To The Moon

Looking back at this AI boom, one shift is becoming clear: the market is no longer paying a premium for "talkative AI" alone.

Whether it's copywriting, image generation, or more natural LLM interactions, these capabilities are rapidly being treated as baseline features. What truly drives valuation divergence is a more pragmatic question—whether AI can actually "get things done" and be embedded in the real world at scale.

And in the U.S. stock market, few institutions have consistently stood at the intersection of technology and capital like Andreessen Horowitz (a16z). From cloud computing and mobile internet to this current AI cycle, a16z has always been early to see where the inflection point lies.

a16z“ 2026

In its newly released Big Ideas 2026 series, a16z doesn't dwell on "how smart AI is." Instead, it proposes a more disruptive perspective:

What happens when AI stops being just a tool on your screen and begins to participate in—and reconstruct—the operating rules of the real world?

If 2023–2024 was the "hallucination era" of AI and 2025 the "infrastructure era," then in a16z's view, 2026 will be the critical turning point when AI formally moves into the execution layer, achieving industrialization and scaled deployment.

This article organizes several core trends from a16z’s report that offer the most insight for U.S. and Hong Kong stock investors.

From "Talking to You" to "Getting It Done for You": AI’s Role Upgrade

a16z repeatedly emphasizes in the report that AI’s next phase lies not in more natural interactions, but in the maturation of Multi-Agent Systems.

As the original text states:
"AI is shifting from systems you talk to, into systems that work on your behalf."

This means AI is no longer just a tool waiting for commands, but can autonomously collaborate backstage, decompose tasks, and continuously drive workflows forward. The way enterprises operate will shift from "human-driven software" to "AI-driven processes."

For investors, the deeper implication of this change is:
Screen time, click frequency, user stickiness—core metrics of the internet era—are losing their central importance.

What will truly command a premium are AI platforms and infrastructure that embed directly into the enterprise execution layer and significantly boost operational leverage. This is also why the market remains highly focused on cloud services, compute power, and enterprise-grade systems.

The Key to AI Deployment Isn’t the Model—It’s the Data

In a16z’s assessment, the biggest bottleneck preventing AI from reaching the core of enterprises is not model performance, but the nature of data itself.

The report notes that roughly 80% of enterprise knowledge still resides in unstructured, multimodal data—contracts, emails, videos, meeting notes. This "dark data" is difficult to verify and continuously update, becoming the greatest obstacle to AI reasoning and execution.

Therefore, a16z points to the ongoing evolution of the AI-native data stack as a key opportunity for the next decade:
Platforms capable of data cleansing, validation, and semantic management will become the "source-of-truth layer" for enterprise AI.

This trend also allows some companies once seen as "traditional enterprise software" to regain strategic value—whoever masters enterprise knowledge structures could become the gateway for AI decision-making.

Agent-Native Infrastructure Is Reshaping the Value of Cloud and Compute

As the number of agents grows and task concurrency increases, a16z clearly states:
Existing cloud and software architectures built for "human operation" are approaching their limits.

Future systems must simultaneously support massive concurrency, ultra-low latency, and dynamic task scheduling—this is the backdrop for a16z’s concept of Agent-Native Infrastructure.

Just as 4G networks unlocked the mobile internet, this new-generation infrastructure will directly determine the ceiling for AI application deployment. This judgment forms a long-term bullish thesis for companies related to compute power, data centers, and cloud platforms—while also explaining why the market remains relatively more patient with "base layer" valuations.

When Bits Take Over Atoms: AI Enters Manufacturing and Energy Systems

The most disruptive part of Big Ideas 2026 comes from its redefinition of the physical world.

a16z introduces the concept of the "Electro-Industrial Stack," emphasizing that electrification, materials science, and AI software are converging—giving software, for the first time, the real ability to "control atoms."

The report states bluntly:
"Factories will increasingly be treated as products."

Through modular design, AI-automated approvals, and software-defined manufacturing, factories, energy facilities, and even infrastructure could be replicated and scaled like code.

For the U.S. stock market, this signals an important pivot: traditional manufacturing, industrial, and energy sectors are entering a new cycle driven by software and AI—and their valuation frameworks may no longer fit the old "heavy asset" mold.

Conclusion: 2026 Is Not Just a Year—It’s a Watershed

a16z’s 2026 perspective essentially signals to investors:
The real value of AI is shifting from "visible applications" to "invisible yet indispensable system layers."

When AI no longer appears frequently in the interface but continuously improves efficiency, reduces costs, and reshapes industrial structures, the market’s pricing focus will shift accordingly.

Perhaps the real question worth asking isn’t "who will be the next AI star," but:

In the process of AI’s full-scale integration into the real world,
which companies are already positioned at the critical nodes of systemic transformation?

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