AI is broadening
Is your technology exposure keeping up?
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Looking beyond the headline names in AI
The next phase of AI may reach well beyond mega-cap technology leaders into the infrastructure and specialist companies enabling adoption at scale. Identifying those opportunities requires deep sector insight, proximity and valuation discipline – not just exposure to the theme.
Nearly four decades of investing through technology cycles have taught a consistent lesson: leadership changes, and the biggest opportunities are not always in the names investors already own.
Twenty-eight years ago, Google had only just launched and the iPhone was still years away. Cloud computing did not exist and artificial intelligence remained largely confined to academic research.
Since then, technology leadership has shifted repeatedly. Each cycle has created new market leaders, often beyond the names investors knew best at the start.
That is why experience matters. Navigating these shifts requires company insight, sector knowledge and valuation discipline – not simply enthusiasm for a powerful theme.
Experience through every cycle
Few investment teams have worked through as many of these technology cycles as Paul Wick and his team. Paul has spent almost four decades investing in technology companies and is one of the longest-serving technology investors in the United States. Today he leads a team managing more than $47 billion1 in technology-focused portfolios.
The team includes 12 senior analysts who cover specialist areas across the technology landscape, with an average of more than 28 years of industry and investment experience. It also includes investors with direct industry experience. One example is semiconductor specialist, Shekhar Pramanick, who previously worked at AMD and generated more than 50 patents before joining Paul’s team. That practical perspective matters in a sector where change often starts inside the supply chain before it is visible in reported numbers.
Crucially, the team is based in Silicon Valley, with additional analysts working out of New York – the two hubs of technology investing in the US. This means we work alongside many of the companies driving the AI revolution. That proximity provides direct access to the management teams, suppliers, customers and engineers shaping the sector’s direction – insight that rarely reaches the wider market until much later.
1 Columbia Threadneedle Investments as of 30 June 2026.
Where the next opportunity lies
That vantage point shapes how the team sees AI today. The theme has become one of the most powerful in markets, but exposure is still concentrated in a small group of very large companies. In many portfolios, owning “AI” effectively means owning the same familiar mega-cap names.
As we argued in a recent article2, the next phase of AI value creation may be broader, extending beyond chip and cloud leaders to the infrastructure, specialist components and enabling technologies needed to deploy AI at scale.
AI is not only about processors. It also depends on the wider infrastructure that allows data to be stored, moved and processed at scale. Following that capital through the value chain is where specialist research can uncover less obvious beneficiaries.
2 Source: Columbia Threadneedle Investments, AI After the Rally: Finding the Next Layer of Technology Winners.
From theme to specific opportunity
Western Digital and Marvell Technology illustrate the point. Western Digital is exposed to the growing need to store, access and manage vast volumes of data as AI workloads expand – a less glamorous, but essential, part of the infrastructure build-out. Marvell addresses a different bottleneck: moving data quickly and efficiently across increasingly complex AI data centre infrastructure through custom silicon, networking and optical connectivity. In both cases, the investment case is not simply “AI exposure”, but whether demand, competitive position and valuation support durable growth.
The same logic extends to the physical backbone of data centres, including power management, cooling and storage infrastructure. These may not be the most obvious AI names, but they can occupy important positions in the ecosystem enabling adoption at scale.
Discipline, not excitement
Experience helps investors spot opportunities. It also helps them avoid mistakes.
As enthusiasm around AI has grown, valuation discipline has become more important, not less. Early in a major technological shift, markets often reward broad exposure to a theme. But as cycles mature, fundamentals matter more: revenue durability, margins, cash-flow generation and the ability to defend returns. Investors who have lived through previous cycles know how quickly a strong narrative can become an expensive one.
That is why the team follows a Growth-at-a-Reasonable-Price (GARP) philosophy, combining detailed fundamental research with a firm focus on valuation. Portfolio construction is driven by conviction, opportunity and risk – not benchmark weights or market momentum.
By being disciplined around valuation, the team works to avoid chasing momentum plays or overpaying for growth.
For investors already exposed to technology, the question is whether that exposure reaches the companies enabling the next phase of AI growth.
In a crowded market, proximity, sector experience and valuation discipline can make the difference between simply owning the theme and owning it well.
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