A16z Outlook 2026: Electric Industry, Financial Infrastructure, and AI Agent Layer, forming the industrial pillars of the AI era

a16z in the latest wave of “2026 Big Ideas,” three long-term investors in American industries, financial services, and enterprise software, present their key observations for 2026. The overall discussion focuses on three main directions: the acceleration of the electrical industrial stack formation, the transformation of core architecture in finance and insurance industries utilizing AI systems, and the rise of dynamic AI proxy layers in enterprise software, beginning to shake the dominance of traditional system cores.

First Direction: Electrical Industry Stack, Driving a New Industrial Revolution

Electrical Industry Stack Takes Shape, Industrial Revolution Moves Inside Machines

Ryan McEntush, partner at the US dynamic investment team, points out that the key change in 2026 is the beginning formation of the “Electrical Industry Stack,” driving the next industrial revolution.

He states that industrial progress is no longer confined to factories but extends into equipment and machinery itself. Electric vehicles, drones, data centers, and modern manufacturing rely on a comprehensive set of electrical and electronic technologies, including batteries, power electronics, semiconductor components, computing power, and motors.

He notes that the US is not lagging in engineering and critical technologies; the real challenge lies in industrializing and scaling these technologies to be cost-competitive. In contrast, China’s advantage comes from a complete supply chain and institutional support, enabling rapid enterprise expansion.

Ecosystems and Supply Chains Determine Long-term Competitiveness

McEntush uses SpaceX as an example to illustrate that high vertical integration is often not a strategic choice but a result of insufficient supply ecosystems. In China, a complete supply chain has already formed, but in the US, it still needs time to catch up.

Therefore, to establish the electrical industry stack, simultaneous advancement of technology, supply chains, and institutional frameworks is necessary, rather than shifting bottlenecks. On talent, he believes that software culture and traditional industrial experience must be combined, through close collaboration between engineering and manufacturing, to accelerate progress and attract top talent with a strong sense of mission.

As software and AI continue to penetrate industrial and military applications, controlling key supply chains will influence the distribution of global economic and military power over the coming decades.

Second Direction: Financial and Insurance Industries Say Goodbye to Old Cores, AI Native Platforms Become the New Mainstream

System Transformation at a Critical Point, Old Architectures Pose Greater Risks

Angela Strange, partner at an AI application fund, points out that 2026 will be a pivotal year for the financial and insurance industries. For a long time, the industry has believed that replacing core systems is too risky, but this perception is changing.

She observes that more and more large institutions are choosing to let contracts expire and adopt AI-native platforms because the risks of not upgrading outweigh the transformation itself. She emphasizes that the core of new infrastructure is not just “adding AI to old systems” but integrating information scattered across existing cores, external systems, and unstructured data to rebuild the data core, enabling financial institutions to expand and truly leverage AI benefits.

Process Reengineering and Scale Expansion, Early Movers Continue to Outperform

Strange states that the new platforms bring structural changes such as parallelized processes, risk and compliance data integration, and software-driven workforce reduction, which amplify market scale.

She explains that this wave of transformation is initiated now because legacy mainframe systems are reaching their limits, AI revenue opportunities are becoming tangible, and new AI-native startups that truly understand the industry are emerging. Banks and insurance companies that have already completed system transformations have seen significant profit improvements in some areas, while those slower to adapt are widening the gap year by year.

Third Direction: Dynamic AI Proxy Layer Takes Shape, Enterprise Software Enters a Structural Transition Period

Rise of Dynamic Proxy Layers, System Core Positions Erode

Sarah Wang, partner at a16z growth investment team, focuses on structural changes in enterprise software. She points out that when AI proxies can directly move from “user intent” to “actual execution,” the traditional passive-recording system core begins to lose its original justification.

She admits that her past long-term investments in ERP and similar system cores were based on data stickiness, but this is the first time a technology has emerged that can truly shake their position. For example, in IT service management, a field once dominated by enterprise software company ServiceNow, is being rapidly rewritten by a new generation of AI proxies. A senior IT executive even states that this is the first time in his 20-year career that he believes IT support will undergo fundamental changes within the next five years.

Proximity to Users and Rapid Iteration Are Key to Success

Wang explains that the disruptive power of AI proxies lies in their ability to understand needs, classify requests, coordinate processes, and execute in real-time, significantly shortening lengthy application and processing workflows.

She believes that while foundational models will still exist, the long-term value will be accumulated in the proxy layer closest to users, which will continuously collect user preferences and behavioral data, forming a new competitive advantage. At the same time, product evolution speed is critical; if proxies are not accurate and reliable enough, they will struggle to gain user trust. She also notes that even proxies built on large platforms are being replaced by innovative AI SRE companies, indicating that the enterprise software market is undergoing rapid reshuffling.

(Note: AI SRE companies refer to a type of startup focused on applying AI to website/system reliability engineering, enabling AI to automatically monitor, detect, diagnose, and even repair issues in IT infrastructure or software systems, rather than just passive alerting. )

(The future business models of AI remain unpredictable. a16z analyzes the next wave of AI technology and investment shifts.)

This article, a16z’s outlook for 2026: electrical industry, financial infrastructure, and AI proxy layers, forming the industry pillars of the AI era, first appeared on Chain News ABMedia.