Silicon Valley's AI bet could hit record $200 bn this year; investors warn of dot-com parallels

OpenAI is closing a $40 billion funding round, known to be one of the largest private tech deals on record. The staggering growth of artificial intelligence (AI) has triggered an unprecedented surge in venture capital, with global AI investments projected to hit “$200 billion” this year. But as money floods into the sector—particularly large language models and foundational AI systems—top investors are beginning to voice concerns about sustainability, profitability, and the eerie parallels to past tech bubbles.

At a panel discussion during Tredence AI Day 2025 featuring venture capitalists, Rishabh Iyer, Vice President at ChrysCapital, Arjun Gobinath, Director at Advent International, and Anirudh Jain, Principal at APAX Partners moderated by Shubh Bhowmik, co-founder and CEO of Tredence where Iyer revealed that nearly 70% of all AI funding is currently being funnelled into LLMs and foundational models.

Tech giants like Microsoft, Google, and Salesforce are driving much of this spending, betting that these technologies will become the backbone of future enterprise and consumer applications. Yet the investment wave extends beyond just software—data centers, semiconductor firms, and even clean energy providers are experiencing a surge in demand as AI’s infrastructure needs grow.

Gobinath noted that AI-related startups now account for 46% of all U.S. venture funding, a dramatic increase from just 10% five years ago. But he also struck a cautionary tone, drawing comparisons to the dot-com boom of the late 1990s. "We’re seeing billion-dollar investments in pre-revenue AI companies—that’s something we’ve never seen before," he said. "Not all of these firms will survive. There will be consolidation, and only those with truly differentiated offerings will endure."

Jain likened the rise of generative AI to the discovery of electricity—a foundational shift that will reshape industries. However, he emphasized that real-world adoption, not just hype, will determine long-term success.

When asked how investors distinguish promising AI startups from overhyped ventures, the panellists pointed to scalability, workforce readiness, and clear paths to profitability. Jain also stressed the importance of internal AI adoption, noting that companies failing to upskill their employees risk falling behind.

Despite the enthusiasm, an undercurrent of unease ran through the conversation. Rising anxiety in Silicon Valley, where concerns about regulation, ethical dilemmas, and another potential "AI winter" loom large. Gobinath acknowledged these fears, predicting a coming wave of consolidation as the market separates viable businesses from those riding the hype cycle.

As AI investment continues to break records, the central question remains: Is this boom the dawn of a transformative era, or are investors fuelling another unsustainable bubble? For now, venture capital shows no signs of slowing down—but the warnings from those writing the biggest checks suggest that the stakes have never been higher.