Is the EU Leading the Charge or Losing the Race in Regulating AI?

Is the EU Leading the Charge or Losing the Race in Regulating AI?

As I sit down to reflect on the European Union’s emerging AI regulatory framework, I can’t help but feel a mix of admiration and unease. The EU is charting a bold course, aiming to classify AI tools based on their potential risks and impose stricter rules on high-risk systems like self-driving cars and medical technologies, while giving more leeway to lower-risk applications like internal chatbots.

As someone who has spent years covering the intersection of technology and policy, I’ve seen the transformative power of innovation and the chaos that can ensue when it’s left unchecked. The EU’s approach feels like a necessary step toward ensuring AI remains trustworthy and aligned with human values, but I worry it might come at the cost of stifling the very creativity it seeks to protect. This isn’t just a European issue—it’s a global one, and the world is watching closely.

The EU’s AI Act, which took effect in August 2024, is a groundbreaking piece of legislation, the first of its kind to tackle AI governance on such a comprehensive scale. The European Commission has divided AI systems into four risk categories: unacceptable, high, limited, and minimal. High-risk systems, like those used in healthcare or law enforcement, face rigorous requirements, including mandatory safety checks and detailed documentation. For instance, AI tools in medical devices must meet strict standards to ensure they don’t endanger patients, a move that reflects the EU’s deep commitment to safeguarding fundamental rights, as outlined in the official documentation of the AI Act. On the other hand, lower-risk systems, such as chatbots used within companies, are subject to lighter regulations, allowing businesses to innovate without being bogged down by red tape. It’s a thoughtful, risk-based approach designed to strike a balance between fostering innovation and protecting citizens.

I can’t help but admire the EU’s ambition here. Growing up in a world where technology often seemed to outrun regulation, I’ve seen the consequences of letting innovation run wild—data breaches, biased algorithms, and the erosion of privacy. The EU’s General Data Protection Regulation (GDPR), implemented back in 2018, set a global standard for data privacy, inspiring similar laws in places like Brazil and California. Over 130 countries have adopted data protection laws influenced by the GDPR, proving that the EU has the power to shape global norms. The AI Act could follow in its footsteps, becoming the go-to model for AI regulation worldwide. For companies operating in or targeting the European market, compliance isn’t just a legal checkbox—it’s a strategic necessity. Getting ahead of these rules could save businesses from costly last-minute scrambles and bolster their reputation as ethical innovators.

But there’s a catch, and it’s a big one. Critics worry that the EU’s regulatory zeal could backfire, particularly for smaller companies and startups. The European Commission estimates that compliance costs for high-risk AI systems could amount to €400,000 per system, depending on the complexity and scale. For small and medium-sized enterprises (SMEs), which make up 99% of all businesses in the EU and employ nearly 100 million people, these costs could be dealbreakers. I’ve spoken to entrepreneurs who fear they’ll be priced out of the European market or forced to abandon their AI projects altogether. If regulations push these smaller players away, Europe risks losing its competitive edge in a global AI race that’s heating up fast.

And then there’s the broader global context. While the EU is busy crafting its regulatory masterpiece, other major players like the United States and China are taking very different paths. The U.S., under President Donald Trump, has embraced a more hands-off approach, relying on voluntary guidelines and industry self-regulation. Meanwhile, China is pouring resources into AI development, with companies like DeepSeek emerging as global leaders. Analysts estimate that AI technology could bring $600 billion annually for China’s economy, fuelled by government support and a regulatory environment that’s far less restrictive than the EU’s. The third Artificial Intelligence Action Summit in Paris, held in February, highlighted these stark contrasts, with world leaders and tech executives grappling with how to regulate AI without losing ground to less regulated markets. China’s DeepSeek app, for example, which can self-train on coding and math problems, has only intensified these concerns, raising questions about whether the EU’s approach might leave it playing catch-up.

The EU’s AI Act also comes at a time when the AI landscape is evolving rapidly, with trends like AI-driven search snippets and workplace automation reshaping industries. Take Google’s AI Overviews, for example. A 2024 analysis by Seer found that these snippets, which provide answers directly on the search page, are reducing click-through rates for many businesses. While this is great for users who get quick answers, it’s a headache for companies that rely on organic traffic. On the workplace front, McKinsey’s 2024 report, “Superagency in the Workplace,” argues that AI can boost productivity and creativity but only if companies invest in training employees to collaborate with these tools. The report found that organizations that prioritize people-centric AI strategies—offering practical training, clear communication, and ethical guidelines—saw productivity gains. These insights suggest that regulation alone isn’t enough; success depends on how well organizations and societies adapt to AI’s potential.

Yet, for all the challenges, there’s a compelling case to be made for the EU’s approach. Proponents argue that well-crafted regulations can build trust and encourage responsible development. The AI Act’s focus on transparency, such as requiring developers to disclose details about their training data, resonates with growing public demand for accountability. 68% of Europeans want government restrictions on AI, citing concerns about privacy, bias, and job displacement. By addressing these issues head-on, the EU could position itself as a global leader in ethical AI, attracting businesses and consumers who value trust and safety. And let’s not forget the EU’s track record with the GDPR, which showed that robust regulation can coexist with innovation if it’s done right—thoughtfully, collaboratively, and with a clear eye on the bigger picture, as evidenced by its widespread global influence.

So, where does that leave us? As I see it, the EU’s AI regulatory framework is a bold and necessary experiment, one that reflects the bloc’s commitment to putting people first in an increasingly tech-driven world. But its success hinges on finding the right balance—encouraging innovation without sacrificing accountability and protecting rights without stifling growth. For businesses, the message is clear: don’t wait to adapt. Staying informed and preparing early could make all the difference, both in terms of compliance and reputation. For the EU, the challenge is even greater: to lead with vision, flexibility, and a willingness to learn from the global AI race. As a journalist, I’m cautiously optimistic, but I’ll be watching closely to see whether this framework becomes the global benchmark it aspires to be—or a cautionary tale of good intentions gone awry.

 

 

Source: https://intpolicydigest.org/is-the-eu-leading-the-charge-or-losing-the-race-in-regulating-ai/

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”.

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Balancing the scales: Why Crypto and AI both need urgent oversight

Balancing the scales: Why Crypto and AI both need urgent oversight

Technology has a way of moving faster than the rules meant to govern it, and nowhere is this more evident than in the parallel rise of cryptocurrency and artificial intelligence (AI). As someone who has spent years reporting on the intersection of innovation, finance, and policy, I’ve seen firsthand how these two forces have reshaped the global landscape. For a long time, I was convinced that cryptocurrency was the most pressing issue regulators needed to tackle. Its decentralized nature, its potential for misuse, and its volatile markets seemed to demand immediate action. But as AI has surged forward—especially with the recent emergence of AI agents capable of making independent decisions—my perspective has shifted.

Both crypto and AI are moving at breakneck speed, and both need urgent attention. However, if I had to prioritise, I’d argue that AI now poses the greater challenge. Its ability to influence critical processes, blur ethical lines, and even disrupt the crypto sector itself makes it a more complex and immediate concern. We’re in a regulatory race, and the consequences of falling behind could be profound.

Need for crypto regulation hasn’t diminished

Let’s start with cryptocurrency, which has long been a lightning rod for debate. When Bitcoin first gained traction over a decade ago, it was hailed as a revolutionary alternative to traditional finance, but it also raised red flags for regulators. The anonymity of blockchain transactions, the wild price swings, and the potential for cryptocurrencies to be used in illegal activities like money laundering made it a regulatory nightmare. I remember the frenzy of 2017, when Initial Coin Offerings (ICOs) were popping up everywhere, raising billions of dollars with little to no oversight. It was a wake-up call for governments and financial watchdogs. The Financial Action Task Force (FATF) stepped in with guidelines to curb illicit uses of crypto, and countries like the U.S. and those in the European Union started working on laws to regulate exchanges and wallet providers. Yet, even now, the global regulatory landscape for crypto remains uneven. Based on what I have seen, I believe that only about half of the jurisdictions surveyed had robust crypto regulations in place, leaving plenty of room for risks to fester.

The need for crypto regulation hasn’t diminished. With the total market value of cryptocurrencies hitting $3.1 trillion in early February 2025, according to CoinMarketCap, digital assets are no longer a niche interest—they’re a significant part of the financial ecosystem. The rise of decentralised finance (DeFi), where users can lend, borrow, and trade without traditional intermediaries, has only added to the complexity. These platforms are innovative, no doubt, but they often operate in a murky legal space, with little protection for users if things go wrong. The collapse of FTX in 2022, which wiped out $8 billion in investor funds, was a stark reminder of what can happen when oversight fails to keep pace with innovation.

And while regulators like the U.S. Securities and Exchange Commission (SEC) and the European Securities and Markets Authority (ESMA) have started cracking down, the global patchwork of rules still leaves too many gaps. In my course of advisory work, the feedback I got was that many cross-border crypto transactions happen in regions with weak or no regulations, raising the stakes for financial stability and crime prevention.

The rapid ascent of AI agents

But as significant as these issues are, they’ve been overshadowed by the rapid ascent of AI. When I first started covering AI, it was mostly seen as a tool for improving efficiency—think predictive analytics or targeted advertising. That’s changed dramatically in just a few years. Today’s AI systems, especially generative models like GPT-4 and autonomous AI agents, aren’t just tools; they’re decision-makers. In finance, for example, AI is now managing portfolios, executing trades, and even approving loans, tasks that used to require human expertise. Based on my opinion and how fast AI is being adopted, AI could handle up to 30% or even 40% of all financial transactions by 2030. That’s a massive shift, and it raises serious questions about accountability and risk. Who is responsible when an AI agent makes a bad call? How do we ensure these systems are transparent and fair? And what happens when they make decisions at a scale and speed humans can’t easily oversee?

The financial sector isn’t the only area feeling the impact of AI’s rapid growth, but it’s a prime example of the challenges we face. AI agents are now deeply embedded in trading, using vast amounts of data to spot trends and make split-second decisions. This has raised concerns about market stability. The European Central Bank (ECB) cautioned in 2024 that AI-driven trading could lead to sudden market crashes if algorithms converge on the same strategies or amplify volatility. And when you bring AI into the crypto world, the risks multiply. AI is already being used to optimise trading strategies, detect fraud, and even govern decentralised organizations. But as a recent social media post pointed out, the use of AI in crypto smart contracts could open the door to exploitation if these systems aren’t carefully designed. Regulators are only beginning to grapple with these issues, and the pace of change isn’t slowing down.

Our regulatory systems are struggling to keep up

Another area where AI poses unique challenges is intellectual property. Generative AI can produce content—text, images, music—in seconds, but who owns the result? In finance, AI-generated reports and analyses are becoming standard, but the legal status of that content is far from clear. There are cases where AI developers are using copyrighted financial data to train models, and the cases are still unresolved. I did a survey in my private group consisting of business owners and more than 70% of them who were using AI for content creation were unsure about the legal implications. This uncertainty is even more pronounced in crypto, where AI-generated content is often used to promote new tokens or sway market sentiment, sometimes without any disclosure of AI involvement. These gray areas aren’t just legal headaches; they’re potential breeding grounds for abuse.

Looking at the current state of play, it’s clear to me that our regulatory systems are struggling to keep up. Crypto regulation has made some progress—think of the EU’s Markets in Crypto-Assets (MiCA) framework or the SEC’s efforts to classify certain tokens as securities—but it’s still a fragmented effort. AI regulation, on the other hand, is even further behind. The EU’s AI Act, passed in 2024, is a step in the right direction, categorising AI systems by risk level and setting stricter rules for high-risk applications. But even this groundbreaking law has been criticised for not fully addressing the global nature of AI development or the specific challenges posed by AI agents.

AI needs to take precedence

So, where should regulators focus their energy? In my view, AI needs to take precedence, not because crypto’s challenges are insignificant, but because AI’s implications are broader and more profound. Crypto’s risks—volatility, fraud, regulatory gaps—are serious, but they’re largely confined to finance. AI, by contrast, has the potential to reshape every facet of society, from healthcare to education to governance. Its ability to amplify risks within crypto, such as through AI-driven trading bots or flawed smart contracts, only underscores the need for a comprehensive approach.

This isn’t to say crypto should be ignored. The lessons we’ve learned from trying to regulate digital assets—such as the need for consumer protections and international cooperation—can and should inform AI regulation. But AI’s unique challenges, from ethical concerns to systemic risks, demand a level of urgency and innovation that we haven’t yet seen. Regulators need to act quickly, establishing clear rules for AI-driven decision-making and ensuring these systems are transparent and accountable. This will require not just technical expertise but also collaboration across borders and sectors. Initiatives like the UK Financial Conduct Authority’s Digital Sandbox, which uses synthetic data to test AI applications, are a good start, but they need to be scaled up and adopted globally.

Ultimately, the regulatory race between crypto and AI isn’t about choosing one over the other; it’s about recognising the unique risks each poses and responding accordingly. Both are transformative technologies with the power to reshape our world, for better or worse. But as AI continues to accelerate, its potential to disrupt decision-making, challenge ethical norms, and even destabilise systems like crypto makes it the more immediate priority. We can’t afford to wait. The future of finance, technology, and society depends on getting this right, and the clock is ticking.

 

 

Source: https://ciosea.economictimes.indiatimes.com/blog/balancing-the-scales-why-crypto-and-ai-both-need-urgent-oversight/118572627

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”.

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Binance’s CZ Sparks Debate: Should AI Projects Be Built on Layer 1 or Layer 2 Blockchains?

Binance’s CZ Sparks Debate: Should AI Projects Be Built on Layer 1 or Layer 2 Blockchains?

The broader discussion aligns with industry trends, where AI and blockchain convergence is becoming a focal point for developers and investors alike.

Where Should AI Live? CZ Fuels L1 vs. L2 Discussion

In a recent post on X (Twitter), CZ highlighted that the core purpose of such projects is not to develop a superior blockchain. Instead, it is to use blockchain technology to support AI economics.

He noted that while L1 provides greater sovereignty and decentralization, it also demands more effort in maintaining nodes and validators. In contrast, L2 networks offer convenience by leveraging existing ecosystems like Ethereum’s decentralized exchanges (DEXs), perpetual contracts, and tools without significant value leakage to the base layer.

“L1 vs L2…Does it matter if a new AI project is an L1 or an L2?… Is L1 cooler than L2 or the reverse? Old topic, but wondering if sentiment has changed or not,” CZ posed, welcoming conversation.

Crypto analyst Hitesh Malviya argues that L1 blockchain is the superior choice. The analyst advocates this network for projects seeking to establish their own consensus mechanisms, optimize performance, and reduce validator costs.

However, he also warns that despite extensive fundraising and user acquisition efforts, many L1 projects still experience retention drops of 70-90% after token generation events (TGE).

“…even if you retain users, you would only see one category or niche capturing the maximum traction onchain. So if the destination is already known—retention drop, higher user acquisition costs, and niche-specific demand capture—then why not build an app chain using an L2 stack,” Hitesh suggested.

Given these challenges, he suggests that building an AI-focused blockchain as an L2 app chain is a more practical approach. This would allow for faster development, marketing, and scalability.

Meanwhile, Walter from the BNB Chain Business Development team supports L2. He emphasized its accessibility to existing tools and infrastructure. His comment also hints at speculation regarding CZ’s possible attendance at an upcoming Crypto Summit at the White House.

AI & Blockchain: The Layer 1, Layer 2, and Layer 3 Debate

Investor and blockchain advisor Anndy Lian adds another dimension to the debate. In a subsequent comment on X, he argued that AI is most effectively deployed at Layer-3 (L3). He explains that while implementing AI on L1 is theoretically possible, it is impractical due to security and resource constraints.

“AI can be implemented on blockchain Layers 1, 2, or 3… In practice, Layer 3 is where AI is most effectively and frequently utilized, leveraging the blockchain’s strengths while accommodating AI’s computational needs,” Lian explained.

On L2, the blockchain advisor noted that AI can optimize scalability. However, AI is most frequently utilized in L3, enabling a diverse range of AI-powered applications while leveraging blockchain’s strengths.

Meanwhile, CZ discusses AI’s placement in the blockchain ecosystem amid growing interest in AI-integrated L2 networks. In June 2024, Binance Labs (now YZI Labs) invested in Zircuit, an AI-enhanced L2 network that utilizes zero-knowledge rollups to improve security.

This investment signals Binance’s strategic focus on AI-blockchain integration, potentially influencing CZ’s latest inquiry.

Ethereum co-founder Vitalik Buterin has also been actively discussing L1 and L2 scaling solutions. Last month, Buterin outlined a roadmap for scaling Ethereum’s L1 and L2 protocols in 2025. However, he also recently cautioned that certain L2 networks will likely fail due to weak economic models and poor execution.

These statements further fuel the debate on whether AI projects should build their sovereign chains or integrate with existing ecosystems.

Nevertheless, CZ’s timing in raising this question may suggest he is gauging market sentiment for a new AI blockchain initiative. Given Binance’s investment in AI-driven L2 solutions and the increasing interest in modular blockchain architectures, he could be testing the waters for future ventures.

The trade-offs between sovereignty, scalability, and accessibility will shape the future of AI-blockchain integration. This could make it essential for developers and investors to weigh their options carefully.

 

 

Source: https://beincrypto.com/ai-layer1-vs-layer2-cz-debate/

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”.

j j j