ByteDance is weighing capital expenditure of as much as $70 billion this year as the TikTok owner accelerates an artificial intelligence push aimed at strengthening its position in China’s intensifying technology contest. The Beijing-based group is discussing one of the largest spending programmes by a private technology company outside the United States, with funds expected to go into data centres, AI chips, networking equipment and model development. […]
The arrangement makes BlockShoals the approved local intermediary under the SEC’s StratBox framework, while Binance supplies technology, security systems, operational support and compliance expertise developed across regulated markets. The sandbox phase is expected to begin in the second half of 2026 and run for at least two years, giving regulators direct oversight of product testing before any wider rollout to users.
The move marks a notable shift in Binance’s strategy in the Philippines. Rather than seeking to restore access through an offshore model, the exchange is now pursuing market participation through a domestic company operating under SEC supervision. BlockShoals, a Philippine-incorporated fintech firm, secured approval under the crypto asset intermediary framework after a multi-year process involving regulatory conditions, compliance checks and investor-protection requirements.
Binance’s online presence in the Philippines was blocked in 2024 after the SEC said the platform had offered investment and trading services without the necessary licence. The regulator had warned the public about the exchange in November 2023, then moved to restrict website access through telecommunications authorities the following year. The action became one of the clearest signals that Manila intended to bring offshore digital-asset platforms under local rules.
That enforcement drive has since widened. The SEC’s crypto-asset service provider rules, issued in 2025, require firms serving Philippine users to register, maintain sufficient capital, observe marketing standards, and meet operational and reporting obligations. The framework is intended to protect retail investors while allowing controlled innovation in a market where crypto use remains high by regional and global standards.
The Philippines ranked ninth in the 2025 global crypto adoption index, reflecting strong activity across retail centralised services and digital-asset platforms. Usage has been driven by a young, mobile-first population, remittance demand, online work, gaming-linked crypto activity and a broad appetite for alternative financial products. That adoption has also heightened regulatory concern over fraud, weak disclosures, market volatility and the risks of foreign platforms serving users without domestic accountability.
Seker, Binance’s head of Asia-Pacific, described the Philippines as one of Southeast Asia’s most dynamic digital economies, saying frameworks such as StratBox create a channel for regulators and industry participants to work together while maintaining user protection and market integrity. The company has presented the BlockShoals partnership as part of a compliance-first approach rather than a conventional market relaunch.
BlockShoals has framed its role around local accountability. A company representative said the partnership was an opportunity to show that global digital-asset platforms and domestic regulatory frameworks could operate constructively together, adding that the firm would work under direct SEC supervision while building a secure platform for users.
The sandbox structure gives the SEC room to monitor how products are configured, how customer onboarding is handled, how risks are disclosed, and how safeguards such as know-your-customer checks, anti-money-laundering controls and transaction monitoring are applied. It also gives Binance a pathway to rebuild trust after a period in which its Philippine operations were defined by access restrictions and licensing concerns.
The Philippine approach mirrors a broader shift across Asia, where regulators are moving away from informal tolerance of offshore crypto activity and towards domestic licensing regimes. Singapore, Hong Kong, Thailand, Indonesia and Japan have tightened rules for exchanges, stablecoin activity, custody, marketing and investor suitability. The result is a more fragmented operating environment for global platforms, with access increasingly dependent on local registration, capital commitments and regulator-facing governance.
For Binance, the Philippine partnership carries strategic value beyond one market. The exchange has spent the past several years seeking to repair relations with regulators after facing scrutiny in multiple jurisdictions. A successful sandbox test in Manila would support its argument that global crypto platforms can adapt to local rules through partnerships, product controls and supervised deployment.
Humanity is consuming resources at a rate the planet cannot sustain, a new peer-reviewed study has warned, placing pressure on food systems, climate stability, biodiversity and living standards as the global population moves deeper into ecological overshoot. Researchers led by Corey J. A. Bradshaw of Flinders University found that the world’s population has already surpassed Earth’s sustainable carrying capacity, with today’s 8.3 billion people well above the […]
Dubai and Abu Dhabi’s office and retail property markets remained resilient in the first quarter of 2026, as tight supply, steady occupier demand and flexible leasing strategies helped prime assets withstand regional uncertainty and softer tourism-linked spending. JLL’s Real Estate Market Dynamics report showed that office rents across both emirates continued to rise at double-digit annual rates, led by constrained availability in prime districts and a sustained […]
Arabian Post Staff -Dubai Washington is pressing ahead with claims of progress toward a peace deal with Tehran, even as fresh US strikes on targets in southern Iran and renewed uncertainty over the Strait of Hormuz exposed the fragility of efforts to end a war approaching its third month. The latest flare-up came after US forces struck what they described as missile launch sites and mine-laying boats, […]
The summit signaled a clear “cross‑border restructuring.” With computing power collaboration entering a new phase, AI competition is expanding from single‑model parameters to industrial scenarios like math, life sciences, financial risk control, and complex macro decisions. Chow Kit Hui argues that extensive competition based on capital and model scale is shifting to refined competition—the future AI ecosystem hinges on integrating technology, data, and scenarios.
At the summit, Chow Kit Hui and NVIDIA launched a new strategic collaboration on algorithm optimization, AI training architecture, vertical data assets, and decision‑model integration, aiming to boost computing efficiency and drive deployment of industry‑level AI agents and autonomous reasoning in complex scenarios.
Chow Kit Hui unveiled his strategically positioned AI fund, AlgoVision AI Growth Partners Foundation. Driven by computing power, capital, and application scenarios, it backs upstream tech breakthroughs and high-value downstream applications, bridging AI research with industrial use. From academic discourse to computing coordination, the summit revealed a new competitive landscape: core advantage now lies in integrating technology, data, scenarios, capital, and resources—not the capability of a single model. With data-driven rationality and risk control, Chow injected lasting long-termism into global AI deployment.
Hashtag: #KitHuiGrowthFinancialAcademy
The issuer is solely responsible for the content of this announcement.
Kit Hui Growth Financial Academy was founded by Chow Kit Hui. Chow Kit Hui has long focused on global asset allocation, corporate mergers and acquisitions, private equity, derivatives, risk management, macroeconomic research, and financial valuation modeling. The academy does not center on short-term market predictions or teaching investment “tricks.” Instead, it helps learners establish a rational, long-term, and structured path to financial understanding. The academy emphasizes structured comprehension of market mechanisms, risk-prioritized decision-making, and independent judgment.
Official website: https://www.kithuiacademy.com/
Arabian Post Staff -Dubai ROSHN Group has signed a new agreement with Tatweer Buildings Company to design, build and supervise a public educational facility at WAREFA, its integrated residential community in East Riyadh, strengthening the role of schools as core infrastructure in Saudi Arabia’s expanding master-planned neighbourhoods. The agreement places Tatweer Buildings Company in charge of managing and executing the project through all phases, while ROSHN will […]
South Africa’s diesel shock has turned a distant Middle East conflict into a domestic economic threat, exposing how sharply the country’s transport, mining, farming and power systems now depend on imported refined fuel. The Iran war and disruption around the Strait of Hormuz have pushed global energy markets into a new phase of volatility, but South Africa’s vulnerability is not driven by crude oil alone. The deeper […]
Forty high-performing schoolgirls from underprivileged communities in Ghana will receive annual scholarships under the newly launched Educating Linda programme, a joint initiative of Merck Foundation, Ghana’s First Lady Lordina Dramani Mahama and the Lordina Foundation aimed at keeping girls in classrooms until graduation. The programme, formally launched in Accra, is designed to remove financial barriers that often force girls out of school, including tuition costs, uniforms, stationery […]
Microsoft has opened a clearer path for Windows 11 users and administrators to remove Copilot, marking a notable shift in its handling of artificial intelligence features that have become increasingly visible across the operating system. The change means Copilot can be removed like a conventional app on many devices, while IT administrators managing business PCs now have policy tools to uninstall or prevent the Microsoft Copilot app […]
Global enterprise AI expenditure is expected to reach about $940 billion in 2026 and climb to roughly $2.1 trillion by 2029, reflecting a shift from experimental deployments to large-scale use across manufacturing, finance, logistics, health care, energy and public services. China is emerging as one of the fastest-expanding markets within that cycle, helped by heavy infrastructure spending, state-backed industrial policy and a corporate race to build domestic alternatives to foreign chips, models and cloud platforms.
The acceleration is no longer confined to model development. China’s AI buildout is moving across the full technology stack, from data centres and accelerators to enterprise software, robotics and agentic systems capable of handling complex workflow tasks. The first phase of the investment wave was dominated by computing power, foundational models and large infrastructure projects. The next phase is being shaped by applied AI, intelligent services and automation across production lines, offices and consumer platforms.
That transition is putting pressure on global rivals. US technology groups still lead in advanced chips, frontier models and hyperscale cloud capacity, but China’s market has advantages in deployment speed, manufacturing depth and policy coordination. Companies including Alibaba, Tencent, Baidu, Huawei and ByteDance are expanding AI services while also trying to reduce dependence on restricted US semiconductor supplies. Alibaba has unveiled a new AI chip through its T-Head unit and is directing tens of billions of dollars into cloud and AI infrastructure over several years. Huawei’s Ascend processors have become central to China’s domestic accelerator strategy as export controls limit access to top-tier Nvidia products.
Infrastructure remains the foundation of the race. Worldwide AI infrastructure spending is on course to exceed $1 trillion by 2029, with accelerated servers accounting for the overwhelming share. China remains the second-largest AI infrastructure market after the US, even though export restrictions have created supply constraints for high-end accelerators. Those restrictions have encouraged domestic chip design, local server ecosystems and more efficient deployment models for inference, where many commercial AI applications run after models have been trained.
China’s data centre expansion is also moving into more specialised formats. AI workloads demand dense computing power, stable electricity supply and advanced cooling, all of which are raising costs and straining grids. Projects near Shanghai and other technology hubs are testing alternative energy and cooling systems, including offshore and renewable-powered facilities. These efforts reflect a broader attempt to manage the energy burden of AI while supporting national ambitions in cloud services, industrial software and smart manufacturing.
Robotics is becoming a central pillar of the spending wave. China already has the world’s largest industrial robot base and is pushing into embodied intelligence, where AI systems are integrated into machines that operate in factories, warehouses, homes and public spaces. Forecasts for China’s robotics market point to rapid expansion over the next five years, with demand coming from electric vehicles, electronics, logistics and elder care. The combination of AI models, sensors, batteries and manufacturing scale gives domestic firms a route to compete internationally beyond software alone.
Policy support is reinforcing corporate investment. Beijing’s “AI Plus” strategy, issued in 2025, aims to embed artificial intelligence across the economy by expanding access to data, compute and talent while promoting open-source ecosystems and industrial adoption. Local governments have added funding programmes, innovation parks and procurement support, creating competition among cities such as Beijing, Shanghai, Shenzhen and Hangzhou. That model can accelerate deployment, though it also raises the risk of duplicated capacity, uneven standards and projects driven more by subsidy incentives than commercial demand.
The competitive picture remains mixed. China leads in AI publication volume, citations, patent output and industrial robot installations, while the US continues to produce more frontier models and higher-impact patents. The performance gap between leading US and Chinese models has narrowed, aided by open-source releases and engineering efficiency from Chinese labs. DeepSeek’s breakthrough earlier in the cycle demonstrated that capable systems could be produced with fewer resources than previously assumed, intensifying debate over whether raw spending alone will determine leadership.
Arabian Post Staff -Dubai Etihad Rail has unveiled the official uniforms for its passenger-facing teams, offering the clearest sign yet that preparations for the UAE’s first national passenger rail service are moving into their final operational phase. The new look, built around a contemporary grey palette with bold red accents, will be worn by onboard hosts, station staff and other customer-facing employees across the passenger network. The […]
The Securities and Exchange Board of India is examining whether companies that list only debt securities should continue to face disclosure and compliance obligations similar to those imposed on equity-listed companies. The review is part of a wider effort to deepen the corporate bond market, where heavy reliance on private placements, limited retail participation and concentration among highly rated issuers have kept market breadth below policy ambitions.
Chairman Tuhin Kanta Pandey, who took charge of the regulator in March 2025, has signalled that the next phase of reform will focus on making the debt market more usable for issuers and investors without weakening safeguards. A pilot framework for tokenising corporate bonds is expected to be launched within six to nine months, testing whether distributed-ledger technology can improve settlement speed, servicing, traceability and operational efficiency.
The proposed easing would be especially relevant for entities that raise money only through listed non-convertible securities and do not have listed shares. Such issuers have argued that several provisions under the Listing Obligations and Disclosure Requirements framework were designed primarily for equity-market governance, where public shareholders carry voting and ownership rights. Debt investors, by contrast, are focused mainly on credit quality, repayment capacity, covenant compliance and timely interest payments.
The regulatory challenge is to separate investor-useful disclosure from procedural duplication. Quarterly financials, credit-rating updates, default alerts, asset-cover statements, related-party exposure and material event reporting remain central to creditor protection. Requirements linked more closely to equity ownership, board-shareholder dynamics and public float may be reviewed where they impose costs disproportionate to the risks faced by bondholders.
India’s corporate bond market has expanded sharply but remains structurally narrow. Net outstanding corporate bonds rose from ₹17.5 trillion in FY2014-15 to about ₹53.6 trillion in FY2024-25, with fresh issuances touching ₹9.9 trillion during 2024-25. The market accounts for roughly 15-16 per cent of GDP, far below deeper Asian and developed markets, and is still dominated by highly rated financial and public-sector issuers.
Private placements remain the preferred route for large borrowers, while public bond issues account for only a small share of overall issuance. That pattern has kept institutional investors at the centre of the market and limited participation by individuals, smaller corporates and lower-rated issuers. For policymakers, the issue is not simply market size but market diversity, liquidity and the ability of bonds to finance infrastructure, housing, manufacturing and growth-stage companies at competitive rates.
Tokenisation is being positioned as a market-infrastructure experiment rather than a replacement for existing bond-market systems. Under such a model, a bond can be represented as a digital token on a permissioned ledger, with ownership transfers, coupon payments and redemption records updated through automated processes. A well-designed pilot could reduce reconciliation gaps, improve audit trails and allow faster post-trade processing while preserving regulatory oversight.
Global fixed-income markets have been exploring tokenisation for similar reasons. Automation through smart contracts can simplify issuance, settlement and corporate actions, while better record keeping can lower operational risk. The benefits, however, depend on legal clarity, interoperability with depositories and clearing systems, cyber-security standards and clear rules on investor rights if technology vendors, wallets or ledger nodes fail.
Sebi’s review also comes amid wider changes in India’s debt-market architecture. Online bond platforms have been brought under regulation, the request-for-quote platform has gained traction, and policymakers are looking at ways to widen access to international debt products through regulated channels. Municipal bonds are also drawing greater attention as cities seek market funding for infrastructure, adding to the broader shift from bank-led financing towards market-based debt.
Investor protection will remain the central test for any relaxation. Lighter disclosure rules could encourage more issuers to list debt securities, but weaker transparency would raise borrowing costs and damage confidence if defaults rise or credit risks are obscured. The most likely outcome is a calibrated framework that retains credit-critical reporting while reducing requirements that do not materially affect bondholder decisions.
A targeted cyber-espionage campaign has struck China’s higher education sector, using deceptive PDF-style shortcut files to install Cobalt Strike beacons on victim machines and open a path for remote control. The operation, labelled Dragon Whistle, has focused on Changzhou University and related academic users by exploiting a familiar administrative pressure point: compulsory student fitness testing tied to the 2026 National Student Physical Fitness and Health Standards. The […]
The aircraft, operating the Muscat–Kannur sector on May 15, was preparing for a night departure from Muscat International Airport when it became misaligned during take-off. Instead of tracking along the runway centreline, the aircraft moved along the right-side edge-light area and hit multiple lights before the crew rejected the take-off. The pilot acted after hearing a loud bang and receiving a cockpit alert.
No injuries were reported among passengers or crew. The aircraft stopped on the runway and was disabled after the impact, prompting evacuation and ground response procedures. The Boeing 737-800 has remained grounded in Muscat pending technical inspection, repairs and regulatory clearance.
The occurrence has been classified as an accident by Oman’s Air Accidents Investigation Sector, which has opened a probe into the sequence of events, crew actions, runway conditions, lighting environment and air traffic control communication. The investigation is expected to examine why the aircraft was not aligned with the runway centreline before take-off clearance was acted upon.
Flight IX-712 serves an important expatriate corridor between Oman and Kerala’s Kannur district, which has a large base of workers and families linked to the Gulf. The route is part of Air India Express’s wider West Asia network, where the airline operates high-frequency services catering mainly to price-sensitive passengers, migrant workers and family traffic.
The aircraft involved was a Boeing 737-800, a narrow-body model widely used for short- and medium-haul operations. The type is part of Air India Express’s core fleet and is configured for high-density international services. The 737-800 is regarded as a mature aircraft platform, but runway alignment events remain serious because they can expose aircraft to structural damage, tyre failure, hydraulic loss and runway obstruction risks during the most critical phase of flight.
Runway edge lights are designed to mark the lateral boundary of a runway, while centreline guidance helps crews maintain the correct track during take-off and landing, especially at night or in reduced visibility. Misidentification of lighting cues can become more hazardous during night operations, when visual references are narrower and cockpit workload is high. Investigators will assess whether lighting layout, crew situational awareness, taxi routing, clearance procedures or human factors contributed to the incident.
The hydraulic leak is a key technical concern because aircraft hydraulic systems power essential functions including flight controls, braking, landing gear and steering. A flat tyre during an aborted take-off also raises operational risk, as the aircraft must stop safely while managing heat, braking load and directional control. The crew’s decision to reject take-off after the bang and warning indication prevented the aircraft from becoming airborne with possible system damage.
The incident comes at a time of intensified scrutiny of airline operational discipline, runway safety and crew resource management across global aviation. Regulators have placed growing emphasis on runway incursion prevention, proper line-up procedures, cockpit cross-checking and visual confirmation before take-off. Airports and airlines are also under pressure to strengthen safety reporting systems so that operational errors are identified and corrected before they lead to more serious outcomes.
Air India Express, now operating under the Tata group’s aviation restructuring plan, has been expanding and consolidating its network as part of a broader integration of low-cost operations. The airline has a substantial presence on Gulf routes, where competition is intense and aircraft utilisation remains high. Any grounding of a narrow-body aircraft can disrupt schedules, especially on tightly planned international rotations.
Kannur International Airport has depended heavily on Gulf connectivity since its opening, with Oman, the UAE, Saudi Arabia, Qatar and Bahrain forming core markets for the airport’s passenger flows. Services from Muscat are particularly significant for northern Kerala travellers, who often prefer direct flights over longer road journeys to airports in Kozhikode, Kochi or Mangaluru.
PuTTY users have been urged to move to version 0.84 after the maintainers fixed three low-severity security flaws affecting SSH key exchange, NIST ECDSA signature verification, and Telnet or Rlogin session prompt handling. The update, released on 22 May 2026, addresses defects that could allow a malicious server or a man-in-the-middle attacker to crash a PuTTY session or mislead a user during older, insecure remote-login workflows. The […]
Washington has moved to fold Middle East normalisation into its Iran diplomacy, with President Donald Trump urging key Muslim-majority states to join the Abraham Accords as negotiations with Tehran enter a delicate phase. Trump used a Truth Social post to say talks with the Islamic Republic of Iran were “proceeding nicely”, while warning that failure to reach what he called a “great deal” could send the parties […]
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.
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.
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.
The window also highlighted the broader support ecosystem available to SMEs, including a broader ecosystem of over 16,000 solution providers globally via IMDA’s Open Innovation Platform, alongside the SME AI Playbook which offers practical use cases, success stories from real businesses, FAQs and an AI readiness diagnostic tool.
Economy-wide AI adoption – the kind that drives meaningful productivity gains across the full breadth of Singapore’s business community – only happens if SMEs are part of the story. The DBS SME AI Playbook is a direct response to that reality: a practical, accessible entry point into AI adoption calibrated to the real constraints and real ambitions of smaller businesses.
The collaboration between DBS and KPMG reflects how Singapore’s AI ecosystem works at its best: financial institutions, professional services firms, government platforms and businesses working together to make trusted AI adoption accessible to every part of the economy, not just its largest players.
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KPMG in Singapore is part of a global organization of independent professional services firms providing Audit, Tax and Advisory services. We operate in 138 countries and territories with more than 276,000 partners and employees working in member firms around the world. Each KPMG firm is a legally distinct and separate entity and describes itself as such. KPMG International Limited is a private English company limited by guarantee. KPMG International Limited and its related entities do not provide services to clients.
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