May 31st, 2026

Asia faces ‘costly paradox’ over divergent AI rules in US and EU

Asian technology firms are facing a “costly paradox” as they try to navigate an increasingly uneven global AI rule book, with divergent compliance requirements in the European Union and the United States threatening to blunt their competitive edge.

Analysts say the challenge is acute for Asian companies. While the EU has a single, comprehensive and legally binding artificial intelligence framework based on the landmark EU AI Act, US technology-related laws are decentralised at the state level.

For firms building AI systems, compliance with regulations is essential to earning consumer trust, avoiding potentially crippling penalties and ensuring they can continue operating in two of the world’s largest consumer markets.

Asian firms embedded in the global AI ecosystem face dual costs to comply with different EU and US rules, according to Martyna Sucharzewska, a senior technology analyst at BMI, a unit of Fitch Solutions.

“Organisations operating across both jurisdictions must build parallel compliance architectures, and the cost of doing so is not trivial,” she said.

The implications are significant because Asian tech firms play critical roles in the AI space, ranging from semiconductor and memory chips makers from Taiwan and South Korea to cloud infrastructure developers.

Asian countries were aligning their AI rules with the EU’s governance-led model or the American innovation-based approach or adopting elements of both, Sucharzewska said.

Singapore followed a voluntary and principles-based approach closer to the US model to build its governance framework for agentic AI, or autonomous AI, while South Korea’s AI Basic Act was aligned with the EU legal framework, she said.

This fragmentation in AI governance has arisen due to the absence of a global consensus on the technology, a divide that is accelerating, according to Sucharzewska.

A Fitch report released last week on global AI regulation says the Gulf Cooperation Council – comprising Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and the United Arab Emirates – follows a light-touch governance model and has emerged as an alternative to the EU’s “prescriptive approach”.

While the Middle East was increasingly being seen as an important region for AI adoption, the biggest challenge for Asian companies was meeting the “dual compliance” requirements of the EU and the US and different market demands, said Anndy Lian, a Singapore-based adviser to governments on blockchain and information technology.

Consequently, these companies had to bear the burden of a “regulatory fragmentation tax” and a “costly paradox”, Lian said.

“This friction splits Asian research and development down the middle. Instead of focusing capital on core model breakthroughs, Asian start-ups must bleed resources into engineering hyper-localised” solutions for compliance, he added.

Raj Kapoor, president of the India Blockchain Alliance, said that navigating divergent rule books was imposing a disproportionate burden on Asian companies, many of which were creators of AI-enabled products as well as major consumers of Western AI technology.

Lian said that apart from hurting competitiveness, “the danger is that Asian AI plans will become structurally fractured, building Balkanised versions of the same technology to satisfy Western regulators”.

According to Lian, some Asian countries are leaning towards the US approach. Prioritising “ironclad guardrails” through regulations, such as in the EU, over developing technological capability was “an expensive luxury they cannot afford”, he said.

“The core of the dilemma is that Asia relies heavily on the US for bleeding-edge AI infrastructure, yet looks to Europe as a massive consumer market for its digitised products and services,” Lian said.

The implications of regulatory compliance would have a broader economic impact beyond technology, said Raj Kapoor, president of the India Blockchain Alliance.

The World Economic Forum (WEF) said in November that the next phase of Southeast Asia’s digital economy would be powered by AI across all sectors.

“Alongside physical infrastructure, robust AI regulation and governance frameworks are paramount. These policies must strike a careful balance: encouraging innovation while establishing clear ethical guidelines to build and maintain the necessary consumer trust,” the WEF said.

According to a McKinsey report released in February, 46 per cent of Southeast Asian businesses have moved beyond the pilot phase of AI adoption, surpassing the global average of 35 per cent.

The choice of regional countries in adopting the US or the EU AI regulatory framework would ultimately reflect their geopolitical stance within the global tech nexus.

“For Asian governments, selecting a regulatory framework is rapidly evolving from a technical policy decision into a defining geopolitical statement, one that may determine not only economic opportunity but also their place in the architecture of the future digital world,” Kapoor said.

Source: https://www.scmp.com/week-asia/economics/article/3355327/asia-faces-costly-paradox-over-divergent-ai-rules-us-and-eu?module=perpetual_scroll_0&pgtype=article

Anndy Lian

Anndy Lian is an early blockchain adopter and experienced serial entrepreneur who is known for his work in the government sector. He is a best selling book author- “NFT: From Zero to Hero” and “Blockchain Revolution 2030”.

Currently, he is appointed as the Chief Digital Advisor at Mongolia Productivity Organization, championing national digitization. Prior to his current appointments, he was the Chairman of BigONE Exchange, a global top 30 ranked crypto spot exchange and was also the Advisory Board Member for Hyundai DAC, the blockchain arm of South Korea’s largest car manufacturer Hyundai Motor Group. Lian played a pivotal role as the Blockchain Advisor for Asian Productivity Organisation (APO), an intergovernmental organization committed to improving productivity in the Asia-Pacific region.

An avid supporter of incubating start-ups, Anndy has also been a private investor for the past eight years. With a growth investment mindset, Anndy strategically demonstrates this in the companies he chooses to be involved with. He believes that what he is doing through blockchain technology currently will revolutionise and redefine traditional businesses. He also believes that the blockchain industry has to be “redecentralised”.

www.anndy.com

j j j

May 30th, 2026

The $500 Trillion AI Bet Depends on Energy, Infrastructure, and Policy, Not Just Code

Jensen Huang’s recent remarks on AI’s economic trajectory are as bold as they are inevitable. “There’s a belief that the world’s GDP is somehow limited at a hundred trillion dollars,” he said. “AI is going to cause that hundred trillion dollars to become two hundred, three hundred, five hundred trillion… Everybody’s jobs will change.”

The pitch is seductive, and on the micro level, largely correct. AI will not simply replace jobs; it will strip away friction. Workers will spend less time wrangling spreadsheets or typing prompts and more time orchestrating, deciding, and creating. Productivity will surge. Those who fail to integrate AI will lose to those who do.

But macroeconomics rarely bends to technological optimism. The real question is not whether AI expands the economic pie. It is how that expansion prices out, and who captures the gains.

Pressure-testing Huang’s $500 trillion vision reveals two sharply different futures. One to structural deflation and abundance. The other leads to inflationary distortion.

Scenario A: The Nominal Bubble

If the $500 trillion figure is driven more by financial engineering than physical output, the result could be an inflationary shock.

A booming AI sector would generate enormous paper wealth across companies such as NVIDIA, Microsoft, and OpenAI. Investors and founders would recycle those gains into real-world assets: housing, energy, food, and commodities. That is classic demand-pull inflation, amplified by unprecedented .

At the same time, AI’s digital promise collides with physical bottlenecks. Training models requires vast amounts of copper, semiconductors, data centers, and electricity. Competition for those constrained resources pushes up costs across the broader economy while non-AI sectors struggle to keep pace.

In this scenario, the $500 trillion economy is not real growth. It is a valuation bubble chasing finite real-world supply.

Scenario B: The Deflationary Engine

The counterargument is that AI could create genuine GDP expansion while driving structural deflation.

Jensen Huang, Founder and CEO of Nvidia, Source: Wikipedia

GDP is ultimately price multiplied by quantity. If AI removes the constraints of human labor and intelligence, the quantity of goods and services could scale dramatically even as prices fall.

When AI automates coding, legal work, diagnostics, research, and eventually physical production through robotics and automated manufacturing, the marginal cost of creating products and services collapses. Software, logistics, energy optimization, and even manufacturing become radically cheaper.

If output expands severalfold while costs decline, the economy grows in real terms. Living costs fall, purchasing power rises, and abundance—not inflation—defines the outcome.

This is the future Huang is implicitly betting on. And mathematically, it is possible.

The Dangerous Transition Gap

The real risk lies between those two scenarios.

Markets may price in AI-driven abundance long before the physical infrastructure exists to support it. Building advanced energy grids, semiconductor fabs, robotics supply chains, and transmission networks could take 10 to 15 years.

That creates a dangerous mismatch. Capital floods into AI today, asset prices surge, and resource competition intensifies before supply-side abundance arrives. Energy, housing, metals, and essential goods could all become more expensive during the transition.

In effect, the path to abundance may first pass through inflation.

Central banks would face an impossible balancing act between suppressing inflation and supporting growth. Workers in disrupted industries could face displacement before new AI-augmented roles scale fast enough to absorb them. Social and political friction could undermine the productivity boom AI promises.

Abundance is not automatic. It has to be engineered.

The Real Question

Huang is probably right that GDP is not capped at $100 trillion. He is also right that AI will fundamentally change how people work.

But whether the world reaches $500 trillion through abundance or distortion will depend less on algorithms and more on institutions.

The outcome will hinge on energy policy, industrial capacity, monetary discipline, and labor adaptation. Technology creates productive capacity. Governments, central banks, and markets determine whether that capacity translates into stability.

AI will reshape the global economy. The real question is whether society can manage the transition as effectively as it trains the models powering it.

Source: https://www.financemagnates.com/institutional-forex/the-500-trillion-ai-bet-depends-on-energy-infrastructure-and-policy-not-just-code/

Anndy Lian

www.anndy.com

j j j

May 26th, 2026

Are institutions ditching Bitcoin for AI-themed products?

Bitcoin sits at US$76,638.55, and I still see a range play. The price action reflects a market digesting competing forces rather than breaking into a new trend. Institutional capital is not fleeing digital assets but rotating with purpose. Money is moving out of mainstream Bitcoin and Ether ETFs and into AI-themed funds and select altcoin products. This shift tells a nuanced story about risk appetite, narrative momentum, and the search for growth in a macro environment that favours selectivity over broad exposure.

Recent flow data makes this rotation unmistakable. Between 18 and 22 May, US spot Bitcoin ETFs recorded about US$1.26 billion in net outflows. Ether ETFs lost roughly US$216 million over the same window. At the same time, Solana, XRP, and Hyperliquid HYPE products attracted inflows of about US$15.6 million, US$22 million, and US$72.4 million, respectively. Reports show total BTC and ETH ETF redemptions reached nearly US$2.7 billion over two weeks.

These numbers do not signal a retreat from crypto. They show capital reallocating within the asset class toward ecosystems with idiosyncratic growth drivers, such as network adoption and derivatives activity. The flagship funds remain massive. CMC aggregate data still puts Bitcoin ETF assets at around US$106.22 billion and Ether ETF assets at nearly US$13.8 billion. The system is large but is currently experiencing a net trickle-out from the core holdings.

Outside crypto, the AI infrastructure trade commands intense attention. An AI-linked memory chip ETF, DRAM, gathered more than US$6.5 billion of assets within 27 trading sessions after its April launch. It surpassed US$10 billion within 30 sessions. That pace makes it one of the fastest-growing and most traded ETFs in the United States. Institutions express AI conviction through familiar equity wrappers rather than more volatile coins. Hedge funds have ramped up their exposure to tech and AI stocks, reinforcing this preference. The narrative around chips and model-training infrastructure offers a compelling growth story that aligns with current macro expectations. Managers appear to use crypto price rebounds to trim exposure to rate-sensitive benchmark assets such as BTC and ETH while keeping risk on the table through altcoins and AI themes.

Macro expectations have shifted toward higher-for-longer interest rates. This backdrop shapes how institutions position across digital assets and equities. When rates stay elevated, investors favour assets with clear near-term catalysts and visible adoption curves. Within crypto, products tied to more sustainable ecosystems fit that bill. They offer exposure to specific network effects and derivatives activity that can drive outsized returns even when large caps face headwinds. The rotation reflects enthusiasm for growth narratives in AI infrastructure and higher beta altcoins, not a total exit from digital assets. Risk appetite has not vanished. It is being reallocated toward perceived higher growth and more targeted narratives, both inside and outside crypto.

Global markets provide important context for this flow dynamic. On Tuesday, May 26, 2026, equities worldwide pare early gains as Middle East geopolitical developments compete with optimism over an interim diplomatic breakthrough. US equity-index futures trade higher by 0.6 per cent, with S&P 500 futures up one per cent and Nasdaq 100 futures up 1.4 per cent compared to Friday’s close. This follows an eight-week consecutive winning streak for the S&P 500. Investors return from the Memorial Day holiday, focusing on upcoming PCE inflation and GDP figures.

In the Asia-Pacific, benchmarks show mixed performance. Japan’s Nikkei 225 surged 2.87 per cent to 65,158.19 points, driven by technology and component manufacturers. Australia’s S&P/ASX 200 slid 0.4 per cent to 8,656.6, weighed down by losses in large banks and real estate players. Hong Kong’s Hang Seng gained 0.86 per cent, tracking recovery in local property markets and optimism around Chinese tech listings. These moves matter because crypto increasingly correlates with traditional risk assets. When tech equities rally, crypto often follows. When macro uncertainty rises, correlations can tighten further.

Energy and commodities add another layer. Brent Crude trades around US$97.54 to US$98.00 per barrel after volatile swings tied to US-Iran diplomatic developments. WTI Crude hovers near US$91.00 per barrel. Spot gold rose 0.75 per cent to US$4,550.18 per ounce amid lingering safe-haven demand. Iron Ore edged down slightly by 0.11 per cent to US$109.67 per tonne.

The US Dollar Index prints a touch stronger at 99.34 against its Group-of-10 peers. Cash trading of US Treasuries resumed with a minor rally, leaving the 10-year Treasury yield at 4.55 per cent as investors await core inflation indicators. These variables influence institutional positioning across all risk assets. A stronger dollar and sticky yields can pressure rate-sensitive holdings. Geopolitical tensions can boost safe havens while creating volatility that benefits high-beta names.

For Bitcoin and Ethereum, sustained ETF outflows could cap upside or increase sensitivity to negative macro surprises. These vehicles remain a primary channel for institutional demand. Persistent redemptions signal caution among large allocators. The DRAM ETF’s explosive growth demonstrates how powerful the AI infrastructure narrative can be when wrapped in a familiar vehicle. Concentration risk rises if narratives fade or liquidity reverses. Investors paying for growth today expect delivery tomorrow.

Practical signals deserve close monitoring. Watch daily net flows into BTC, ETH, and major altcoin ETFs. Track relative performance between crypto ETFs and AI equity ETFs. Observe changes in the probability of rate cuts or hikes implied by Treasury yields and Fed funds futures. If macro conditions ease and AI enthusiasm broadens back into digital assets, flows could rotate again, potentially back toward BTC and ETH. The interplay between these factors will determine whether the current shift becomes a lasting regime change or a temporary tactical adjustment.

Breakouts require either a macro catalyst that reignites broad institutional demand or a narrative breakthrough that pulls capital back into the flagship assets. Until then, selective exposure and careful flow monitoring offer the clearest path forward.

Source:

https://e27.co/are-institutions-ditching-bitcoin-for-ai-themed-products-20260526/