知名投资人 Elad Gil 在 TechCrunch Disrupt 活动上表示，AI 是他见过最不可预测的技术浪潮之一。他指出，尽管 AI 领域许多早期初创公司已获得巨额投资，但部分 AI 市场，特别是基础模型和 AI 辅助编码等领域，已显现出明显的领导者，新进入者面临巨大挑战。然而，金融工具、会计、AI 安全等领域仍充满机遇。Gil 强调，企业对 AI 战略的迫切需求推动了新市场的快速增长，但并非所有快速增长的市场都能持续，只有经过市场验证的模式才能真正成功，并点名 Harvey 是一个“正在奏效”的成功案例。

💡 AI 投资充满不确定性，市场领导者正在快速形成。Elad Gil 认为，AI 领域的发展速度和演变速度超出了许多人的预期。尽管许多初创公司获得了大量投资，但像基础模型和 AI 辅助编码这类市场，已经出现了显著的市场领导者，这使得后来者难以追赶。这种快速的市场固化现象是 AI 领域的一个突出特征。

🚀 部分 AI 市场已显现领导者，新进入者面临高门槛。Elad Gil 指出，在基础模型、AI 辅助编码、医疗转录和客户支持等领域，市场领导者已经确立，例如 OpenAI、Anthropic、Mistral 在基础模型领域，Cursor 和 Devin 在 AI 辅助编码领域。这些领域的竞争格局已趋于稳定，新进入者需要付出巨大的努力才能获得一席之地。

💰 金融工具、会计和 AI 安全等领域仍是开放的蓝海。与已显现领导者的市场不同，Elad Gil 认为金融工具（fintech）、会计和 AI 安全等领域仍然是充满机遇的“开放游戏”。这些领域尚未出现明确的市场主导者，为新的创新者提供了广阔的发展空间，预示着未来可能出现新的独角兽企业。

📈 企业对 AI 的迫切需求推动市场增长，但需警惕虚假信号。Gil 指出，大型企业为了制定 AI 战略，正积极尝试各种 AI 技术和解决方案，这导致了新 AI 市场的快速增长。然而，他警告说，这种增长并不总是代表可持续的成功，初创公司和投资者需要区分真正的市场需求和暂时的市场热度，只有经过市场验证、能够持续产生价值的业务才能真正脱颖而出，例如 Harvey 在法律 AI 领域的成功就证明了这一点。

Solo VC investor extraordinaire Elad Gil said on stage at TechCrunch Disrupt that AI has been one of the least predictable tech booms he’s ever seen.

Gil is on the cap table of virtually every hit company of the past decade, including many of today’s leading AI companies.

Still, he thinks that over the last year, certain AI markets appear to be nearly sewn up by market leaders. Beyond these areas, a vast swath of AI remains anyone’s game.

“I started investing in generative AI in 2021 … at the time, not very many people were paying that much attention to it,” Gil said. But he had seen the massive leap in capability between GPT 2, launched in 2019, and GPT 3,  launched in 2021. “The step between 2 and 3 was so large that if you just extrapolated out the scaling laws, or the curve, then you could really assume that this was going to be incredibly important,” he said.

That convinced him to start backing early-stage startups building products powered by large language models. His bets included both foundational model makers like OpenAI and Mistral, as well as application companies like Perplexity, Harvey, Character.ai, Decagon, and Abridge. Yet throughout 2024 and much of 2025, the capabilities of foundational models leaped with every release, upending AI every few months.

“I used to say at the time that AI was the one market where the more I learn, the less I know. Usually, the more you learn about something, the better you know it, the easier you can predict the future, etc. But AI was just hazy. There’s just too much uncertainty. And I think there’s still markets like that in AI,” he said.

However, he’s also now seeing markets with clear winners. The most obvious example is with foundational models themselves. Even though hundreds of models exist, and some countries like South Korea are still working now to develop sovereign models by local companies, leaders have emerged. “Google, Anthropic, OpenAI, maybe xAI, maybe Meta, maybe Mistral — it’s like a handful,” he predicts of the winners.

After models, he thinks AI-assisted coding has runaway winners that will make it hard for new entrants to catch up. Not only have the foundational model makers moved in (Anthropic with Claude Code, OpenAI with Codex) but startup leaders like Anysphere’s Cursor and Cognition’s Devin (which acquired Windsurf) will be hard to beat. And there are well-funded startups like Magic (whom Gil called a possible “outlier”) or Poolside on their tails.

He sees medical transcription as being cornered, with Abridge a front runner and a handful of others like Ambiance being “important.”

He names customer support – which was an early target of both traditional AI and the new crop of AI agent startups – as having hard-to-catch market leaders, such as his portfolio company Decagon. (It raised $131 million at a $1.5 billion valuation in June.) OpenAI chairman Bret Taylor’s startup, Sierra, competes in this space. This is also an area where the incumbents — Salesforce, Hubspot, and many others — are adding AI offerings.

So which markets seem wide open? Gil says financial tooling (fintech), accounting, AI security, and “other markets that we know are by default very interesting. We just don’t know who’s going to do it.”

Ironically, fast growth isn’t the signal it once was that a company is going to be a breakout hit. “The CEOs of every big company are basically telling their teams, hey, we have an edict. We need to figure out our AI strategy,” Gil said. “These giant enterprises are willing to try things that two years ago they never would have tried, and it’s only because of AI.”

So new AI markets can land a lot of revenue from big-name, enterprise customers quickly, “but that doesn’t mean they’re going to stick,” Gil points out.

It is only after a market goes through its trial-phase boom cycle that a startup and investors can see if this revenue will stay and grow. “There’s false signal, and then there’s stuff that is just working,” Gil said. He calls out legal AI startup Harvey as one of the market-leaders that’s “just working.” It raised three massive rounds in 2025, leaping from a $3 billion valuation to $5 billion to $8 billion, in just a few months.