AI Lessons From The Web3 Boom,Bust And Boom

The artificial intelligence sector is experiencing an unprecedented surge in investment, reminiscent of the Web3 and cryptocurrency boom of recent years. With investments by Nvidia, AWS, Google, OpenAI, and more startups entering everyday, how do investors, technologists, and business leaders know where to place their focus.

The global AI market is experiencing remarkable growth, with investments surging to new heights. Per Grand View Research, the market is projected to reach approximately $184 billion, which is staggering. In the U.S. alone, the AI market is anticipated to expand from $55.8 billion this year to a whopping $219 billion by 2030, growing at a compound annual growth rate (CAGR) of 25.6%. This tells me that there’s a significant momentum driving this sector forward.

When we look at the broader landscape, I think it’s fascinating to see that, per IngestAI, the U.S. has led the way with around $290 billion in venture capital investments in AI over the past five years. This number, in my view, underscores just how crucial AI has become to tech giants, startups, and research institutions alike. But it’s not just the U.S. that’s making waves. China is expected to push its AI market beyond $61 billion by 2025, which I find quite impressive, given their strong state-driven growth strategy.

In my opinion, these figures highlight the massive scale and the broad applicability of AI across different sectors, from healthcare to autonomous systems. This is not just a trend; it’s a transformation that’s shaping our future in profound ways​

Both web3 and AI waves captured the imagination of investors, promising revolutionary changes to technology and society. However, as the dust settles on the Web3 boom and bust and boom cycles, investors, technologists, and business leaders in AI would do well to heed the lessons learned. I’ve been exploring the parallels between these two transformative technologies and their respective landscapes.

The Hype Cycle: Web3 vs. AI

Both Web3 and AI experienced similar patterns of hype and excitement in their early stages. Media coverage played a significant role in fueling public interest and investment in both sectors, much of it accurate and insightful but inevitably, some of it quite wide of the mark. However, the more tangible and immediately applicable use cases of AI have captured the public imagination to a significantly greater degree than the often abstract promises of Web3.

This has significant implications for investors, who must discern between genuine potential and overblown expectations in both cases. They must also learn to identify those who claim AI will bring armageddon and those who claim it represents no challenges to humanity at all – and treat these two imposters just the same.

The fact that AI is dominating the front pages (and not just in the tech press) suggests that the scale of investment will outstrip that experienced even by crypto. While both peak periods (crypto in 2021 and AI in 2023) are comparable, with both sectors attracting tens of billions of dollars in venture capital, the AI sector, particularly generative AI, might have seen even more aggressive funding rounds in a shorter period due to its perceived broader applicability across industries.

I was speaking with Cathy Hackl, a tech and gaming executive and co-founder of a stealth startup this weekend. She said that she believes that “AI and Web3 are not just buzzwords; they’re transformative technologies with the potential to reshape our digital landscape. For investors, the key is to look beyond the hype and focus on projects solving real-world problems with clear use cases. Remember, we’re in this for the long haul – both AI and Web3 will take years to fully mature and realize their potential. It’s not just about investing in tech, but in the vision of a more efficient, equitable, and innovative future.”

It’s not just about the numbers, either: the focus of investment is different. Crypto investments were largely driven by speculative trading, decentralized finance (DeFi), and the emergence of non-fungible tokens (NFTs). In contrast, AI investments are more diversified, spanning across enterprise applications, consumer products, and foundational research, indicating a broader potential impact.

The Patterns

Early adopters and tech enthusiasts were the first to jump into both Web3 and AI investments. As buzz grew, institutional investors began to take notice, lending credibility and injecting significant capital into both sectors. The influx of retail investors followed, often driven by fear of missing out (FOMO) and the promise of quick returns. Venture capital played a crucial role in both ecosystems, funding startups and fueling innovation at a rapid pace.

Web3 promised a decentralized internet, while AI offers the potential for unprecedented automation and intelligence in various domains. Both technologies faced challenges in delivering on their ambitious claims, with Web3 struggling with scalability and user adoption, and AI grappling with issues of bias, reliability and data security. The gap between technological promises and real-world implementation has been a sobering reality for investors in both sectors.

Market Correction and Consolidation

The Web3 and crypto markets experienced a significant crash, leading to a period of consolidation and reassessment. That’s hardly surprising, given that they are based on digital tokens which, like any asset with a market value, can be highly volatile. While the AI market is more insulated from the speculator-driven ‘valuation rollercoaster’ and consequently hasn’t seen a comparable crash, there are signs of potential correction as the initial euphoria gives way to more realistic expectations. Investors are becoming more discerning, focusing on AI companies with solid business models and clear paths to profitability.

Regulation played a significant role in shaping the Web3 and crypto investment landscape, with unclear guidelines and crackdowns causing market volatility. The AI sector is now facing increasing scrutiny from regulators concerned about privacy, bias, and the societal impact of the technology. Investors in AI must be prepared for a shifting regulatory landscape that could significantly impact the sector’s growth and direction.

In the aftermath of the Web3 boom, it became clear that some projects offered genuine innovation while others were purely speculative. Similarly, the AI sector is seeing a mix of truly groundbreaking applications and overhyped solutions. Technologists, investors, and users are challenged to distinguish between AI companies offering sustainable value and those riding the wave of speculative enthusiasm.

Lessons for AI

The AI clock started ticking decades ago, with steady progress in machine learning and neural networks laying the groundwork for today’s breakthroughs. In fact, significant AI investment predates the crypto and Web3 boom. As someone who began working in AI back in 2013, I’ve witnessed firsthand the long-term development and investment cycles in this field.

OpenAI’s ChatGPT represents AI’s “Netscape moment,” catalyzing widespread adoption and sparking a new wave of innovation.

In fact on X (Twitter), Blitzscaling Ventures general partner Jeremiah Owyang commented that “AI agents will autonomously handle laborious tasks for us, such as managing repetitive emails, filling out expense reports, booking travel, scheduling calls, doing internet research, and performing monotonous e-commerce tasks. It won’t be perfect, it will take time to refine.As a result, information will come to humans in just a few user interfaces where we can manage our agent workers, reducing the need to traverse websites.

In contrast, blockchain technology, though younger, is rapidly evolving to address both consumer and enterprise needs. Its decentralized nature introduces unique complexities, but also promises revolutionary applications across various sectors.

The Web3 experience underscores the importance of thorough due diligence and a deep understanding of the underlying technology. AI investors should heed these lessons, being wary of unrealistic promises and focusing on companies with clear use cases and revenue models. Maintaining a long-term perspective is crucial, as the full potential of AI, like Web3, may take years to materialize fully.

As these technologies mature, we’re likely to see a convergence, with AI enhancing blockchain capabilities and decentralized systems providing new frameworks for AI deployment and governance. The key for investors and innovators alike is to balance enthusiasm with realistic expectations, recognizing that true technological revolutions often unfold over decades rather than months.

With AI reaching into almost every aspect of life, the future will almost certainly see an integration of AI and Web3 technologies, creating new opportunities as this intersection acts as a “force multiplier” for each revolution’s transformative capabilities. Decentralized AI systems and blockchain-based machine learning marketplaces are just a few potential areas of convergence. So, for investors it’s not a case of either/or: they need to keep an eye on the evolving, often symbiotic landscapes of both Web3 and AI, the implications of new developments on each other, and on the wider tech and industry investment landscapes.

The AI investment boom shares many similarities with the Web3 cycle, but also presents unique opportunities and challenges. By learning from the Web3 experience, investors can navigate the AI landscape more wisely, balancing enthusiasm with caution. Ultimately, both AI and Web3 represent transformative technologies that will continue to shape our digital future, regardless of short-term investment trends.

Emphasize Regulatory Awareness and Ethical Considerations

As with Web3, the AI industry is poised to encounter significant regulatory scrutiny. The implications of AI on privacy, bias, and ethical standards are already drawing the attention of regulators worldwide.

For AI investors, it is crucial to consider the regulatory landscape and invest in companies that not only comply with current laws but are also proactive in addressing potential future regulations. Companies that prioritize ethical AI development, ensuring transparency, fairness, and accountability, are more likely to sustain long-term success and public trust.

It’s All About the Business

As we navigate the exciting yet complex landscapes of AI and Web3, investors, technologists, and business leaders must approach these fields with both enthusiasm and caution. Choose your investments and projects carefully, looking beyond flashy demos to examine the underlying data strategy – it’s the fuel that powers these technologies.

Pay close attention to change management; the most brilliant innovation is worthless if your team or customers can’t adapt to it. Keep a laser focus on tangible business outcomes rather than getting lost in technological rabbit holes. Remember, success in these domains often comes from starting small: begin with pilot projects that demonstrate clear value and build from there.

By taking measured steps, learning from each iteration, and staying aligned with core business objectives, you’ll be better positioned to harness the transformative potential of AI and Web3 while mitigating risks. In this rapidly evolving landscape, those who combine visionary thinking with pragmatic execution will be the ones who truly thrive.