The market for artificial intelligence technologies is expected to continue to grow rapidly in the coming years. From companies leveraging large proprietary datasets to manufacturers embedding AI into operations, the technology’s disruptive impact is spreading across the global economy. This makes a broad, sector-agnostic thematic approach essential for capturing the full opportunity.
The pace of disruption across the economy is accelerating
The boundaries of the technology sector have been steadily dissolving. It is becoming increasingly difficult to differentiate between a pure technology company and disruptive companies in other sectors that are benefitting from technological innovation. The telecommunications sector was renamed communication services in 2018 to reflect the digital transformation in how society now communicates and many fintech companies have recently been reclassified to the financials sector, as many aspects of financial services also undergo a digital transformation. Two of the “Magnificent 7” companies are classified as consumer discretionary and account for approximately 40% of that sector’s market cap. These are some of the most notable examples, but technological innovations are disrupting virtually every part of the global economy and successive innovations developed by pioneering tech companies are reshaping industries.
This means that to capture the full potential of disruptive technology, it is no longer sufficient to focus on the technology sector alone. Instead, investors need to look across a broader horizon to find the best investment ideas. This might include companies that are developing or adopting innovations and applying them in their own industries, either to defend their lead or to transform their competitive position and become the champions of tomorrow.
This dynamic was already at work when AI was in its commercial infancy and in many ways still is. The technology’s rapid development is changing the game, hugely increasing the potential impact of disruption across industries and regions.
Find out more about the current artificial intelligence investment landscape
The significance of the DeepSeek shock
OpenAI’s ChatGPT, released in late 2022, was the first large language model (LLM) to gain widespread acclaim. It sparked a competitive race among the leading US AI companies: OpenAI, Google and Anthropic. New model releases have occurred every few months since 2022, with each iteration bringing advances in capabilities and reductions in computational requirements, resulting in lower operational costs per output.
Then, in January 2025, a Chinese AI lab released the first iteration of DeepSeek, a highly capable generative AI chatbot. This open-source LLM demonstrated strong reasoning, coding and inference skills in benchmark tests. But the most revolutionary aspects of the Chinese chatbot were the efficiency of its training process and the significant reduction in cost per query compared with leading US LLMs.
Although inference costs were already falling fast, with up to 900-fold annual declines depending on the task, DeepSeek gave the process fresh impetus.[1] Combined with the chatbot’s excellent performance, this changed the market’s perception of the competitive landscape nearly overnight leading to investor anxiety about the pace and trajectory of capital spending for AI, specifically the hundreds of billions of dollars being spent annually by several leading US technology companies. Since then, these companies have reaffirmed or, in many cases, increased guidance for their AI spending intentions, reassuring shareholders that the AI arms race is as intense as ever.
As noted by Microsoft CEO, Satya Nadella, falling prices will likely result in increased consumption (a phenomenon known as Jevons Paradox), so the “DeepSeek shock” and more broadly the rapid decline in cost of inferencing, has opened the door for AI to be embedded in many more applications and systems. This will spread AI’s disruptive potential further and faster, cementing its status as a general-purpose technology with immense potential to transform how businesses operate and how we interact as a society more broadly.
Even so, AI adoption is still in its early stages. A 2024 McKinsey survey found that 78% of companies had adopted AI in one or more functions or departments, up from 55% a couple of years previously.[2] But evidence of efficiency gains in the form of wider margins or increasing labour productivity remain nascent, suggesting that most organisations are still experimenting with AI to identify the most impactful use cases and that there is a long runway to disruption at the enterprise level.
Who will benefit from the spread of AI?
So far, the largest beneficiaries of AI innovations have been the companies most critical to the immense task of building the AI infrastructure. This includes the hyperscalers that dominate the cloud computing market where an increasing share of revenues are coming from an explosion of AI workloads and the select few semiconductor companies essential to AI training and inferencing. As well as industrial companies helping to build the new data centres to meet the boom in demand for computing resources along with new and existing utility companies to power the intense growth in electrical demand from AI workloads.
With hundreds of AI startups and established tech behemoths racing to be at the forefront of the AI gold rush, the demand for computing resources continues to far outstrip supply and profits for companies most closely aligned with the AI infrastructure buildout continue to see their profits pile-up at an unprecedented pace. Sequential funding rounds for AI unicorns are occurring at eye-popping valuations with capital raises far outstripping revenues. Private market investors continue to meet the insatiable demand for new money, but at some point the pace of capital investment in AI infrastructure is likely to decelerate or even decline and investors expecting uninterrupted growth will be disappointed.
Meanwhile, the investment opportunity for companies adopting AI to increase efficiency or create new products or services has barely begun. For example, AI enables software developers to write code up to twice as fast by automating routine tasks and code completion.[3]
Another highly promising area is high-quality businesses with large troves of proprietary data. Strong businesses with unique data can leverage AI to develop new products or services that lead to more revenue opportunities, improve productivity and reduce costs. Additionally, AI helps automate workflows in areas such as customer service, sales, and application development, resulting in expanded margins and higher profits.
We expect AI features to proliferate within software, potentially creating stronger engagement trends for those that execute well. We also believe that software development tools, database software and cybersecurity systems are critical components of the digital infrastructure required to support AI initiatives. AI algorithms are software and can be developed and managed with the same tools used for traditional applications. Enterprises have an incentive to upgrade their legacy database software with modern systems that can handle both structured and unstructured data. Cybersecurity is also key to protecting algorithms and data from attacks and cybersecurity systems are incorporating machine-learning techniques to better identify and thwart threats.
Why a thematic strategy makes sense
The spread of AI and technological innovation across industries offers a textbook use case for a thematic investment approach. By applying a thematic lens to disruptive technology trends, a broader opportunity set provides a sound framework for investors looking to capitalise on its economy-wide impacts.
Our Disruptive Technology strategy is agnostic to region, market cap and sector. It instead seeks opportunities across multiple industries, from technology to healthcare, energy, industrials, financials and consumer companies.
The strategy looks for companies that are financially resilient and environmentally sustainable; have a strong competitive position; and are attractively valued. These three pillars effectively commit us to an investment style that combines a top-down evaluation of the themes driving global innovation with a disciplined bottom-up approach to fundamental stock research and portfolio construction. This framework results in a concentrated, high conviction portfolio with lower volatility than many other technology products available on the market.
Because we expect to hold positions for the long term, we put great emphasis on assessing the strength of each company’s competitive positioning and its ability to sustain that advantage. This means focusing on areas such as economic model strength through network effects or scale benefits, proprietary intellectual property and other barriers to entry. We also put significant emphasis on valuation for securities that we purchase, which requires a disciplined process that assesses companies primarily using discounted cash flow analysis, which we find most appropriate for evaluating businesses with high rates of long-term cash flow growth.
Our core investment themes and the technologies to watch
Technology is constantly evolving, but our focus remains anchored in four core themes: AI, cloud computing, the “internet of things” (edge computing) and automation. We’ve been committed to these themes since 2017, but within this framework, we take a flexible approach that also encompasses emerging areas that we want to stay close to as they develop. For example, we may consider investments in quantum computing and autonomous vehicles. Complementing our analysis across these themes are the foundational technologies that enable developments like AI and automation, including semiconductors, cybersecurity and technological infrastructure.
The spreading impact of AI is reflected in our portfolio composition: we estimate that almost 95% of our portfolio holdings are linked to the AI theme to at least some degree, with a mix of AI developers, foundational tech, data plays and AI beneficiaries – companies spread across a variety of industries that we expect to benefit from the adoption of externally developed AI tools.
By focusing end-to-end on the AI supply chain and searching across the global equity universe for underappreciated companies benefiting from AI exposure and the digital transformation of the economy and society, our Disruptive Technology strategy identifies compelling investment opportunities poised to win in the age of AI. Find out more about how we are capturing the many upsides of this exciting theme.
[1]https://epoch.ai/data-insights/llm-inference-price-trends
[2]https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai?form=MG0AV3&utm
[3]https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/unleashing-developer-productivity-with-generative-ai
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