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• 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.

Invest Qatar’s delegation, led by its chief executive Sheikh Ali bin Alwaleed Al-Thani, held executive-level meetings, site visits and closed-door business discussions with Chinese companies across advanced manufacturing, life sciences, industrial technologies and digital platforms. The engagements included WuXi Biologics, Shanghai SUS Environment, Cainiao Group and Ant International, placing the tour at the intersection of Qatar’s diversification agenda and China’s strengths in biotechnology, logistics, environmental services and digital finance.

The visit was designed to present Qatar as a platform for regional expansion, with Invest Qatar highlighting support for market entry, regulatory coordination, site selection, expansion planning and aftercare services. The pitch reflects Doha’s effort to move beyond energy-led ties and attract capital, technology and operational expertise into sectors linked to the Third National Development Strategy and Qatar National Vision 2030.

China already occupies a central place in Qatar’s external economic network. Bilateral cooperation spans energy, logistics, manufacturing, technology and financial services, while Qatar hosts about 520 Chinese companies. Over the 2017-2026 period, China has ranked among Qatar’s top 10 sources of foreign direct investment, with 59 projects generating more than $3bn in capital expenditure and creating more than 3,200 jobs across multiple sectors.

The Shanghai and Hangzhou programme signals a more targeted approach by Qatar’s investment promotion authorities. Rather than broad promotional activity, the delegation focused on companies that fit Qatar’s priority clusters. WuXi Biologics brings relevance to life sciences and contract research, Shanghai SUS Environment operates in waste-to-energy and environmental infrastructure, Cainiao Group is a major logistics and supply-chain player, and Ant International strengthens the digital payments and fintech dimension of the outreach.

Energy remains the anchor of Qatar-China economic relations. China is Qatar’s largest trading partner, with bilateral trade reaching $24.22bn in 2024. China exported goods worth about $4.17bn to Qatar and imported about $20.05bn, led by liquefied natural gas and industrial helium. Qatar is also China’s second-largest source of LNG imports, reinforcing the strategic weight of the relationship at a time when Asian demand remains central to global gas markets.

QatarEnergy’s expansion strategy has further tightened industrial links with China. Long-term LNG supply arrangements linked to the Chinese market, together with major vessel orders placed with Chinese shipbuilders, have created a broader commercial ecosystem around the North Field expansion. Qatar aims to raise LNG production capacity from 77mn tonnes a year to 142mn tonnes by 2030, a target that will require shipping, engineering, financing and downstream partnerships across Asia.

The investment outreach comes as Gulf states increasingly seek to use energy relationships as a foundation for wider economic cooperation with Asia. For Qatar, China offers scale, capital depth and technology capacity. For Chinese groups, Qatar provides political stability, strong transport connectivity, free-zone infrastructure and access to Gulf, African and South Asian markets.

Doha is also seeking to position itself as a business base for companies navigating a more fragmented global trade environment. Regulatory certainty, a relatively high-income market, advanced digital infrastructure and a sovereign investment ecosystem give Qatar tools to compete for regional headquarters, specialised manufacturing and services projects. The challenge will be converting exploratory meetings into project commitments in sectors where regional competition is intense, particularly from Saudi Arabia and the UAE.

Financial services form another important strand of the relationship. Qatar Investment Authority’s moves in China’s asset management sector and broader Gulf interest in Asian financial markets point to a shift from passive portfolio exposure towards more strategic investment channels. That trend could support new capital-market links, fintech partnerships and investment vehicles connecting Doha and Chinese financial centres.

The latest Invest Qatar tour also reflects a diplomatic-economic strategy that has become more visible across Asia. Qatar has sought to deepen ties with major economies while keeping its partnerships diversified across the United States, Europe, China and other Asian markets. This balancing approach allows Doha to pursue commercial opportunities while avoiding excessive dependence on any single investment corridor.

For Chinese companies, Qatar’s offer is strongest where national development goals align with corporate expansion plans. Life sciences companies can tap healthcare investment and research partnerships, logistics operators can link into Hamad Port, Hamad International Airport and regional re-export networks, and digital platforms can benefit from a market that has been investing in cashless payments, cloud services and smart-city infrastructure.

Revenue Up 35.4% Year-on-Year API Token Call Volume Surges Nearly 6 Times

HONG KONG SAR – Media OutReach Newswire – 22 May 2026 – Phancy Group Co., Ltd. (“Phancy” or “The Company”, stock code: 6682.HK), a leading general artificial intelligence company, today announced its unaudited consolidated results for the first quarter ended 31 March 2026.

During the period, Phancy achieved revenue of approximately RMB1.458 billion, representing a 35.4% year-on-year increase. Gross profit margin remained at 35.1%. Phancy leveraged its deep expertise in full-stack AI cloud services, to capitalize on the accelerating adoption of localized computing power and strong enterprise demand for AI solutions. The Company achieved robust growth in its core businesses, accelerated product innovation, and secured several major partnerships, sustaining strong operational momentum.

2026 First Quarter Business Highlights:

Unified Enterprise AI Platform Drives Explosive Core Business Growth

Global computing resources remain constrained, while demand for both private enterprise AI deployments and API-based model calls continues to grow rapidly. Phancy’s enterprise-grade AI platform is built on a unified core architecture that seamlessly supports both API calling scenarios and dedicated private deployments. This significantly boosts AI application efficiency and resource utilization. Supported by a mature computing power supply chain developed over many years, Phancy’s deployable computing power resources have increased by over 200%. This enables the Company to effectively meet surging Token demand and consistently deliver stable, high-quality AI services to its customers.

In the first quarter of 2026, API Token call volume surged nearly 6 times compared to the same period in 2025, and already accounted for nearly 40% of the full-year 2025 total. Meanwhile, the Agentic AI business expanded rapidly, with deepening commercial adoption. Orders on hand grew nearly 100% compared to the end of 2025, emerging as a major growth driver for the Company.

AI Technology Iteration Accelerates, Commercialization Beats Expectations

Building on its continued push into digital employee applications and AI empowerment across business units, Phancy has significantly shortened the product development cycle from R&D to commercialization, enhancing overall operational efficiency and customer satisfaction.

As of mid-May 2026, ModelHub XC has completed adaptation and optimization for over 70,000 AI models on domestic chips, achieving more than 70% of its full-year target – well ahead of schedule.

In May, Phancy launched PhanthyMovie, a professional-grade AI video generation platform designed to enhance creativity, control, and stability in video production, enabling standardized and large-scale content creation for the industry.

Leveraging its advanced technology and proven execution capabilities, PhanthyMovie achieved rapid commercial traction. Just days after launch, the Company entered into a strategic cooperation agreement with Huanxi Media, covering approximately US$200 million in AI Token usage. The two parties will also collaborate on the development of a next-generation AI-powered film and television content production platform, further strengthening Phancy’s position in the AI-driven cultural and creative sector.

Core Products Align Closely with Policy Trends, Strengthening Compute-Model Integration

Since May 2026, China’s AI sector has seen a series of positive policy developments focused on computing infrastructure, data element circulation, and open-source compliance governance. Phancy’s core products, including HAMi vGPU and ModelHub XC, are well-aligned with national policy directions and mainstream industry trends.

In terms of computing resource allocation, policies emphasize cross-regional collaboration and broader access to computing power. Phancy’s HAMi vGPU offers unified scheduling and fine-grained resource partitioning, effectively improving utilization rates, optimizing data center energy efficiency, and supporting unified management across multiple chips to boost single-card efficiency.

In data and model governance, the government continues to promote high-quality dataset development and compliance management. ModelHub XC supports multi-model adaptation and optimization, incorporates data traceability and security certification features to help enterprises reduce compliance risks, and uses the EngineX engine for batch adaptation of domestic chips and models. This significantly improves compatibility while enhancing Token output efficiency through targeted model tuning.

Through deep integration of its computing and model layers, Phancy has built a comprehensive “Compute–Model” integrated solution. This addresses key industry needs such as efficient computing utilization, secure data supply, enterprise compliance, and domestic substitution, while strengthening its technological moat. The Company is well positioned to capture policy dividends and industry opportunities, supporting enterprises in their digital and intelligent transformation.

Hashtag: #PhancyGroup

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

About Phancy Group

Phancy Group (6682.HK) is a leading full-stack AI cloud services platform, providing comprehensive solutions for the AI 2.0 era. Our offerings include SageAIOS, HAMi vGPU and ModelHub XC, delivering efficient and scalable AI infrastructure with end-to-end capabilities. We provide a complete solution from heterogeneous compute resource management and optimization to the deployment of intelligent agent models. These solutions empower digital transformation across a wide range of industries, supporting our vision of building a large-scale and efficient “Token Factory.”

Guided by the mission of “AI for Everyone” and positioned as the “Navigator of AI,” Phancy Group is committed to becoming a global leader in Artificial General Intelligence.

A 2026 software supply chain security assessment shows that about 65 per cent of organisations in India cannot detect malicious packages, while 71 per cent do not use container security tools. The findings underline a widening gap between the speed of AI-led software development and the controls needed to secure code, dependencies, models and deployment pipelines before they reach production systems.

Security teams are facing a more complex threat environment as AI coding assistants, model registries, agent frameworks and machine-learning libraries become embedded in day-to-day software engineering. AI is no longer confined to application features or analytics layers. It is becoming part of the software supply chain itself, influencing how code is written, tested, packaged and deployed.

Enterprises in India have been quick to adopt AI tools to improve developer productivity, reduce repetitive work and accelerate product releases. Yet the same shift has increased reliance on open-source packages, pre-trained models, plug-ins and automated build systems. Each of these components can introduce hidden risks if provenance, integrity and behaviour are not continuously verified.

Global software repositories are now attracting sustained attacks because they provide a direct route into enterprise development environments. Malicious npm packages rose by 451 per cent during 2025, while more than 48,000 new Common Vulnerabilities and Exposures were disclosed worldwide, a rise of about 20 per cent from the previous year.

The pressure on security teams is being amplified by the volume of AI-generated code. Developers in India are spending about 51 per cent of their time reviewing, validating and hardening code produced by AI tools. About 53 per cent treat such output only as a starting point and review every line before use, while 11 per cent rewrite AI-generated fixes from scratch.

This shift has altered the economics of software engineering. AI may reduce the time needed to draft code, but it can also transfer effort to verification, testing and security review. Weaknesses such as cross-site scripting, SQL injection and missing authorisation checks can still be reproduced by automated tools, particularly when developers rely on generated code without adequate scrutiny.

Governance is emerging as another area of concern. Nearly 97 per cent of organisations surveyed said they had certified AI model governance programmes, but only 59 per cent claimed full provenance visibility across production environments. About 48 per cent still needed a week or longer to produce audit-ready compliance evidence.

That gap points to a difference between policy and enforceable control. Many enterprises have AI governance frameworks on paper, but fewer can prove where every model, library, container image and software artefact came from, how it changed, who approved it and whether it complies with internal policy.

CERT-In has also warned that software supply chain compromises are increasingly targeting developer tools and trusted repositories. Its April 2026 activity note referred to attacks affecting npm, PyPI, GitHub Actions and container registries, including incidents involving Checkmarx, Trivy, LiteLLM, Axios, Telnyx and npm packages linked to the CanisterWorm campaign. The payloads observed in these attacks included credential harvesting, data exfiltration, remote execution and persistence within developer systems.

Model registries have added another layer to the risk. Around 1.4 million new AI artefacts were published on Hugging Face during 2025, representing 58 per cent of all new software packages tracked in one assessment. Researchers identified 495 malicious AI models in public repositories with active payloads capable of credential theft, command execution and reverse-shell activity, along with 969 malicious AI-agent skills designed to exploit developer environments and automation workflows.

For enterprises in India, the challenge is sharpened by the country’s role as a major software engineering and global capability centre hub. Bengaluru, Hyderabad, Pune, Chennai and Gurugram host large engineering teams serving banking, retail, telecoms, manufacturing and cloud services. These centres are increasingly responsible not only for maintenance work but also for product development, AI integration and security-sensitive digital platforms.

Regulatory and customer expectations are also tightening. Buyers are asking for software bills of materials, vulnerability disclosure processes, provenance records and proof that build pipelines are protected. CERT-In’s technical guidance on SBOM, QBOM, CBOM, AIBOM and HBOM has emphasised regular updates, vulnerability exploitability exchange documents and staff training around software supply chain visibility.

Security leaders are therefore moving towards stronger controls across development pipelines. These include automated malicious package detection, container image scanning, secrets detection, signed artefacts, dependency pinning, model provenance checks, policy enforcement in CI/CD systems and continuous monitoring of developer environments.

The investment case is becoming harder to ignore. Software supply chain attacks can bypass perimeter defences because they enter through trusted development channels. Once inside, malicious packages can steal credentials, alter builds, move into cloud environments or compromise downstream customers. AI raises the stakes because it can accelerate both legitimate development and attacker experimentation.

The investment is designed to strengthen the chipmaker’s partnerships with foundries, packaging houses, substrate suppliers and server manufacturers that are central to its next generation of AI systems. The programme places Taiwan at the centre of AMD’s effort to scale production of high-performance processors, accelerators and rack-level systems built for increasingly complex AI workloads.

A major focus will be Elevated Fanout Bridge, or EFB, a 2.5D packaging technology intended to improve the speed and efficiency of connections between chip components. AMD plans to use the technology in its sixth-generation EPYC central processing units, codenamed “Venice”, which are being positioned for AI, cloud and high-performance computing deployments.

The move comes as AI infrastructure spending shifts from individual chips towards complete systems that combine CPUs, graphics processors, high-bandwidth memory, networking and software. Advanced packaging has become a critical bottleneck because AI workloads require large volumes of data to move quickly between processors while keeping power consumption and heat within manageable limits.

AMD Chair and Chief Executive Lisa Su said customers were rapidly expanding AI infrastructure to meet rising compute demand. The company is seeking to combine its high-performance computing portfolio with Taiwan’s manufacturing and packaging capabilities to support integrated, rack-scale AI systems.

AMD is working with partners including ASE, SPIL, Powertech Technology, Wiwynn, Wistron, Inventec, Unimicron, AIC, Nan Ya PCB and Kinsus. These companies cover key parts of the supply chain, from advanced packaging and substrates to server assembly and mechanical architecture. Sanmina is also involved in manufacturing support for the company’s Helios platform.

The investment will support both wafer-based and panel-based EFB interconnect development. AMD and Powertech Technology have qualified what they describe as the industry’s first 2.5D panel-based EFB interconnect, a step aimed at improving scalability and production economics for high-volume AI processors.

The technology is expected to help the “Venice” EPYC processors deliver higher interconnect bandwidth and better power efficiency. That matters because data centre operators are increasingly constrained by electricity availability, cooling capacity and rack density, not only by chip performance.

AMD has also begun ramping production of “Venice” CPUs using Taiwan Semiconductor Manufacturing Company’s 2-nanometre process technology in Taiwan. Future production is planned at TSMC’s Arizona facility, extending the supply chain beyond Taiwan while preserving the company’s close reliance on TSMC’s leading-edge manufacturing.

The “Venice” chips will be a central element of AMD’s Helios rack-scale platform, which also includes AMD Instinct MI450X graphics processors, advanced networking and the ROCm open software stack. The platform is scheduled for deployments beginning in the second half of 2026, with AMD describing the opportunity in terms of multi-gigawatt AI infrastructure rollouts.

The strategy puts AMD in a more direct contest with Nvidia, which dominates AI accelerator sales and has built a strong lead through its GPUs, networking, software ecosystem and full-rack systems. AMD’s challenge is not only to deliver competitive silicon but also to prove that it can scale complete AI infrastructure with dependable supply, efficient packaging and broad software support.

AMD’s data centre business has become the company’s main growth engine. First-quarter 2026 data centre revenue reached $5.8 billion, up 57 per cent from a year earlier, driven by demand for EPYC processors and the ramp-up of Instinct GPU shipments. That performance has strengthened investor expectations that AMD can capture a larger share of AI and cloud infrastructure spending.

Taiwan remains critical to that effort because of its concentration of semiconductor expertise. TSMC anchors the foundry side, while packaging, substrate and system-assembly partners provide the manufacturing depth needed to turn chip designs into deployable infrastructure. The concentration also creates geopolitical and supply-chain risks, particularly as governments and companies seek greater resilience across strategic technologies.

This multi-party signing was officiated by Deputy Minister for Territorial and Urban Policy at Ministry of Land, Infrastructure and Transport of the Republic of Korea, Mr Jeong Eui-kyung; the Acting Secretary for Environment and Ecology, Miss Diane Wong; the Director of Electrical and Mechanical Services, Mr Poon Kwok-ying; and the Director-General of Investment Promotion of Invest Hong Kong (InvestHK), Ms Alpha Lau.

Spearheaded by Hyundai Motor Group, the MOU establishes a collaborative framework to build a comprehensive, self-sustaining hydrogen ecosystem in Hong Kong, targeted to be fully operational by the end of 2030. The collaboration will prioritise the development of waste-to-hydrogen technologies to convert landfill gas into clean energy, along with an immediate focus on piloting a liquefied hydrogen refuelling infrastructure. To enable full value chain integration, it also targets the deployment of customised hydrogen fuel cell commercial vehicles, including tour and airport shuttle buses.

Through facilitating public-private partnerships and inter-governmental collaboration, InvestHK is supporting Hyundai Motor Group and its partners to implement go-to-market strategies aligned with the shared vision for hydrogen ecosystem building.

This partnership will also position Hong Kong as a strategic base for Hyundai Motor Group’s hydrogen business expansion across the Asia-Pacific region.

Miss Wong said, “This collaboration marks a significant milestone in developing tangible, on-the-ground hydrogen applications to accelerate the green transition towards carbon neutrality. By combining Korea’s world-class technological capabilities with Hong Kong’s strategic urban context, Hong Kong could serve as an exceptional international demonstration platform for showcasing green and low-carbon technologies. If these cutting-edge innovations could be applied and scaled up successfully here, it will serve as a positive model and provide highly viable options for reference by modern cities worldwide.”

Ms Lau said, “Today’s multi-party signing is both a landmark moment for Hong Kong’s green economy and a clear signal that the city’s hydrogen ecosystem is gaining real traction. Over the past three years, InvestHK has helped leading hydrogen enterprises establish themselves in Hong Kong, several of which have since listed on the Hong Kong Stock Exchange, raising over $2.5 billion in total. For businesses with global green ambitions, Hong Kong is where business growth takes shape.”

Executive Vice President and Head of Energy & Hydrogen Policy Sub-Division at Hyundai Motor Group, Mr Seung Kyu-shin, said, “This MOU was signed as Hyundai Motor Group’s commitment to advancing Hong Kong’s proactive hydrogen policies and driving the acceleration of its hydrogen ecosystem utilising the Group’s hydrogen business capability and experience. Starting with Hong Kong, we look forward to expanding our collaboration and business opportunities across the broader Asia-Pacific hydrogen market.”

Partners entering into this MOU include Hyundai Motor Company and Hyundai Engineering & Construction from Hyundai Motor Group, China Inspection Co Ltd, Chun Wo Bus Services Limited, Chun Wo Construction & Engineering Company Limited, Jiangsu Guofu Hydrogen Energy Equipment Co Ltd, JEA ENG, Templewater Limited, the Hong Kong and China Gas Company Limited, and Veolia Hong Kong Holding Limited.

This multi-party, long-term collaboration is set to establish a robust, end-to-end hydrogen industry chain – spanning production, storage, transportation, refuelling and utilisation.

New energy is vital to Hong Kong’s Climate Action Plan 2050 and the national dual-carbon goals. As set out in the Chief Executive’s 2025 Policy Address, Hong Kong will establish public hydrogen filling facilities on Hong Kong Island and in Kowloon, press ahead with more hydrogen trial projects, and develop the GBA Hydrogen Corridor in collaboration with Guangdong Province. The Hong Kong Special Administrative Region Government is actively advancing hydrogen development through technological innovation, talent cultivation, ecosystem building, and regional co-ordination. To date, over 30 hydrogen trial projects have been greenlit, paving the way not only for decarbonisation targets, but also for unlocking new quality productive forces for green economic growth.
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About InvestHK

Invest Hong Kong (InvestHK) is the investment promotion agency of the Government of the Hong Kong Special Administrative Region (HKSAR).