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The new frontline: from AI build-out to ecosystem dominance
key takeaways.
The battle for AI supremacy between the US and China is creating wide-ranging opportunities to invest in the critical infrastructure that will underpin the 21st-century economy
The ultimate winners, though, may be those countries and companies with the strongest ability to translate AI breakthroughs into a fully functioning AI ecosystem
Our strategies offer diversified, specialist exposure to evolving AI build-out and adoption, from convertible tech bonds and Asia equities to private infrastructure.
In the space of a few years, artificial intelligence has evolved from a theoretical construct into a transformative, real-world technology. The countless implications across productivity, national security, and political power and influence mean the battle for AI dominance will have a lasting global impact.
The prize at stake can hardly be overstated. Owning the critical hardware, software and data infrastructure of the 21st century will let the winners write and impose the AI rulebook, setting standards and creating legal frameworks others must follow. Their control over the AI supply chain will be used as powerful strategic leverage – commercially, politically and even militarily.
Other nations risk becoming economically dependent on foreign tech giants – and geopolitically dependent on one or other of the AI superpowers. As a result, governments are increasingly prioritising control of AI infrastructure and technology.
However, that’s only one phase of the race. Over the longer term, countries that can create the most effective ecosystem for widespread adoption may have the lasting competitive advantage.
For the US and China, AI has rapidly evolved into a contest for international power and influence. However, the two superpowers have taken quite different approaches.
US: an early lead protected by control over advanced IP
Strengths: The US got a head start thanks to investment by the major tech companies and the exertion of political influence over key elements of the supply chain. The world’s largest economy controls a significant part of the critical development stack, including top AI research labs and supplies of the advanced chips essential to frontier AI. America leads the world in AI cloud infrastructure and is the main focus of private investment in new technology.
Weaknesses: The US depends heavily on global supply chains for AI hardware, while grid infrastructure constraints threaten to limit the pace of data centre build-out. Large-scale data centres also face a growing public backlash.
China: gaining fast thanks to cost-efficient open-source models
Strengths: China has embraced a more open AI strategy that benefits from strong government backing, a large talent pool, and abundant data and electricity. The recent release of Moonshot AI’s Kimi K3 large language model (LLM)1 has demonstrated the strength of this approach, closing the performance gap.
Weaknesses: With the US limiting exports of cutting-edge chips, China lacks the semiconductors that can provide optimal AI performance. However, state policy support and investment in domestic chips and compute aim to make China self-sufficient.
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Frontier AI models: the US leads through OpenAI, Anthropic, Google DeepMind and SpaceXAI, but Moonshot AI’s Kimi K3 shows China is hot on its heels
Compute and data centres: a larger infrastructure and data centre footprint gives the US a key advantage, but China is adept at rapid, large-scale infrastructure build-out
Semiconductors and GPUs: in partnership with European and Asian allies in manufacturing technology and production, US companies dominate advanced AI chip design and much of the AI software ecosystem; however, China’s chipmakers are catching up
Open-source models and cost efficiency: China is increasingly strong here, with companies including DeepSeek and Alibaba offering highly capable open-source LLMs at relatively lower cost.
How do LOIM strategies capture the AI theme?
Global Convertible Bonds: exposure to AI innovation with reduced risk
Companies acting as disruptors have historically made effective use of convertible bonds to fund growth. For investors, convertibles issued by tech firms provide stable income while offering the option to convert to equity to gain exposure to AI innovation.
Our highly experienced global convertibles team is dedicated to the asset class, with a robust, scalable approach. It focuses on maximising risk-adjusted returns from key sources of growth and innovation, including electrification and AI.
The battle for AI dominance is creating investment opportunities across the technologies and infrastructure needed to train and run LLMs at scale. Major tech companies are borrowing record amounts for this purpose: as of July 2026, year-to-date investment-grade bond issuance by hyperscale tech firms across all currencies was broadly comparable to UK government gilt issuance over the same period.2
This is being spent on capex across semiconductors, data centres, cloud infrastructure, electricity networks and power generation. Many immediate beneficiaries are traditional ‘pick-and-shovel’ firms involved in the construction and fitting out of physical infrastructure. Meanwhile, cybersecurity and digital resilience are rapidly emerging as further critical areas of investment.
FIG 1. Each link is an opportunity: behind every AI answer lies a chain of essential businesses3
How do LOIM strategies capture the AI theme?
Asia Equities: invest in the region at the epicentre of the revolution
Asia is the engine room of the global AI infrastructure boom, providing advanced chips and supporting hardware along with the renewables tech needed to power AI growth. At the same time, Asian companies are well placed to benefit from increasing regionalisation.
Asian technology, industrial innovation and critical minerals are core themes across our Asia High Conviction and Emerging Market High Conviction strategies, offering access to structural growth opportunities.
Read more about Asia High Conviction here and Emerging Market High Conviction here
The next phase: who will be best at AI diffusion?
Today's AI landscape is defined by competition to build ever more capable models. However, in the longer term, leadership in the technology will most likely be decided by effective diffusion: the ability to deploy practical AI applications widely across the economy that can enhance productivity and innovation.
As yet, this diffusion of AI across economies is still in its early stages. The commercial rollout of agentic AI, characterised by its interactivity, connectivity, ability to learn and autonomy, marks a new phase of growth. Yet while adoption is accelerating, demand is overwhelming supply, with the majority of use cases remaining largely untapped. At the same time, news reports have highlighted how providing unrestrained access to powerful AI models is not necessarily an instant route to budgetary efficiency4.
The next phase of AI’s development is therefore likely to be a marathon rather than a sprint, with success defined by the ability to implement AI effectively at scale across industries and government organisations in a way that maximises benefits and minimises costs.
The next phase of AI’s development is likely to be a marathon rather than a sprint, with success defined by the ability to implement AI effectively at scale
Learning from history: what electricity and computing teach us about AI’s future
The development of AI is likely to follow a similar pattern to past innovations. Electricity and computers only delivered major economic gains once they had been embedded across a wide range of real-world applications.
History is replete with examples of how the greatest fortunes are made not by the companies that develop the underlying technology, but by those that put it to effective use in disrupting existing sectors.
Initially, the internet was something of a novelty. It became transformative as companies such as Amazon (retail), Google (advertising) and Facebook/Meta (social interaction)1 applied the technology to everyday activities at scale and reinvented industries.
Identifying AI’s economic winners
The ultimate winners from the AI revolution will be those countries that can develop and effectively deploy AI, while securing critical supply chains and managing the inevitable disruption.
Success will depend on a range of interdependent factors, including:
Talent: access to, and development of, skilled researchers and workers
Capital: government investment and access to private finance
Resources: advanced chips, data centres, energy, water and raw materials
Government support: effective policies and regulation to guide adoption
Public support: voter enthusiasm and belief in the benefits
Labour: the ability to retrain workers and manage workforce disruption
Beyond the US and China, other countries may gain significant economic and geopolitical advantages. This can be achieved by controlling key AI inputs, or by becoming particularly effective adopters of the technology.
Europe: While it has lagged far behind on model development, Europe could become a ‘smart second mover’ by focusing on AI adoption, industrial automation, healthcare and regulation.5
India: The world’s most populated nation benefits from strong digital infrastructure, a large talent pool and data resources; however insufficient energy resources and limited data centre build-out present challenges5.
The United Arab Emirates, Singapore, Norway, Ireland, France and Spain: These countries have invested in digital infrastructure and skills development. Interestingly, a recent Microsoft report found that the US lags behind these nations in terms of AI use in the working-age population.6
Beyond the US and China, other countries may gain significant economic and geopolitical advantages
Global Infrastructure7: investing in the growth of AI data centres
Technology build-out is a primary focus for Global Infrastructure, along with the linked themes of energy and the consumer. The strategy invests directly in data centre infrastructure, and it also provides exposure to the rollout of electrification that supports AI growth, including renewable power generation, grid expansion and battery storage.
Core infrastructure combines long-term growth potential with relatively predictable income streams, in our view. Many assets are costly and difficult to replicate, giving them a durable competitive advantage.
Where untapped opportunities lie
Critical infrastructure is the current frontline of AI development, with the US and China locked in a battle for supremacy. The race to develop more advanced models and build out the required compute is reshaping the global investment landscape, creating opportunities across industries powering the AI revolution.
Over time, the winners of the race may be those with the strongest ability to translate AI technological breakthroughs into broad-based economic value creation.
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Preference Centre
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1 Any reference to a specific company or security does not constitute a recommendation to buy, sell hold or directly invest in the company or securities.
3 Sources: Bernstein Research (Mar & Jun 2026), Morgan Stanley Research (Apr & Jul 2026), UBS Global Research (Jan 2026). Figures are third-party sell-side estimates as of the dates shown. For illustrative purposes only. Any reference to a specific company or security does not constitute a recommendation to buy, sell hold or directly invest in the company or securities.
4 ‘Uber Burns Its 2026 AI Budget In Four Months On Claude Code’, published by Forbes, May 17, 2026. https://www.forbes.com/sites/janakirammsv/2026/05/17/uber-burns-its-2026-ai-budget-in-four-months-on-claude-code/
5 AI’s Economic Winners: Council on Foreign Relations, published 29 July 2026
7 Lombard Odier Global Infrastructure is a hybrid primary and co-investment strategy in partnership with Macquarie AM.
important information.
For professional investors use only
This document is a Corporate Communication for Professional Investors only and is not a marketing communication related to a fund, an investment product or investment services in your country. This document is not intended to provide investment, tax, accounting, professional or legal advice.
