Seeking out AI’s next winners

Artificial intelligence is driving one of the largest investment cycles in decades. The companies building the infrastructure that underpins AI – from semiconductors and manufacturing equipment to cloud platforms and data centres – are attracting significant attention as organisations invest heavily to develop and deploy the technology.

However, history suggests that the ultimate beneficiaries of transformative technologies are not always the businesses supplying the tools. Electrification created substantial opportunities for power providers, but its broader economic impact came from the companies that successfully applied it to improve productivity and strengthen their competitive positions. AI may prove to be no different.

For long-term investors, the key question is therefore where AI will have the greatest economic impact. While the foundations remain essential, some of the most compelling opportunities may emerge among businesses using AI to improve customer outcomes, operate more efficiently and reinforce strengths built over many years.

Laying the foundations

Understanding that opportunity begins with the infrastructure enabling AI today. The scale of investment is unprecedented, with the world's leading technology companies expected to invest approximately US$730bn in capital expenditure in 2026 alone, much of it directed towards AI infrastructure. Every dollar invested creates demand across a much broader ecosystem, from semiconductor manufacturing and cloud computing to data centres, cybersecurity, industrial automation and the businesses that will use AI to operate more efficiently.

Much of the market's attention has focused on the companies developing the technology. Nvidia, TSMC and ASML sit at the centre of the semiconductor ecosystem underpinning AI, while Amazon and Microsoft are investing heavily in the infrastructure required to develop and deploy the technology. These businesses are likely to continue to play an important role in AI's development.

Once the computing platforms have been built, AI adoption depends on a much wider network of physical and digital infrastructure. Every new data centre requires substantial investment in the facilities and systems that support its operation. Networks must be secured. As AI moves beyond the data centre, intelligence needs to be embedded into factories, vehicles and industrial equipment.

Ferguson demonstrates how the AI investment cycle extends well beyond the technology sector. The build-out of data centres is supporting demand for a wide range of construction and infrastructure products where the company has established distribution capabilities. As the installed base expands, ongoing maintenance, repair and upgrade activity may create demand throughout the asset lifecycle.

Alongside this physical infrastructure sits an equally critical digital layer. As organisations deploy AI more widely, protecting data, applications and networks becomes more important. In our view, this should support long-term demand for Fortinet's cybersecurity solutions as businesses secure increasingly complex digital environments.

Meanwhile, AI's influence is extending beyond data centres and into a growing range of real-world applications. Texas Instruments, a leader in analogue and embedded semiconductors, provides the chips that connect digital intelligence with real-world devices. As AI capabilities are deployed across factories, vehicles, healthcare equipment and industrial systems, we expect demand for these components should grow.

From infrastructure to adoption

The companies building AI infrastructure remain essential to the ecosystem's development. However, history shows that as new technologies mature, value creation often broadens beyond the businesses supplying the tools. The ability to apply technology effectively can become just as important as the technology itself.

AI in the real economy

Intuit illustrates this well. The company is embedding AI across its financial software ecosystem, helping small businesses and consumers automate routine tasks, improve decision-making and operate more efficiently. By incorporating AI into products customers already use every day, Intuit is enhancing customer outcomes while strengthening the value of its platform.

The same principle extends beyond software. EOG Resources is using machine learning and advanced analytics to improve drilling, production and reservoir management, helping the company operate more efficiently and make better-informed decisions.

Similarly, Xylem is combining sensors, software and operational data to help utilities identify leaks, improve efficiency and make better use of increasingly scarce water resources. Meanwhile Mettler-Toledo is enhancing its precision instruments with intelligent software and data capabilities. And leading US less-than-truckload freight carrier ODFL is using technology and automation to optimise network planning, improve service levels and increase operational efficiency.

What makes a long-term AI winner?

While these businesses operate in different industries, they share attributes that may become more important as AI adoption expands. These include proprietary data, deep operational expertise, strong customer relationships and established market positions.

AI is often most powerful when combined with advantages that are difficult to replicate. Rather than disrupting such companies, it may reinforce their competitive positions by improving decision-making and enhancing customer outcomes.

AI is driving one of the largest investment cycles in decades, but history suggests that the most enduring beneficiaries of transformative technologies are not always the companies building the foundations. As adoption broadens, the ability to apply AI effectively may become just as important as developing the technology itself.

For long-term investors, this reinforces the importance of looking beyond today's headlines. In our view, some of the most compelling opportunities may lie with businesses that can use AI to strengthen established competitive advantages, improve customer outcomes and enhance productivity. Where new technology meets enduring business quality, the potential for long-term growth may be greatest.