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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

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.

Recent Google search trends in Thailand show continued growth in interest for both asset classes. Gold trading-related searches such as “XAUUSD today” have consistently generated between 1,000 and 10,000 monthly searches over the past year, while cryptocurrency-related keywords including “crypto” have maintained similarly strong search volumes.

The trend is also reflected in internal traffic data from BrokersThai.com. Pages related to Forex brokers for gold trading generated more than 5,000 impressions over the last year, highlighting continued interest from Thai traders seeking reliable broker comparisons and trading cost information.

The data also reveals that cryptocurrencies like Bitcoin are no longer seen as just tools for quick gambling. Instead, users search for risk management, such as how to handle price drops and volatility, spike every time the stock market experiences volatility. This proves that traders are carefully weighing crypto risks against the steady safety of gold.

Justin Grossbard, CEO of BrokersThai.com, commented: “Thai traders are now interested in trading multiple assets, especially gold and Bitcoin, while paying more attention to trading costs and broker transparency. Many traders are carefully comparing spreads and execution speeds to reduce unnecessary trading costs as much as possible.”

The findings indicate that Thai retail traders are adapting to uncertain market conditions by conducting deeper research before making investment decisions. Rather than choosing between gold or Bitcoin, many traders are now using both together — relying on gold to help preserve capital while viewing Bitcoin as a long-term growth opportunity.

For broker comparisons, visit: https://www.brokersthai.com
Hashtag: #BrokersThai

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The 2026 Sunday Roast Guest Chef Series runs across selected Sundays from February to October, with further dates expected for November and December. Priced at HK$898 per guest, plus a 10 per cent service charge, the programme gives each participating restaurant one Sunday to reinterpret the classic British roast through its own cuisine, while retaining the familiar three-course structure of starter, roast or seafood main, and dessert.

The format reflects a wider shift in Hong Kong’s premium dining scene, where luxury hotels are moving beyond standard brunch buffets and using chef-led collaborations to attract diners who want novelty, scarcity and recognised culinary talent. For Lobster Bar & Grill, long associated with seafood, grills, cocktails and live jazz, the series also positions brunch as a curated dining event rather than a routine weekend offering.

The 2026 line-up began with NOI on 8 February, bringing contemporary Italian cooking shaped by Chef Paulo Airaudo’s wider culinary approach and Hong Kong-based Chef Luigi Troiano’s execution. It continued on 15 March with 22 Ships, known for modern Spanish flavours under Chef Antonio Oviedo, and on 12 April with Yong Fu Hong Kong, whose Ningbo seafood cooking added a refined Chinese coastal identity to the Sunday roast template.

The next phase brings Neighborhood on 31 May, Leela on 28 June and Cristal Room by Anne-Sophie Pic on 19 July. Neighborhood, led by Chef David Lai, enters the series with strong recognition from both Michelin and Asia’s 50 Best Restaurants, where it ranked No. 24 in the 2026 list. Its reputation rests on market-led European bistro cooking, generous sharing dishes and a style that combines technical control with an understated dining room culture.

Leela, led by Chef Manav Tuli, adds a modern interpretation of regional cooking from India, using refined technique, spice layering and tandoor-led elements. Its participation broadens the series beyond European and Chinese traditions, giving the roast format a more expansive culinary identity at a time when Hong Kong diners are showing stronger interest in regional specificity and chef-driven storytelling.

Cristal Room by Anne-Sophie Pic brings the strongest fine-dining profile in the May-to-July phase. The Landmark restaurant, guided in Hong Kong by Chef Marc Mantovani, earned two Michelin stars in the 2026 Hong Kong and Macau guide. Its contribution is expected to bring a more composed French approach to the format, with emphasis on precision, balance and luxury ingredients.

Lobster Bar & Grill’s regular Sunday roast brunch already leans towards abundance, with appetisers such as lobster bisque, smoked salmon and steak tartare, followed by individually plated roast or seafood choices. Signature sides include duck-fat roasted potatoes and honey-glazed carrots, while desserts include banoffee pie, triple chocolate mud pie and seasonal creations. The guest-chef model keeps those anchors intact while allowing each collaborator to alter the flavour profile.

Executive Sous Chef Cary Docherty remains central to the concept. His role is not merely to host outside chefs, but to co-create menus that fit the kitchen’s seafood-and-grill identity while allowing each restaurant’s style to remain visible. That balance is crucial: too much hotel polish could dilute the individuality of the guest chefs, while too much experimentation could alienate diners expecting the comfort of Sunday roast.

The commercial logic is clear. Hong Kong’s dining market remains crowded, and premium hotel restaurants face intense competition from independent restaurants, private clubs and destination bars. A one-day-only brunch creates urgency, encourages repeat visits and lets diners access high-profile kitchens in a less formal setting than full tasting menus. For visiting chefs and independent restaurants, the collaboration offers exposure to a hotel audience with strong spending power.

Located on Level 6 of Pacific Place on Supreme Court Road in Central, Lobster Bar & Grill benefits from a business-district address and the broader Island Shangri-La dining ecosystem. Its Sunday and public holiday brunch service runs from 11.45am to 3.30pm, with last orders at 2.30pm, giving the collaboration format a defined weekend window rather than an open-ended promotional run.

Recognition reflects TDCX’s evolution into a global firm helping clients navigate digital and AI transformation with a combination of human expertise, intelligent technology, and operational precision

Hashtag: #TDCX #OA500 #CX #Outsourcing #EnableTheFuture

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About TDCX

For more information, please visit www.tdcx.com.

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.

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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.