The AI Investment Landscape: Opportunity Amid the Hype

Seattle’s venture capital experts are weighing in on the state of AI investments, offering nuanced perspectives on whether we’re witnessing an AI bubble or the early stages of a transformative technological revolution. While acknowledging pockets of overheating in the market, these seasoned investors see substantial substance behind the excitement, arguing that AI is already delivering tangible value despite concerns about inflated valuations and market saturation.

The most visible signs of market excess appear concentrated in early-stage private companies, particularly at seed and Series A rounds. Sabrina Albert of Madrona points to startups “priced well ahead of fundamentals,” with investors rushing to secure early AI exposure regardless of limited traction. This enthusiasm has created a disconnect between valuations and reality in some segments, though public markets seem more anchored to financial performance. Cameron Borumand of Fuse adds historical context, noting that “new technologies tend to be overestimated in the short term and underestimated in the long term,” suggesting AI’s full impact may take 10-20 years to materialize. Despite this longer horizon, companies like Anthropic are already demonstrating remarkable growth, projecting a leap from $1 billion to $9 billion in revenue by 2025 – evidence that substantial value creation is underway even amid the hype.

The capital deployment picture reveals differing views on where excess might be most pronounced. Chris DeVore of Founders’ Co-op believes significant capital “is almost certainly being misallocated” in global AI investments, particularly in data center buildouts. He contrasts this with previous bubbles in crypto and metaverse technologies, noting that unlike those cycles, “there are actual babies in the bathwater this time” – meaning LLMs represent genuinely valuable tools that will endure beyond any market correction. Sheila Gulati of Tola Capital draws parallels to earlier concerns about cloud computing, recalling similar worries when Microsoft launched Azure fifteen years ago. She sees today’s massive infrastructure investments as necessary foundations for the next wave of AI-powered enterprise software, creating opportunities for startups to deliver comprehensive solutions that blend human capabilities with AI agents. This perspective frames the current market less as a bubble and more as the infrastructure buildout necessary to support a genuine technological revolution.

For founders navigating this landscape, the investors offer remarkably consistent advice: focus on solving real customer problems, build durable revenue models, and prioritize efficiency. Andy Liu of Unlock Venture Partners identifies a growing gap between “narrative-driven AI companies” using AI primarily as a positioning tool and “value-driven AI companies” delivering measurable customer outcomes. He advises founders to “build real businesses, not decks,” noting that modern tools allow products to be built quickly with real revenue before raising capital. This emphasis on fundamentals echoes across all respondents, with Annie Luchsinger of Breakers framing the current environment as “less an AI bubble and more a classic venture cycle playing out around a genuinely transformative platform shift.” The difference, she explains, is the unprecedented “speed, scale, and capital availability” compared to previous technological transitions like cloud, mobile, and social media.

The enterprise software landscape appears particularly ripe for disruption, creating opportunities for AI-native startups to challenge established vendors. Sheila Gulati highlights the “unprecedented malleability of CIO budgets,” suggesting that “the deeply entrenched application stack can now shift to new players which are built with AI from the ground up.” This represents a rare window for startups to compete against incumbents as companies rethink their software investments. Cameron Borumand similarly notes favorable conditions for building, with active M&A markets, available customer budgets, and talent eager to work on innovative projects. However, he cautions that startups must “go deep and really focus on a core customer problem” to stand out amid the noise. The consensus view suggests that while infrastructure has dominated AI growth so far, the next few years will center on AI-powered applications that deliver specific, measurable value in enterprise contexts.

Looking toward 2026, the investors anticipate some market cooling but remain overwhelmingly optimistic about AI’s long-term potential. Several expect a gradual market normalization rather than a catastrophic crash, with Borumand predicting “some pullback in the public markets” as investors recalibrate expectations around enterprise AI adoption timelines. This adjustment might bring growth closer to historical averages after the exceptional AI-fueled performance of recent years. Despite these corrections, Annie Luchsinger emphasizes that “companies with real technology, real distribution, and real customers will endure” through any market fluctuations. The fundamental advice for founders remains consistent across all perspectives: ignore the hype cycle, focus relentlessly on customer problems, build efficient businesses with clear unit economics, and prepare for a potential cooling in valuation expectations. As Andy Liu succinctly puts it, “2026 is going to be an incredible moment to build,” particularly for small teams focused on efficient execution rather than narrative-driven fundraising.

While these Seattle investors acknowledge froth in certain corners of the AI market, they broadly reject the notion of a catastrophic bubble. Instead, they describe a rapidly evolving landscape where genuine innovation is occurring alongside inevitable excesses. The consensus view frames AI as a profound technological shift that is already creating substantial value, even as investors debate precisely where and when the technology’s full impact will materialize. For founders navigating this environment, the path forward involves looking beyond the hype to build solutions that deliver measurable outcomes, generate reliable revenue, and operate with efficient business models. Those who maintain this focus on fundamentals, rather than chasing inflated valuations through narrative alone, will be best positioned to thrive regardless of whether market expectations moderate in the coming years.