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Over the two-year period from 2023 to 2025, cumulative growth reached approximately 5.9-fold in number loans issuedand 8.7-fold in disbursement value. Skyro’s loan portfolio includes POS (point-of-sale) installment loans, cash loans, and сredit lines.

Skyro co-founder, Nasim Aliev:

“We are proud to deliver multiple-fold growth in our loan portfolio, significantly outpacing the overall expansion of consumer lending in the Philippines. Since launching in 2022, Skyro has focused on offering a simple, convenient and mobile-first solution at the point of sale, building a business that is clearly in strong demand. Our core mission is to empower people by providing accessible financing. The priority remains delivering innovative, AI-powered digital finance tools that enhance the customer experience.”

Skyro co-founder, Arsen Liametov:

“We’ve been tripling our revenue every year since 2022. Our success in unsecured lending in the Philippines provides a strong foundation for expansion into additional fintech products and new jurisdictions across developing markets. Backed by Skyro’s multinational team of over 600 fintech professionals with experience across more than 20 markets, we bring a broad perspective that strengthens our ability to scale our business model internationally.”

Over the past year, Skyro’s customer base doubled and remains on a strong upward growth trajectory. At the same time, its loan portfolio was significantly de-risked, primarily dueto Skyro’s AI-driven scoring system. The number of registered users on the Skyro platform reached 6.3 million at the end of 2025. The average loan size grew by nearly 30% year-on-year, driven by a shift toward larger-ticket products.

Skyro’s merchant partner network expanded significantly in 2025, with particularly strong growth in the online channel. The number of online partners grew by 405%, reflecting an active push into e-commerce POS lending. The offline network added 631 new merchant locations, growing by 50%. By the end of 2025, Skyro had partnered with more than 2,000 merchants, including those operating nearly 9,000 brick-and-mortar stores.

Hashtag: #Skyro

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

About SKYRO

Skyro is a high-growth, digital-first fintech group delivering scalable, responsible financial access across high-potential emerging markets. Powered by proprietary data science, AI-driven credit decisioning, and alternative-data scoring, the company combines a mobile-native experience with modular fintech architecture to serve underserved client segments at scale.

In just three years, Skyro has grown to serve over one million active customers in the Philippines, underpinned by a robust credit portfolio exceeding $200 million. The company’s strategic ambition is to establish itself as the preeminent full-spectrum financial services group across dozens of emerging markets worldwide.

Prudent Risk Management Yields Solid Outcomes metrics, Core Pawn Business Demonstrates Resilient Growth with Proposed Final Dividend of HK$1.15 cents per share

Results Highlights:

• Profit for the year attributable to shareholders increased by approximately 47.8% YoY to approximately HK$82.6 million
• Net profit margin increased by approximately 16.2 p.p. YoY to approximately 50.2%
• Impairment losses recognized on loan receivables decreased by approximately 72.6% YoY to HK$12.7 million
• Revenue from pawn loan business increased by approximately 12.9% YoY to approximately HK$98.6 million
• Proposed final dividend of HK$1.15 cents per share

HONG KONG SAR – Media OutReach – 27 May 2026 – The board of directors of Oi Wah Pawnshop Credit Holdings Limited (HKEx stock code: 1319.HK, the “Group” or “Oi Wah”) announced its annual results and its financial position. For the year ended 28 February 2026 (“FY2026“), the Group recorded revenue of approximately HK$164.4 million. Profit attributable to shareholders of the Company reached approximately HK$82.6 million, representing an increase of 47.8% compared to the year ended 28 February 2025 (“FY2025“). During the year, net interest margin expanded to approximately 17.2%.

As of 28 February 2026, the cash and cash equivalents (net of bank overdraft) amounted to approximately HK$376.9 million, representing a substantial increase of approximately 74.8% YoY. The net assets increased to approximately HK$1,155.7 million. Concurrently, the gearing ratio dropped to 4.1%. During the year, the earnings per share increased by approximately 48.3% YoY to HK 4.3 cents. The Board of Directors recommends a final dividend of HK 1.15 cents per share.

BUSINESS REVIEW

Mortgage loan business

In FY2026, the economy entered a phase of gradual recovery, leading to a steady resurgence in financing demand. The revenue from the mortgage loan business was approximately HK$65.8 million and accounted for approximately 40.0% of the Group’s total revenue during the year. The gross mortgage loan receivables were approximately HK$612.5 million as at 28 February 2026. During the year, net interest margin of the mortgage loan business was approximately 10.1%.

In FY2026, the Group maintained a disciplined and risk-sensitive approach in its lending activities. While we observed an encouraging stabilization in the residential property market, the Group exercised intensified vigilance toward the commercial and industrial sectors due to persistent supply overhangs and valuation pressures. Our underwriting strategy remained focused on building a resilient loan portfolio by prioritizing high-quality collaterals and prudent loan-to-value ratios. During the year, the average loan-to-value ratio for first mortgage was approximately 56.27%, while overall average loan-to-value ratio for subordinate mortgage was approximately 40.82% of which, average loan-to-value ratio of subordinate mortgage that the Group participated in was approximately 3.73%.

Reflecting our robust credit risk management, the charge for impairment losses recognized on loan receivables decreased from approximately HK$46.3 million to approximately HK$12.7 million, representing a decrease of approximately 72.6% or HK$33.6 million.

Pawn Loan Business

The revenue from the pawn loan business increased by approximately 12.9% to approximately HK$98.6 million in FY2026. The business’s profitability was further bolstered by a significant 73.0% increase in the gain on disposal of repossessed assets, which reached approximately HK$19.2 million as compared to approximately HK$11.1 million in FY2025. This performance was mainly attributed to the unprecedented strength of gold prices and a highly active secondary market for luxuries, particularly high-end timepieces. These factors have further solidified the pawn loan business as a resilient and strategic hedge against broader economic volatility.

During the year, the Group continued to channel resources to advertising and promotion to enhance the Group’s brand exposure. Such effort has generated demand for one-to-one pawn loan appointment services for pawn loans exceeding HK$0.1 million.

PROSPECTS

Looking ahead, the Group maintains a stance of cautious optimism regarding the global economic recovery. While macroeconomic and geopolitical uncertainties may persist, we remain dedicated to a proactive yet prudent strategy to ensure sustainable long-term growth and maximize returns for our shareholders.

Within the mortgage loan market, our strategy will be characterized by a calibrated and divergent approach. We continue to hold an optimistic outlook on the residential property segment, where we intend to capitalize on the stabilizing interest rate environment by identifying high-quality mortgage opportunities. Conversely, we maintain cautious and vigilant towards the commercial and industrial sectors. Given the structural challenges of inventory overhang and the increasing prevalence of distressed assets, the Group will exercise intensified oversight in its credit underwriting and collateral appraisal to mitigate valuation risks.

Regarding our core operations, we anticipate our pawn loan business to remain resilient, supported by a firm gold price trajectory and sustained demand for liquidity management. To further enhance operational efficiency, the Group is actively optimizing its pawn shop network. We are strategically identifying more cost-effective locations within our established service areas, aiming to relocate our pawn outlets to premises with more competitive lease terms to reduce operating overheads while maintaining our leading market presence.

Simultaneously, our strategic partnership with PACM Group remains a key driver for geographic diversification. By proactively exploring institutional credit opportunities in developed markets while maintaining rigorous investment oversight, the Group is well-positioned to navigate evolving industry dynamics and deliver stable value to all stakeholders.

Mr. Edward Chan, Chairman and CEO of the Company, said, “Global geopolitical and macroeconomic uncertainties intertwine, placing pressure on the global economic recovery and posing ongoing challenges to the local property market. In the face of a complex external environment, Oi Wah has consistently adhered to a proactive yet prudent management strategy. Our core pawn loan business has fully demonstrated its role as a strategic tool to hedge against macroeconomic fluctuations, showcasing the Group’s strong resilience amidst market challenges.

Looking forward, we will adopt a carefully calibrated differentiation strategy and continue to drive regional diversification. Under strict investment monitoring, we will actively explore business opportunities in developed markets to further expand our revenue streams and customer base, striving to deliver long-term, stable, and sustainable returns for our shareholders.”

Hashtag: #OiWah

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

About Oi Wah Pawnshop Credit Holdings Limited

Oi Wah is a financing service provider in Hong Kong, mainly providing short-term secured financing, including pawn loans and mortgage loans. The Group established its first pawnshop in 1975 and currently owns 10 pawnshops and one premium service center in various locations in Hong Kong. Oi Wah diversified into mortgage loan business in 2009. The Group is the first local pawn shop which successfully listed on the Main Board of The Stock Exchange of Hong Kong Limited on 12 March 2013.

Online retail sales of goods and services rose 6.6 per cent year on year in January-April, reaching about 6.53 trillion yuan, as digital platforms continued to draw shoppers through discounts, livestreaming, faster delivery and wider service offerings. Online retail sales of goods contributed 72.2 per cent to the growth of total retail sales of consumer goods, underlining the sector’s importance to household consumption and the wider services economy.

The performance stood out against a softer macroeconomic backdrop. Total retail sales of consumer goods increased 1.9 per cent year on year to 16.49 trillion yuan in the first four months, while April’s retail sales rose only 0.2 per cent from a year earlier, slowing sharply from March. Industrial output also moderated in April, while fixed-asset investment weakened in the January-April period, adding pressure on policymakers to keep consumption and digital commerce at the centre of growth-support measures.

Food, apparel, daily necessities and services remained key pillars of online demand. Online sales of agricultural products rose 12.2 per cent during the four-month period, reflecting stronger farm-to-consumer supply chains and the growing ability of digital platforms to connect rural producers with urban buyers. E-commerce transactions involving metal products climbed 34.8 per cent, while chemical products rose 12.2 per cent, signalling that business-to-business digital trade is becoming a larger part of the sector’s expansion.

Services delivered some of the strongest growth. Online tourism sales jumped 33.2 per cent, while online catering sales rose 20 per cent, helped by domestic travel demand, app-based restaurant bookings, group-buying promotions and instant delivery networks. This shift has broadened the definition of e-commerce beyond parcel delivery, making it a channel for local services, entertainment, travel and food consumption.

China’s major platforms remain central to the sector’s trajectory. Alibaba continues to rely on Taobao and Tmall while pushing faster local delivery through integrated quick-commerce services. JD. com is using its logistics network to defend its position in electronics, household goods and same-day fulfilment. Pinduoduo remains a powerful force in value-led shopping, while Douyin and Kuaishou have expanded livestream commerce by converting entertainment traffic into direct sales. Meituan has become a key player in instant retail, extending its food-delivery infrastructure into groceries, medicines, flowers, consumer goods and convenience-store items.

The fastest change is taking place in instant retail, where platforms promise deliveries within an hour by linking consumers to nearby warehouses, restaurants, pharmacies and shops. The model has moved beyond food delivery into daily essentials and non-food categories, creating a new battleground for Alibaba, JD. com and Meituan. Heavy subsidies have helped attract users, but they have also raised concerns about margins, rider welfare, food safety and wasteful competition.

Regulatory scrutiny is rising alongside the sector’s growth. Authorities have fined major food-delivery and e-commerce platforms over failures in vendor verification and consumer protection, while new rules on platform pricing and unfair competition are tightening oversight of discounting, algorithms and merchant treatment. The regulatory direction suggests support for digital commerce will continue, but platforms are being pushed towards higher-quality growth rather than unchecked subsidy wars.

Cross-border e-commerce also remained a bright spot. The Silk Road e-commerce initiative helped lift online sales of imported products from partner countries, with Thai durians, beverages from the UAE and Italian casual trousers recording sharp gains in January-April. The trend points to growing consumer appetite for imported food, fashion and lifestyle products, while also helping overseas exporters access China’s vast digital marketplace through platform partnerships, bonded warehouses and livestream selling.

Rural e-commerce is another policy priority. Expanded digital infrastructure, village-level logistics points and platform-backed agricultural campaigns have helped smaller producers sell fruit, tea, seafood, grains and speciality foods directly to consumers. The model supports rural incomes and reduces dependence on traditional wholesale chains, though smaller sellers still face challenges from platform fees, return costs, traffic concentration and intense price competition.

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.

Commerce and Industry Minister Piyush Goyal’s visit to Ottawa and Toronto, accompanied by more than 100 business leaders, has added momentum to negotiations on a Comprehensive Economic Partnership Agreement, which both sides see as central to expanding market access, investment flows and supply-chain cooperation. The visit comes after a prolonged freeze in trade discussions caused by the diplomatic dispute that followed the 2023 killing of Sikh separatist Hardeep Singh Nijjar in British Columbia.

New Delhi and Ottawa are now working to rebuild trust through a structured commercial agenda covering energy, agriculture, critical minerals, technology, education and services. The scale of the business delegation travelling with Goyal underlines the attempt to shift the relationship from political caution to transaction-led engagement. A “Team Canada” delegation is expected to visit India later this year, signalling that both governments want to sustain ministerial and private-sector contact beyond formal negotiating rounds.

Bilateral trade remains below potential for two large economies with complementary strengths. Merchandise trade between the two countries stood at about $13.6 billion in 2025, with Canada exporting vegetables, mineral fuels, oils and wood pulp, while imports from India were led by precious stones and metals, machinery, pharmaceuticals and manufactured goods. Services trade, especially in technology, education, professional services and mobility-linked sectors, has grown into a significant part of the relationship.

The $50 billion target is ambitious but not beyond reach if negotiations produce tariff concessions, regulatory clarity and stronger investment protections. India is seeking reliable access to critical minerals, energy products, gas, fuel and agricultural inputs from Canada. Ottawa, for its part, sees India as a large growth market at a time when Canada is trying to diversify trade beyond its heavy dependence on the United States.

Energy is likely to become one of the pillars of the renewed partnership. Canada’s reserves of uranium, potash, natural gas and critical minerals fit India’s requirements for food security, clean energy expansion and industrial supply chains. Civil nuclear cooperation has returned to the agenda, with uranium supply discussions forming part of the broader effort to rebuild strategic confidence. India’s rising electricity demand and its plan to expand non-fossil energy capacity give Canada a commercial opening in nuclear fuel and related technologies.

Agriculture and fertilisers also carry strategic weight. Canada is a major supplier of potash, while India’s farm sector requires stable input supplies to support food production. Pulses have long been part of the trade basket, though pricing, phytosanitary rules and domestic market sensitivities have at times complicated flows. A broader agreement could provide more predictable rules, but both sides will have to manage farmer concerns and safeguard mechanisms carefully.

Technology and education offer another route to deeper engagement. Canada remains a major destination for students from India, while companies in both countries are exploring artificial intelligence, clean technology, fintech, cybersecurity and advanced manufacturing. Talent mobility will remain a sensitive but crucial component of any expanded economic relationship, especially as Canada adjusts immigration settings and India pushes for easier access for skilled professionals.

The political backdrop remains complex. Relations deteriorated sharply in 2023 after Canada alleged involvement by agents linked to New Delhi in Nijjar’s killing, an accusation India rejected. Diplomatic expulsions and a pause in trade talks followed, slowing a relationship that had already been marked by differences over separatist activism, security concerns and diaspora politics. The decision to restart CEPA negotiations reflects a pragmatic calculation that economic interests can create stabilising channels even when political trust is still being repaired.

Business groups on both sides are pressing for faster progress. Exporters want lower tariffs, simpler customs procedures and clearer standards rules. Investors are seeking safeguards, dispute-resolution mechanisms and sectoral openings. Canada’s pension funds and institutional investors already have exposure to infrastructure, real estate and financial assets in India, while companies from India are looking at Canadian opportunities in technology, mining, manufacturing and services.

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.

• 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.

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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.

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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.

Commerce and Industry Minister Piyush Goyal is scheduled to visit Canada from May 25 to 27, accompanied by around 150 business leaders for meetings in Ottawa and Toronto. The delegation is expected to include senior representatives from mining, energy, automotive, aerospace, manufacturing, pharmaceuticals, education and technology, with talks centred on investment, market access and the proposed Comprehensive Economic Partnership Agreement.

The visit comes as negotiators from both countries hold another round of discussions in Ottawa from May 25 to 29. Officials are working towards an early conclusion of the trade pact after formally relaunching negotiations this year. The agreement is intended to widen market access, reduce barriers and deepen supply-chain cooperation across sectors where both economies see strategic value.

Bilateral trade stood at nearly $9bn in 2024-25, modest in relation to the size of the two economies. Both governments have set a target of raising trade to $50bn by 2030, a goal that would require faster progress in goods, services, investment and energy cooperation. Canada is seeking stronger commercial links beyond its heavy dependence on the United States, while New Delhi is trying to secure reliable supplies of critical minerals, uranium, clean-energy technology and advanced manufacturing inputs.

Energy and minerals are expected to figure prominently in the discussions. Canada holds significant reserves of uranium, potash, lithium, nickel, cobalt and rare earth elements, all of which are relevant to New Delhi’s nuclear power, fertiliser security, electric mobility and electronics manufacturing plans. Earlier this year, the two sides announced a C$2.6bn uranium supply arrangement involving Cameco, giving fresh weight to talks on long-term clean-energy cooperation.

Market access will be another sensitive area. New Delhi wants wider entry for textiles, leather goods, processed foods, pharmaceuticals and services, while Canada is expected to push for opportunities in agriculture, energy, education, financial services and high-technology sectors. Businesses on both sides have argued that tariffs, standards, certification rules and mobility restrictions have limited the relationship despite strong people-to-people ties and a large diaspora in Canada.

The delegation also carries political significance. Relations deteriorated sharply in 2023 after Ottawa alleged involvement by New Delhi in the killing of Sikh separatist leader Hardeep Singh Nijjar in British Columbia. New Delhi rejected the allegation, and both sides expelled diplomats as the dispute spread into security, visa and intelligence cooperation. The strain interrupted trade talks and pushed commercial engagement into a lower gear.

A gradual reset began after political engagement resumed at senior levels. Canada’s Prime Minister Mark Carney invited Prime Minister Narendra Modi to the G7 summit in Alberta in June 2025, and the two governments subsequently restored channels for trade and strategic dialogue. Carney’s visit to India in March 2026 gave the relationship a clearer economic framework, including the signing of terms of reference for the trade pact and a commitment to expand cooperation in energy, technology, agriculture, education and defence-related sectors.

The May visit is designed to move that process from political signalling to business execution. Meetings with Canadian ministers, industry bodies and corporate leaders are expected to test where near-term agreements are possible, especially in sectors less vulnerable to political friction. Ottawa and New Delhi are also exploring cooperation in shipbuilding, pharmaceuticals, tourism and education, areas identified during earlier ministerial exchanges.

Canada’s interest is shaped by a broader effort to diversify export markets and reduce exposure to shifts in US trade policy. New Delhi, meanwhile, is looking for partners that can support its manufacturing expansion, clean-energy transition and mineral security. The fit is commercially evident, but negotiations are likely to remain complex because both sides have defensive interests in agriculture, labour mobility, procurement and regulatory standards.

For businesses, the scale of the delegation suggests a wider appetite to resume investment conversations that had slowed during the diplomatic dispute. More than 600 Canadian companies have a business presence in India, while firms from India have built interests in information technology, steel, automotive components, hospitality and financial services in Canada. Student mobility and professional services also remain important links, although visa and security concerns have added caution to the relationship.

The Tokyo-listed investment group has become one of the most closely watched proxies for AI demand after committing tens of billions of dollars to OpenAI and building exposure across chips, power infrastructure, robotics and data-centre supply chains. The latest rally extended a sharp two-session advance that added tens of billions of dollars to SoftBank’s market value, marking one of its strongest runs since the technology boom that first made the group a symbol of risk-taking capital.

Investor enthusiasm has been driven by two linked expectations. OpenAI is preparing for a confidential US initial public offering filing that could set up a listing as early as September, while SB Energy, a power and data-centre infrastructure company backed by SoftBank and OpenAI, has said it intends to confidentially file for a US IPO. Together, the developments have strengthened the market view that SoftBank’s private holdings may be moving closer to public-market price discovery.

SoftBank’s OpenAI position is the main driver of that reassessment. The group has invested $34.6bn in the ChatGPT maker since September 2024 and has agreed to make a further $30bn investment through SoftBank Vision Fund 2. Completion of those tranches would lift its cumulative investment to $64.6bn for an ownership interest of about 13 per cent. The preferred shares are designed to convert automatically into common shares if OpenAI completes an IPO or related listing transaction.

OpenAI’s valuation has become central to SoftBank’s investment case. The company was valued at $852bn in private markets and preliminary discussions around a listing have included the possibility of a valuation as high as $1tn. The company is also seeking to raise at least $60bn at the lower end of earlier discussions, reflecting the huge capital needs of frontier AI model development, data centres, chips and power supply.

The OpenAI bet has already reshaped SoftBank’s earnings profile. The group reported a sharp profit rebound, helped by valuation gains tied to OpenAI, and said cumulative gains on the investment had reached $45bn. Its annual profit of about ¥5tn was described by the company as the highest recorded by a Japanese company, underscoring how quickly Son’s AI strategy has altered investor perceptions after years of scrutiny over the Vision Fund’s uneven performance.

SB Energy has added another layer to the rally because its business sits at the intersection of AI and power infrastructure. Founded in 2019, the company develops large-scale energy and data-centre projects and has positioned itself to benefit from surging electricity demand linked to AI workloads. It has raised more than $18bn in project capital and has a portfolio of about 5 gigawatts of operating and under-construction energy assets.

The company’s January partnership with OpenAI under the Stargate initiative placed it inside a broader push to build AI and energy infrastructure in the United States. That has made SB Energy more than a conventional renewable power developer in the eyes of investors. Its appeal rests on the argument that AI expansion will require dedicated power generation, grid connections and purpose-built campuses capable of supporting high-density computing.

SoftBank’s rally has also been supported by strength in Arm Holdings, the UK chip designer in which the group holds a large stake. Arm remains a key public asset for SoftBank and is viewed as a beneficiary of AI-related semiconductor demand. Gains in Arm shares have helped reinforce confidence that SoftBank owns multiple assets tied to the same structural theme, rather than a single concentrated wager on OpenAI.

The optimism carries risks. OpenAI faces intensifying competition from Alphabet’s Gemini, Anthropic’s Claude and other model developers, while the cost of training and operating advanced AI systems continues to rise. Credit analysts have raised concerns that the size of SoftBank’s OpenAI commitment may affect liquidity and asset quality, particularly as the group uses loans, asset sales and financing backed by holdings such as Arm and SoftBank Corp. to fund its strategy.

SoftBank arranged a $40bn bridge loan in March and drew $20bn in April, largely for the OpenAI investment, while also repaying part of that borrowing. The group has sold stakes in holdings including Nvidia and T-Mobile, issued bonds and considered other financing options as it reallocates capital towards AI. Chief Financial Officer Yoshimitsu Goto has said the group may also explore ways to use its OpenAI assets for financing if market conditions allow.