Beyond the Valley: Why the Next Big Wave of Value in AI Will Be Created Outside Silicon Valley

Articles

April 6, 2026

Artificial intelligence investments are breaking records - but the geography absorbing that capital is strikingly narrow. In 2025, roughly one-third of global VC funding went to artificial intelligence, yet approximately 85% of that capital was concentrated in U.S.-based companies [1]. Meanwhile, the vast majority of the world’s economic value is still generated in sectors and regions that remain well outside Silicon Valley’s radar. In this article, we examine the shift in AI value creation - from foundational AI to applied AI and from “Silicon Valley to the field” - drawing on global data, fund theses, and our own on-the-ground observations.

Costs Have Fallen, the Playing Field Has Changed

According to Stanford HAI’s 2025 AI Index Report, the per-query cost of a model performing at GPT-3.5 level dropped from $20 per million tokens in November 2022 to $0.07 in October 2024 - a decline of more than 280-fold in just 18 months [2]. ARK Invest’s Big Ideas 2026 report notes that data center investment reached approximately $500 billion in 2025 [3]. Capital flowing into infrastructure is surging, while the cost of using that infrastructure is collapsing.

Read together, these two trends point to a clear conclusion: in AI, value is shifting from developing models to integrating models into the right workflows. As model access becomes commoditized, the differentiating factors are domain expertise, data access, and business process integration.

The concrete evidence of this shift is the rise of vertical AI. According to a16z’s Big Ideas 2026 report, AI companies in healthcare, legal, and property management reached over $100 million in ARR within just a few years [4]. Harvey (legal) achieved a $5 billion valuation, EliseAI (property + healthcare) reached $2.2 billion, and Abridge (medical transcription) hit $5.3 billion [5]. What they share in common is clear: they are not general-purpose chatbots, but vertical solutions that deliver end-to-end outcomes within a specific workflow.

Silicon Valley’s Blind Spot: Where Will Value Be Created?

This is where an interesting tension emerges. a16z partner Joe Schmidt makes it explicit in Big Ideas 2026: AI has so far created value mostly for companies that are in or connected to Silicon Valley; in 2026, that dynamic will reverse [4].

Schmidt’s observation is this: founders naturally sell to companies they can physically reach or connect with through investor networks - which largely confines their customer base to the Silicon Valley ecosystem. This means the bulk of the opportunity - in traditional consulting, system integrators, manufacturing, and other slow-moving industries - remains undiscovered.

The structural reason behind this observation matters. The majority of global GDP is still produced in traditional sectors: manufacturing, agriculture, logistics, construction, retail, and healthcare. Most of these sectors run on paper-based processes, legacy software, and low levels of digitalization. AI’s greatest productivity gains will not come from sectors that are already digitalized; they will emerge in areas that have yet to digitalize but carry enormous economic weight.

There is also a geographic dimension. Outside the U.S., traditional sectors carry significantly more weight. In developing economies, a substantial share of GDP is concentrated in agriculture, manufacturing, logistics, and retail. Workflows in these markets are typically more complex, less standardized, and more dependent on human intervention - precisely the points where AI can make the greatest difference [4].

The “forward-deployed” approach that a16z describes - going to the customer’s site and understanding the workflow firsthand - is, in fact, the natural advantage of founders in developing markets. A Silicon Valley founder would need to “forward deploy” to understand the workflow of a manufacturing plant in Anatolia or a logistics operation in Southeast Asia. Founders born in those markets, by contrast, already start with the domain knowledge; they simply layer AI on top.

A critical distinction must be made here: this is not about “cheap labor.” The cost of accessing an AI model through APIs is the same in Istanbul as it is in San Francisco. The real difference lies in three structural advantages:

First, domain depth. An intimate understanding of a given market’s regulations, business practices, and industry conventions directly determines the quality of the solution built on top of a model. The defining characteristic of winning vertical AI companies is not a “better model” but “better workflow integration.”

Second, operational efficiency. In developing markets, a $1–2 million seed investment provides a significantly longer runway thanks to lower cost structures. While the same seed round might finance 12–15 months of operations in the U.S., in these markets it can sustain 24 months or more. As AI tools continue to drive down software development costs, this advantage compounds further: smaller teams, less capital, and faster iteration become possible.

Third, valuation arbitrage. According to Equidam’s global startup valuation analysis, seed-stage startups in Europe are funded at valuations averaging 52% lower than their U.S. counterparts; by Series A, this gap narrows to 38% [6]. The State of European Tech 2024 report paints a similar picture: at the seed stage, U.S. median valuations are more than double Europe’s, but the gap closes as companies scale [7].. In developing markets, this discount is even more pronounced. For early-stage investors, this translates into significant upside potential. Consequently, investors seeking to catch the next value wave in vertical AI early need to look not only at the Valley but also at the emerging ecosystems where these structural advantages converge.

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Traditional SaaS “offers a tool”; the vertical AI approach “delivers an outcome.” The winning products are not those that use a smarter model - they are those that produce measurable and reliable business results.

The Rise of Emerging Ecosystems

These dynamics are not unique to any single market. In 2025, India attracted approximately $11 billion, the MENA region recorded a record $7.5 billion [8], Southeast Asia drew approximately $5.4 billion [15], and Latin America pulled in $4.1 billion [16] in startup investment. What these markets share in common: large populations, low digitalization rates, strong engineering talent, and rapidly growing AI adoption.

The diaspora effect and local domain expertise are also playing decisive roles. Legora (formerly Leya), a Swedish legal AI company, differentiated itself through European regulatory expertise and multilingual capabilities, reaching a $1.8 billion valuation [9]. Its U.S. counterpart Harvey stands at a $5 billion valuation, but Legora turned “European legal system” domain knowledge into a competitive advantage - a concrete example of the “local domain expertise + global AI infrastructure” formula.

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Türkiye occupies a meaningful position in this landscape. According to KPMG Türkiye’s report, 2025 saw $1.4 billion in volume across 360 deals, with AI standing out as the most active sector by deal count [10]. In Startup Genome’s 2025 report, Istanbul rose to third place globally among emerging ecosystems [11]. However, diaspora ventures secure a median funding level 24 times higher than domestic startups [12] - a clear indication that homegrown ventures still face a significant gap in accessing global capital.

The Cost of Creating Value Beyond the Valley

The thesis that AI value will shift beyond Silicon Valley rests on strong foundations - but this shift will not be frictionless. The risk of “AI washing” is growing on a global scale; in Crunchbase’s 2026 predictions, VCs are clear: capital will reward genuine AI advantage while penalizing the cosmetic application of AI onto old ideas [13] - yet in still-maturing ecosystems, distinguishing “AI-native” from “AI-enabled” is harder for both founders and investors. Go-to-market challenges also take on a different dimension: in developing markets, sales cycles are longer, access to decision-makers is more complex, enterprise customers have higher trust thresholds - and the initial customers won by local domain expertise can become a constraint rather than an advantage when expanding to a different geography. The funding ladder is also fractured: while it is possible to start at the seed stage with local funds, Series A and beyond require international investors - and at this transition point, sourcing capital locally can be difficult.

Yet the other side of the coin is equally real: for founders who can convert domain expertise into a genuine applied-AI advantage, produce measurable business outcomes instead of an AI veneer, and combine local knowledge with a global vision, the window of opportunity is wider than ever. The same is true for investors who can spot these structural opportunities outside Silicon Valley’s radar early and reach the right teams. For teams that can turn domain depth into a competitive edge and AI into real business value - and for investors who catch this trend early - the coming period may present one of the most productive opportunity windows of recent years.

BV Perspective

As we launched our applied-AI-focused BV Growth II fund at Bogaziçi Ventures, our core thesis was this: value will be generated not in foundational AI, but in the secure and measurable integration of models into business processes. The global data we have examined in this article supports that thesis.

The winning ventures will not be those that use the most advanced model; they will be the teams that produce measurable outcomes in a specific workflow, convert domain expertise into a competitive advantage, and elevate autonomy in a controlled manner.

The next great value wave in AI will not emerge from a better model - it will come from better system design, deeper domain expertise, and smarter go-to-market strategies. By definition, this wave is not confined to Silicon Valley’s borders.

For over a decade, we have worked with great dedication to contribute to and create value within Türkiye’s technology startup ecosystem. We support entrepreneurs with the deep knowledge and strong networks we have built during this time. At Bogaziçi Ventures, as we shape our investments, we believe in the potential of delivering sustainable and intelligent solutions by harnessing the power of technology across multiple verticals.

We invite entrepreneurs to apply for investment discussions at [email protected]. Apply now to scale your technology venture and join our global network!