singapore Economic Development Board (EDB), and Ms Lee Sze Yeng, Managing Partner of KPMG in Singapore.

KPMG’s 2025 Global CEO Outlook shows that more than seven in ten CEOs now rank AI as a top investment priority — yet for many, the gap between ambition and sustained enterprise impact remains wide. Governance, data readiness and workforce capability are the defining constraints of this next phase of adoption. Singapore-based businesses face a further dimension: as they expand regionally and globally, they need their AI systems to be trusted not just at home but across multiple jurisdictions — each with its own regulatory expectations and stakeholder standards.

Lee Sze Yeng, Managing Partner at KPMG in Singapore, said: “Across every sector, we are seeing the same pattern: organisations that moved fast on AI are now asking harder questions — where is the real value, are our people genuinely ready to work alongside AI, and can we stand behind the decisions our systems make? These are not technical questions. They are leadership questions. And for Singapore businesses with ambitions beyond our shores, there is an added dimension: the trust that matters to customers and regulators in the markets you are entering may be defined differently from what is required here. Through the KPMG Singapore Trusted AI Centre of Excellence, we are partnering with businesses to rigorously assess where they stand, close the gaps that matter, and build AI that is trusted not just locally but in the markets most critical to their growth. Trusted AI is not a constraint on ambition. Done well, it is the foundation for it.”

Jermaine Loy, Managing Director, EDB, said: “KPMG’s Trusted AI Centre of Excellence here in Singapore will enable businesses across diverse sectors – including financial services, healthcare, logistics and manufacturing – to scale use of AI with confidence, supported by robust governance frameworks and assurance capabilities. At the same time, this strengthens Singapore’s growing AI ecosystem by building enterprise capabilities and workforce readiness for AI adoption. We welcome KPMG Singapore’s efforts to work with EDB and the relevant agencies in advancing Singapore’s position as a globally trusted hub for AI deployment and innovation.”

Trusted AI Assurance — Giving Singapore Businesses a Foundation to Scale AI

For Singapore businesses, the ambition to scale AI is rarely the obstacle. What is harder — and more consequential — is the question of whether the AI they are building and deploying can genuinely be stood behind: by their boards, by their customers, employees and by the regulators and partners they will encounter as they grow beyond Singapore’s shores.

KPMG’s Trusted AI Assurance offering (the “Trusted AI Assurance”) was developed in response to the need to address the trust deficit with AI in the business community to boost adoption. It is not a certification exercise or a compliance checklist. It is a rigorous, evidence-based independent assessment that gives leadership teams an honest picture of where they stand — and a clear, practical path to where they need to be.

What makes it meaningful is its specificity. The Trusted AI Assurance is calibrated to each organisation’s sector, operating context and growth ambitions — because a financial institution navigating cross-border data regulation faces a fundamentally different set of questions from a manufacturer embedding AI into operational workflows, or a healthcare provider deploying AI-assisted diagnostics. Generic benchmarks serve neither well.

The assessment examines two things that are often conflated but must be considered separately: whether an organisation has the governance, culture and leadership practices to deploy AI responsibly; and whether the AI solutions it has built or acquired are themselves trustworthy — documented, risk-assessed, well-integrated and performing as intended. An organisation can have the right intentions and still be running AI that falls short of what its stakeholders — or another country’s regulators — would accept.

Across four domains, the Trusted AI Assurance examines what genuinely matters:

AI Governance — Whether the frameworks, operating models, policies and procedures that govern AI are real and embedded, not aspirational documents that sit untouched between audits.

AI Systems — The AI systems themselves: how they are documented, how risks are inventoried, how models are integrated into business workflows, and whether the data foundations — including Retrieval-Augmented Generation, pipelines and datasets — are robust enough to be relied upon.

AI Regulatory Compliance — How prepared an organisation is for the regulatory environments it currently operates in, and those it intends to enter. For Singapore businesses with expansion ambitions, this is often where the most important gaps surface: the Trusted AI Assurance can identify whether a specific AI system meets the requirements for deployment in a given market — such as the European Union — or what adjustments would make it so.

AI Security — The strategies and processes in place to protect AI systems, manage privacy, and ensure the organisation can detect, respond to and recover from threats as they evolve.

The stakes are sharpest for businesses in highly regulated sectors. Financial institutions, healthcare providers and infrastructure operators have long been accustomed to navigating complex compliance environments — and Singapore’s AI governance frameworks are among the most developed in the region. But as the EU AI Act moves into full enforcement, a new and specific set of expectations is taking effect for any organisation deploying AI within European markets, or handling the data of European citizens. What satisfies regulators here does not automatically satisfy regulators there.

The reality is one of regulatory diversity: different jurisdictions are building their AI governance regimes at different speeds, with different emphases, and with different evidentiary requirements. A Singapore company that has passed relevant local standards may still find that its AI systems require different documentation, greater explainability, or additional human oversight controls to operate with compliance and trust in a European context. Discovering that gap in the middle of a market entry, a cross-border partnership or a regulatory review is a risk that can be avoided.

The Trusted AI Assurance maps these jurisdictional differences, giving organisations a clear read of where they stand against the specific requirements of markets they are entering — before those requirements become obstacles. It is aligned with globally recognised standards including the EU AI Act, the NIST AI Risk Management Framework, ISO 42001 and Singapore’s Model AI Governance Framework, ensuring that what organisations build here is credible and defensible everywhere.

The Trusted AI Assurance is coupled with consultancy guidance — from KPMG or partnered stakeholders — ensuring every assessment leads to a practical path forward. The intent is to give Singapore businesses the clarity and confidence to grow their AI ambitions without having to rebuild trust from scratch in new markets they enter into regionally or globally.

A Framework for Singapore’s AI Ambition: The Four Doors

Beyond the Trusted AI Assurance, organisations can leverage the AI CoE to assess their broader AI strategies through KPMG’s Four Doors framework — four strategic pillars that help Singapore businesses move from isolated pilots to trusted, sustained AI at scale. Together, they address what it takes for Singapore to be not just an AI-capable nation, but a globally trusted one: where the AI solutions developed and deployed here meet the expectations of regulators, partners and customers worldwide.

Value — From Activity to Impact: Establishing the clear metrics and sector-specific solutions needed to distinguish AI activity from measurable business value, across Financial Services, Government, Healthcare, Real Estate, Infrastructure and Manufacturing.

Trust — Trusted-by-Design AI: Built on a human-centric foundation encompassing ten ethical pillars — including Fairness, Transparency, Accountability, Privacy and Sustainability — the Trust pillar puts responsible governance at the centre of AI strategy, rather than treating it as a compliance afterthought.

People — Genuine AI Fluency: Covering sustainable AI workforce strategy, job redesign, leadership development and change management — from executive ignition sessions that build board-level commitment to the behavioural shifts needed to embed AI into everyday working practices.

Data and Technology — Scalable Foundations: Establishing the trusted data and technology infrastructure that enterprise AI requires, supported by KPMG’s proprietary platforms and a market-ready suite of AI tools, with rigorous attention to data quality, system integration, product development and enterprise-wide AI deployment.

For Singapore’s business community, the Four Doors offer a structured path to becoming AI-trusted — not just AI-active. As global regulatory standards tighten and international partners raise governance expectations, that distinction will increasingly determine which Singapore enterprises are positioned to lead in the markets they enter.

Building AI Capability in Singapore

The Trusted AI CoE (the “CoE”) is designed to function as a capability hub to support Singapore’s position as a trusted node in the global community — co-creating knowledge, accelerating innovation and strengthening Singapore’s AI ecosystem across the business community, academia and the public sector.

At its core is a dedicated innovation team of AI/Software Engineers, Solution Architects, Data Analysts, Product Managers, Tech Business Analysts and Designers — 100 per cent Singapore-based and locally hired. This specialist nucleus is complemented by KPMG’s 3,600-strong Singapore workforce and over 275,000 professionals globally, giving the CoE both deep technical capability and multi-disciplinary reach across Audit, Advisory and Tax.

Solutions co-developed through the CoE are pressure-tested with KPMG as default “Client Zero” where appropriate — rigorously iterated across the firm’s own operations before being brought to clients. Initial focus sectors include Financial Services, Infrastructure and Logistics, Manufacturing, Government, Healthcare and Real Estate, alongside functional domains such as Finance, Governance Risk and Compliance, Customer Services and Operations. Strategic partnerships with technology companies, academic institutions and government agencies further support Singapore’s ambition to serve as a trusted and well-governed regional AI hub.

KPMG’s Commitment to Singapore

KPMG is the world’s first professional services firm to attain ISO/IEC 42001 certification for AI Management Systems — the globally recognised standard for responsible AI governance. This underpins every element of today’s launch, reflecting KPMG’s commitment to practising what it advocates: embedding the disciplines of trusted AI governance into its own operations before bringing them to clients.

KPMG continues to invest in Singapore’s AI talent pipeline through international mobility programmes, internal rotations and capability development across data, digital and leadership disciplines — directly aligned with Singapore’s national goal of growing the skilled workforce its AI ambitions require.

ANNEX: Bringing the KPMG Singapore Trusted AI Centre of Excellence to Life

To bring the KPMG Trusted AI Centre of Excellence (AI CoE) to life, guests at the launch were invited to explore four interactive stops (“windows”) showcasing how trusted AI can move from strategy into real-world enterprise and national impact.

FIRST WINDOW – AI Philosophy

The first window introduced guests to KPMG’s Four Doors framework and Trusted AI Assurance – an evidence-based approach designed to help organisations move from AI experimentation to AI that is genuinely trusted by their boards, their customers, and the regulators and partners they encounter as they grow beyond our shores.

Through an interactive scenario set in the financial services sector, the demonstration illustrated how organisations are assessed across four strategic pillars: Value, Trust, People, and Data and Technology. The walkthrough explored whether businesses have the governance structures, workforce readiness, data foundations and operational oversight needed to support trusted, scalable AI deployment.

1. Value — Whether the organisation has clearly defined what its AI investments are meant to deliver, and whether it has the metrics to distinguish genuine business impact from mere AI activity
2. Trust — Whether the organisation’s AI is built on a responsible, human-centric foundation — covering governance frameworks, ethical guardrails, risk management, security and accountability for AI-driven decisions
3. People — Whether the workforce, from board to frontline, has the genuine AI fluency needed to work alongside AI systems, including the leadership commitment, job redesign and capability development required for adoption to take hold
4. Data and Technology — Whether the data assets, infrastructure and system integration practices are robust enough to support trusted, scalable AI deployment

The experience also demonstrated how AI systems themselves are assessed – including areas such as system documentation, risk inventories, model integration and data platform robustness – highlighting the importance of building AI that is genuinely trusted.

1. System Card — Whether each AI solution is properly documented, including how it performs and how it is used in practice
2. Risk Inventory — Whether AI systems across the enterprise have been identified and their risks catalogued
3. Model Integration — Whether adequate processes and controls govern how AI models are integrated into business workflows
4. Data Platform — Whether the data foundations underpinning AI outputs — including Retrieval-Augmented Generation (RAG) pipelines and datasets — are fit for purpose

A second stage of the scenario then explored the reality of regulatory diversity across jurisdictions. While an organisation may be assessed as “trusted” in Singapore, areas that require attention may emerge when expanding into international markets such as Europe under the EU AI Act.

The demonstration underscored the growing importance of regulatory readiness for Singapore businesses with international ambitions, and how the AI CoE is designed to help organisations expand with confidence through trusted AI governance.

SECOND WINDOW – AI Journey

The second window focused on KPMG’s “Client Zero” approach, where suitable AI solutions are developed and applied within its own operations under real-world conditions, and in some cases co-developed with clients depending on their specific needs. This model reflects a simple philosophy: credibility in guiding responsible AI adoption must be earned by applying the same discipline internally. This approach is particularly relevant in Singapore’s context, where trust and reliability are central to how AI is being adopted across sectors.

KPMG’s “Client Zero” approach provides a structured pathway for scaling AI responsibly. Solutions are first embedded into live workflows – allowing organisations to address practical considerations such as human oversight, explainability, data handling and accountability – before broader deployment. This mirrors the journey many enterprises in Singapore are now facing, as they transition from pilots to AI that can be relied on consistently in regulated, cross-border environments. This shift is important, as trust at scale is built not through experimentation alone, but through systems that are reliable, auditable, and able to operate consistently across different contexts.

At this window, MOS will see this pathway brought to life with AI applied across real business workflows, through three solutions: KPMG’s Digital Gateway (DG) GenAI, KPMG Clara Intelligence and Kiara. These solutions are already implemented in real-time across KPMG’s various functions.

The first demonstration illustrates how the audit and tax professions are beginning to deploy AI agents within their workflows to enhance how work is performed. Rather than treating AI as standalone tools, these capabilities are being embedded into business processes to support analysis, decision-making and execution in a controlled and accountable manner. DG GenAI, KPMG’s Generative AI capability embedded within our Digital Gateway platform, will be used as a demonstration of how this is operationalised in practice — showing how AI capabilities can be integrated into everyday workflows, with appropriate governance, data security and user controls in place.

The second demonstration presents KPMG Clara Intelligence, an intelligent AI-powered platform which acts as a centralised platform. KPMG Clara Intelligence showcases the future of audit, where AI is used to support data-driven risk assessment, better insights and analysis and decision-making on a single platform. This reduces reliance on manual processes and enables auditors to focus on higher-value judgement, improving both efficiency and audit quality. MOS will see how this reflects a broader shift in the profession — towards AI-assisted workflows that require new skills and deeper analytical capabilities.

This window also highlighted how AI is reshaping the accountancy and professional services sector. As AI becomes embedded into core workflows, roles within the profession are evolving — routine, manual tasks are increasingly automated, allowing professionals to focus on higher‑value judgement, analysis and advisory work. At the same time, this shift requires a broader base of AI fluency across the workforce, not just among specialists, as professionals will need to work alongside AI systems in their day‑to‑day roles.

These changes are driving a wider rethinking of skills development across the sector, including how institutions and employers prepare current and future talent. Efforts are underway to align training and education pathways with these evolving needs, ensuring that individuals entering the profession — and those already in it — are equipped to operate effectively in an AI‑enabled environment. This reflects a broader transition towards a workforce that combines strong domain expertise with AI capabilities, in line with Singapore’s ambition to develop an AI‑bilingual workforce.

The third solution, Kiara, is KPMG’s GenAI recruitment assistant, illustrating how AI can enhance the candidate engagement and streamline scheduling of interviews. This highlights how AI is not only transforming business processes, but also how people work and interact with technology.

Overall, the window demonstrated how these solutions reflect the same principles KPMG advises its clients to adopt: strong data foundations, embedded governance, and human oversight at key decision points – illustrating the practical steps organisations take to deploy AI responsibly at scale, underpinning the rigour required for Singapore to continue its progress as a trusted hub for AI.

THIRD WINDOW – AI Vision

The third window focused on how AI does not merely change the tools organisations use, but changes the nature of work itself – which roles exist, how decisions are made, and what it means to be genuinely capable in a professional environment.

As organisations navigate AI-driven workforce transformation, the showcase highlighted the same set of questions organisations consistently grapple with: which roles are genuinely enhanced by AI, and which risk being hollowed out? Where should organisations invest in reskilling, and on what timeline? How are accountability and professional standards maintained when AI is embedded into decisions that used to rest entirely with a person?

The insight that emerges across sectors is consistent: organisations that treat AI workforce transformation as a technology deployment tend to underinvest in the human dimensions – and that is where adoption stalls, quality erodes or trust breaks down. The organisations that get it right treat it as a leadership and organisational design challenge first, with technology as the enabler.

The window also demonstrated how KPMG Mystro™, an AI-enabled workforce intelligence platform, is used to map how work is done today at the task and decision level, and model where AI can responsibly augment human roles across functions such as finance, audit and operations.

Drawing on examples from finance, audit and operations, the showcase illustrated professionals working alongside AI in ways that redirect their expertise toward work requiring human judgement. More broadly, it reinforced the importance of approaching AI transformation not simply as a technology deployment exercise, but as a broader leadership and organisational design challenge.

Singapore’s commitment to building an AI-bilingual workforce – professionals who are not merely aware of AI but genuinely capable of working alongside it, questioning its outputs and being accountable for the decisions it informs – rests on organisations taking the human dimension of transformation as seriously as the technology itself. The insights at this window speak directly to that agenda: what it takes to build not just AI capability, but the kind of AI-confident workforce that sustains Singapore’s competitiveness over the long term.

FOURTH WINDOW – AI Ecosystem

The fourth window focused on how trusted AI adoption cannot be the preserve of large enterprises alone. Singapore’s economic resilience depends on its SME community — the businesses that form the backbone of the economy and that stand to gain enormously from AI, but that often lack the resources, expertise or confidence to navigate adoption responsibly.

Referencing the DBS Spark GenAI programme and DBS SME AI Playbook – developed through a collaboration between DBS and KPMG, and supported by SkillsFuture Singapore – the showcase highlighted practical pathways designed to help SMEs build awareness and accelerate their AI adoption through tailored pathways depending on their AI maturity.

1. Start — For businesses at the beginning of their AI journey: practical orientation on what AI can realistically deliver, where to begin, and what foundational steps to take before committing to more significant investment
2. Accelerate — For businesses that have taken initial steps and are ready to move further: guidance on identifying higher-value use cases, building internal capability and managing the operational changes that come with deeper AI adoption
3. Scale — For businesses ready to embed AI more systematically: the governance, integration and workforce considerations that responsible scaling requires

The window also highlighted the broader support ecosystem available to SMEs, including a broader ecosystem of over 16,000 solution providers globally via IMDA’s Open Innovation Platform, alongside the SME AI Playbook which offers practical use cases, success stories from real businesses, FAQs and an AI readiness diagnostic tool.

Economy-wide AI adoption – the kind that drives meaningful productivity gains across the full breadth of Singapore’s business community – only happens if SMEs are part of the story. The DBS SME AI Playbook is a direct response to that reality: a practical, accessible entry point into AI adoption calibrated to the real constraints and real ambitions of smaller businesses.

The collaboration between DBS and KPMG reflects how Singapore’s AI ecosystem works at its best: financial institutions, professional services firms, government platforms and businesses working together to make trusted AI adoption accessible to every part of the economy, not just its largest players.

Hashtag: #KPMG

The issuer is solely responsible for the content of this announcement.

About KPMG in Singapore

KPMG in Singapore is part of a global organization of independent professional services firms providing Audit, Tax and Advisory services. We operate in 138 countries and territories with more than 276,000 partners and employees working in member firms around the world. Each KPMG firm is a legally distinct and separate entity and describes itself as such. KPMG International Limited is a private English company limited by guarantee. KPMG International Limited and its related entities do not provide services to clients.

For more details about our structure, please visit kpmg.com/governance.
For more information, visit kpmg.com.sg
LinkedIn: linkedin.com/company/kpmg-singapore

Huang is expected to meet Taiwan Semiconductor Manufacturing Company chairman and chief executive C. C. Wei as Nvidia prepares a second-half production ramp for Vera Rubin, the next-generation platform that combines new Vera CPUs, Rubin GPUs, advanced memory and high-speed networking for rack-scale AI systems. The visit has drawn close attention because Nvidia’s product cycle is now tied more tightly than ever to Taiwan’s foundries, packaging houses, server assemblers and component suppliers.

Nvidia reported revenue of $81.6bn for the quarter ended April 26, up 85 per cent from a year earlier, with data-centre revenue reaching $75.2bn, up 92 per cent. The company also authorised an additional $80bn in share repurchases and raised its quarterly dividend to 25 cents a share from 1 cent, underscoring the scale of cash generation from the AI infrastructure boom.

Demand is being driven by cloud providers, AI model developers, enterprise customers and sovereign AI projects, all seeking clusters capable of training and running larger generative and agentic AI systems. Nvidia has described the buildout of “AI factories” as one of the largest infrastructure expansions in technology history, with its platform spanning chips, networking, systems software and reference designs for data centres.

Vera Rubin is expected to follow the Blackwell and Grace Blackwell generation, which is still being shipped in high volumes. That overlap is creating pressure across Taiwan’s supply chain because new capacity must support existing commitments while preparing for a platform with different requirements in advanced packaging, high-bandwidth memory integration, board assembly, cooling and system validation.

Huang has described Vera Rubin as potentially the biggest product ramp in Nvidia’s history and one of the largest technology manufacturing efforts Taiwan has handled. Industry estimates around the platform point to millions of parts across each system and the involvement of well over 100 Taiwan-based ecosystem partners, from chip fabrication and advanced packaging to printed circuit boards, power systems, connectors, thermal modules and final server integration.

TSMC remains central to the effort because Nvidia depends on its leading-edge process technology and advanced packaging capacity. The challenge is not limited to wafers. CoWoS and other packaging technologies have become strategic bottlenecks as AI accelerators require multiple logic dies, high-bandwidth memory stacks and dense interconnects. Any delay in packaging expansion can ripple through server production schedules, cloud deployment plans and Nvidia’s revenue timing.

Taiwan’s broader technology sector has become a critical artery for the global AI trade. TSMC, Foxconn, Quanta, Wistron, Wiwynn, Inventec and a dense network of specialist suppliers are competing to add capacity while dealing with constraints in land, power, water, skilled labour and equipment availability. The concentration gives Nvidia speed and engineering depth, but also exposes the company to geopolitical and operational risks.

China remains the clearest commercial setback. Huang has said US export controls have pushed Nvidia’s share of China’s advanced AI chip market to zero, a striking reversal for a company that once held a dominant position there. The restrictions have strengthened the opening for Huawei and other domestic suppliers, while leaving Nvidia dependent on whether Washington and Beijing allow compliant chips to be sold without triggering national-security objections.

That loss has not slowed Nvidia’s global momentum, but it has changed the composition of growth. Revenue is now increasingly concentrated in markets where hyperscale cloud companies, enterprise AI developers and governments are building large AI data centres outside China. For investors, the question is whether demand can keep absorbing each successive architecture at the scale implied by Nvidia’s guidance.

Nvidia forecast revenue of about $91bn for the current quarter, above market expectations, signalling that orders for AI infrastructure remain strong despite concerns about overcapacity, power shortages and the pace at which customers can monetise AI services. Operating expenses rose 49 per cent to $7.75bn, reflecting the growing cost of research, supply commitments and ecosystem investments needed to sustain the company’s lead.