VC and AI: The Rush into Historically Overlooked Sectors

Traditional Sectors Attract VC Attention

Historically, areas such as defense, energy, robotics, and government have been avoided by venture capital (VC) investors. These sectors, often labeled as "hard," are characterized by slow supply cycles, strict regulations, and challenging customer migration. Traditional software providers like IBM, SAP, ServiceNow, and Schneider Electric have long benefited from this complexity, allowing them to innovate at a slow pace without risking their customer base.

This situation has made the massive sell-off of these software giants, exacerbated by anxiety surrounding AI this year, all the more dramatic. While headlines have attributed this sell-off to rapid tool launches by Anthropic for vertical industries, there is more at play. The true driver of this trend is a newfound enthusiasm among founders to create AI-native solutions in traditional sectors, supported by VCs who see a unique opportunity to disrupt these industries.

A Shift in Investor Perception

The current geopolitical context, marked by instability and supply chain pressures, has placed industrial resilience at the heart of national policies in both the United States and Europe. Policymakers are encouraging investments in critical infrastructure, including upgrades to electrical grids, transportation infrastructure, and the public sector. They are also reevaluating supply and compliance systems that have slowed the adoption of emerging technologies that could enhance this industrial resilience.

At the same time, rapid advancements in AI and agentic systems are making it possible to create a new class of AI-native software. These software solutions are tailored for "hard" industries through deep integration with verticalized tools and specialized automation of critical workflows. The old barriers of established companies, such as lengthy migration cycles that discourage businesses from switching software providers, are also being challenged. Integrated automation reduces these migration processes from several weeks to just a few days.

Software creation has become a commodity in the age of AI. More and more investors realize that operational depth, an intuitive user interface/user experience, speed to market, and seamless integration into complex real-world systems are characteristics of high-quality vertical software that startups are well-positioned to develop.

Investors are also becoming aware that most of the available value from horizontal SaaS has already been extracted. In these early post-ChatGPT years, VCs have largely supported AI companies building for adoption by unregulated SMEs — exactly the audience that foundational model players like OpenAI and Anthropic are now targeting as they enter the enterprise space. Foundational models are inherently general, and their verticalization can only extend so far. In this context, AI-native products designed for heavy industries represent attractive and competitive propositions for VCs.

The Vulnerability of Established Players

There has always been considerable skepticism among investors and tech leaders regarding the ability of AI startups to significantly challenge the established players that have dominated for decades. However, these companies operate with product architectures and extensive processes built in the pre-AI era. Transitioning from this status quo to AI-native systems is a massive challenge, while new companies are launching with these systems in place from day one.

Established players also have little incentive to innovate quickly when customer loss is limited. However, in the current context of rapid improvements in AI models and agentic systems, waiting for customer loss to manifest will be too late. Skepticism may also overlook the profile of exceptional founders who are building AI-native challengers. Some of the fastest-growing startups in defense, energy, government, and the public sector are led by individuals directly from the same industries they are transforming. Their understanding of sector constraints and operational realities gives them an advantage over general software providers who lack the same specialization and experience.

The Rise of Investments in Hard Sectors

Savvy entrepreneurship and venture capital investors are coming together to tackle hard sectors. Once considered inaccessible due to procurement complexity or regulatory burdens, these sectors represent enormous untapped potential in the age of native AI. Emerging companies offering solutions designed for these industries, with integration of specific tools and automation of critical workflows, are well-positioned to capture a growing share of overall AI funding, addressing customer problems that have remained unanswered for years.

We are talking about disruption in markets worth trillions. The scale of the opportunity for increasing VC interest in sectors they have historically avoided is neither a mystery nor a miscalculation. The vision is ambitious. Rather than simply building better software, the foundational sectors of the global economy are on the verge of being reinvented.

Thomas Cuvelier is a partner for the United States and Europe at the early-stage venture capital firm RTP Global. He is currently overseeing the deployment of the firm's latest $1 billion fund, supporting a range of AI-native startups aimed at disrupting traditional industries and business processes. Personally, Cuvelier invested in Lovable during its pre-seed round.