Accelerating the AI revolution: powering what comes next
The first wave of artificial intelligence euphoria has carried the Magnificent 7 to new highs and to increasingly lofty valuations. While AI-related investment in computing power and data centres rises inexorably amid a race for large language model dominance, we see this investment surge as a potential risk for investors. We prefer to target two other fast-growing areas of AI-related technology that are now attracting significant and lucrative investments: i) electricity generation, transmission infrastructure and cooling systems to support the escalating demands of AI data centres, and ii) Agentic AI, the next generation of AI that can learn autonomously, make decisions with flexibility and independence, and adapt to new situations. While automation and robotics still have significant potential for growth, Agentic AI is set to impact virtually all industries, enabling innovative applications and use cases.
Our recommendations
A theme focused on AI’s next stage and what it will require.
- Power generation, transmission infrastructure, energy storage (batteries)
- Nuclear power
- High-end chips designed for data transfers, storage and computing; sensors
- Certain metals and special materials, such as copper, lithium, aluminum, titanium, lightweight composites, some rare earth elements
- Efficient cooling systems, water-related technologies
- Cybersecurity
- Robotics and humanoids-related hardware and software
- New (Agentic) AI applications in healthcare, finance and other industries.
Key risks
- AI adoption and monetisation are slower than expected, especially if some of the bottlenecks we mention in this theme turn out to be complex to resolve.
- Massive investment by hyperscaler companies in AI may result in poor ultimate returns on investment due to intense global competition. If returns on investment are lower than anticipated, the rollout of AI could be delayed.
- A recession could lead to a reduction in AI budgets, potentially hindering the progress of AI implementation and slowing down the realisation of the potential benefits.
- Security aspects likely to become more important in the whole AI ecosystem.
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