Disruptive tech, concentrated alpha: Inside GVC’s high-conviction approach

The significance of AI as a once-in-a-generation technological shift is increasingly reshaping how capital is allocated, how industries compete and where equity market leadership resides.

For investors, it is a dual-engine dynamic. The US remains dominant in semiconductors, software and platform ecosystems, while China continues to scale rapidly across applications, data ecosystems and hardware integration. Together, they are defining the revolution of the global AI supply chain.

“Recent performance in both markets shares a common driver: AI is one of the most transformative technological innovations in human history, marking the first time machines can replace and augment human intelligence,” said Wan at GVC. “We expect AI to remain the key theme driving bullish trends in both markets.”

The opportunity set extends well beyond mega-cap technology names. It spans semiconductors and memory, large language models and data infrastructure, as well as downstream applications such as intelligent driving and robotics. “The industry widely expects AI to reshape production and daily life, sparking an unprecedented investment race,” added Wan.

From exposure to expertise: why AI investing is different

For private wealth portfolios, AI is no longer a sector exposure, but a core allocation spanning industries. This requires exposure across the full value chain, including the providers of next-generation platforms and operating systems.

“This is particularly relevant for China’s wealthy, as they shift a greater share of their asset allocation towards more sophisticated, globally diversified and technology-focused portfolios,” said Wan.

Yet as the AI ecosystem deepens and investors’ scope widens, so too does the complexity required to invest effectively. Understanding competitive advantage now involves detailed knowledge of chip architecture, data pipelines, software frameworks and supply chain dynamics – alongside, of course, macro and geopolitical considerations.

This is where the dispersion of outcomes remains high, and where inefficiencies persist. Despite short-term trading becoming increasingly commoditised by quantitative and algorithmic strategies, long-term forecasting of technological disruption remains far less efficient.

“Identifying structural winners requires multidisciplinary insight, on-the-ground research and technical validation”, said Wan. These are areas where generalist approaches often fall short – instead, specialists capable of navigating both US and China markets are key.

Concentration driving AI alpha, not diversification

GVC’s model reflects this reality. The firm focuses on three core areas: semiconductors; software and internet; and big data and AI. Its research framework combines deep industry expertise with a broad macro overlay, supported by continuous engagement with technical specialists.

For example, its analysts engage directly with engineers, industry practitioners and technical experts, while portfolio managers integrate macroeconomics, geopolitics and trade dynamics into the investment process.

Notably, the investment process continues to evolve. Version 1.0 emphasised foresight and long-term holding discipline, with version 2.0 integrating a stronger macro dimension alongside derivatives and risk management tools, in line with the increasing importance of managing volatility and geopolitical risk.

Despite managing a relatively modest $400 million to $500 million in assets, GVC’s ambition is not scale for its own sake, but differentiation. “We remain focused on being a global specialist in technology growth stocks,” explained Wan. “The goal is not to become the largest, but to be the most distinctive and trusted partner in wealth management.”

At the core of this philosophy is a direct challenge to conventional portfolio construction, with stock selection guided by four pillars: first principles; disruptive innovation; comparative advantage; and a long-term, concentrated investment style.

• First principles – this prioritises business fundamentals over price movements or technical signals, with equity investing balancing growth and stability, shaped by industry dynamics and company strength.
• Disruptive innovation – this refers to technologies that transform industries and deliver high-risk, high-return opportunities, but with clear competitive winners.
• Comparative advantage – this approach invests in global leaders within regions which display structural strength, such as US technology.
• Long-term, concentrated portfolios – this translates into a portfolio of six to eight stocks held long term, based on research showing excess diversification can dilute returns, while long-term conviction offsets the diminishing edge of short-term trading.

“We have always believed that investing in stocks means investing in businesses,” Wan said, “partnering with founders and management teams of listed companies.”

Identifying winners early

That approach is tried and tested in how GVC applies it consistently via early-stage winners.

In electric vehicles, for instance, Wan and his team initiated a position in a leading player as early as 2016, scaling conviction in 2019 when battery energy density crossed critical thresholds and production constraints began to ease. Extensive due diligence, including site visits and expert consultation, supported the decision to build the position into a top holding, contributing significantly to returns.

Similarly, in data and AI platforms, the team identified the structural potential of a key company in this space, particularly its ontology-based data integration capabilities and the strategic vision of its founders. Following the launch of its AI platform in 2023, GVC scaled its position aggressively ahead of a growth inflection, generating returns of approximately 10-times its initial investment.

Both stocks underscore a key point: outsized returns in technology are often driven not by consensus positioning, but by early identification of inflection points – and the willingness to hold through uncertainty.

Portfolio implications: fewer bets, higher conviction

GVC’s approach reflects the likelihood that in the AI era, returns will be unevenly distributed. They will accrue disproportionately to a narrow set of companies – and to the investors willing to identify them early and hold them with conviction.

For allocators, the implication is clear: capturing AI-driven alpha is less about broad exposure, and more about backing specialist managers capable of navigating complexity, uncertainty and concentration risk across both US and China ecosystems.

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