Investors can access long-term technology growth without concentrating exposure in the largest US mega-cap stocks, said Anthony Ginsberg, CEO of GinsGlobal Index Funds, spoke at the HANetf Investment Conference in London last week.
Ginsberg cautioned against equating strong AI earnings with a broader endorsement of heavy exposure to a handful of dominant names. Instead, he outlined the case for diversified access to structural technology themes.
He highlighted an equal-weighted approach spanning multiple technology sub-sectors, including AI, robotics, fintech, blockchain, cloud computing, clean energy, defense technology and cybersecurity.
Unlike traditional tech benchmarks that are dominated by a limited number of companies, the approach reduces concentration risk while maintaining exposure to global innovation. Ginsberg stressed that technological leadership is not confined to Silicon Valley and that meaningful innovation is taking place across Asia, Israel and other global markets.
Technological convergence emerged as a key theme during the session. “AI, cloud infrastructure and cybersecurity are increasingly interdependent, creating overlapping growth opportunities across industries,” said Ginsberg. The development of digital infrastructure and computing capacity reflects structural demand rather than speculative excess, he added.
Addressing comparisons with the late-1990s technology bubble, Ginsberg said today’s technology leaders operate with more established revenue models, stronger balance sheets and clearer commercial pathways. While acknowledging that not all AI-related companies will succeed, he suggested that diversified thematic exposure can reduce the risk of backing the wrong segment at the wrong time.
He also pointed to defence technology and quantum computing as areas likely to attract sustained investment.
For European investors already heavily allocated to US mega-cap stocks through passive strategies, he suggested a more globally diversified framework could provide access to emerging technologies without increasing single-stock dependency.