What investors are asking…

We believe investing in technology is compelling for three key reasons: i) technology stocks have the best fundamentals of any sector – not just growth, but the highest return on invested capital (ROIC), free cash flow margins and lowest leverage; ii) technology stocks have a strong long-term historical returns profile, underpinned by strong growth in earnings; iii) we are at the beginning of a new technology cycle driven by AI that we expect to generate strong earnings growth over the coming years.

As with any investment, technology stocks have risks. They can be volatile and subject to swings in sentiment and macroeconomic and financial conditions.

Moreover, not every great technology or innovation is a good investment. To minimise this risk, we seek to invest in technology companies that i) create high value for customers through innovation; ii) capture value for shareholders through barriers to competition; iii) have good management; and iv) generate strong returns on capital.

AI is in its early stages and therefore while there is huge potential, there is also the heightened risk to investors of backing the wrong horse. This requires a flexible mindset and investment process and the willingness to change one’s views as the facts on the ground change.

The Global Innovation team primarily considers four factors: value creation through innovation, value capture through barriers to competition, good management, and strong returns on invested capital.

If a company meets our requirements on these four characteristics, then we consider including it in our Global Innovation 200 universe. Inclusion in the funds is then determined by valuation upside. We seek to buy companies in a cyclical downturn where possible.

We seek a persistently high strong return on invested capital (ROIC) and for more established companies and an upward trajectory in ROIC for companies earlier on their journey. Across all companies, we demand a sound balance sheet, particularly a healthy net debt to EBITDA (earnings before interest, taxes, depreciation, and amortization) ratio.

We view AI as a general purpose technology, meaning the potential productivity gains are everywhere. Quantitatively, it is of course difficult to project the coming impact but estimates from Mckinsey suggest that generative AI could ultimately add $2.6 trillion to $4.4 trillion to the global economy annually, while Goldman Sachs believes that AI could eventually increase annual global GDP by 7%. Although the projections of generative AI’s productivity boost vary (with some forecasting as much as a 14% global GDP boost by 2030), the direction and significance of the uplift is widely accepted.

Crucially, we believe AI has the potential to enable certain companies to both create and capture value, our key requirements for the potential of innovation to drive stock returns.

The US is currently leading the AI race but will by no means be the sole beneficiary. Europe has led the effort to regulate AI across developed nations, Canada has been the first country to announce a national AI strategy and the UK is investing heavily in AI infrastructure, including a $100 million strategic investment in semiconductor procurement. In Harvard Business Review’s ‘top ranked AI nations’ index, the UK sits in third position (behind the US and China), with Germany and France coming in fifth and sixth positions respectively.4

Mega-cap technology companies may reside in the US, but companies that enable and benefit from AI can be found across the world. ASML, a Dutch leading supplier to the semiconductor industry, has a virtual monopoly in the production of extreme ultraviolet lithography machines (which pattern the tiny details on advanced microchips, including AI chips). Beyond European technology companies, L’Oréal is pioneering ‘beauty-tech’ through harnessing AI.

AI sits on the shoulders of the past three major information technologies – the internet, mobile and cloud – which means that some of the leading companies in these technologies (including the Magnificent 7) are currently leading in AI and already generating incremental profits. For example, Nvidia (with around 85% AI-related revenues) generated over $6 billion in net profit last year, while Broadcom (with around 25% AI-related revenues) generated over $14 billion in net profit. Moving up the tech stack, although value creation will take time to disperse up to the software application layer, pioneers in AI like Adobe and Salesforce are already successfully monetising AI.

While there are always over and undervalued companies in the market, we believe that overall current technology valuations are justified by fundamentals. Although AI is sometimes compared with the 2000 dotcom bubble, valuations are nowhere near the levels reached in that episode. In 1999, the S&P 500 IT sector traded at a forward price-to-earnings ratio of 75 times, representing a 3 times premium to the overall market; today, the S&P 500 IT sector trades at about 28 times and a 1.4 times premium to the overall S&P 500 index and the Nasdaq 100 index trades at a 1.3 times premium.We believe the current valuations are justified given strong fundamentals (the technology sector has the highest ROIC and lowest leverage of all sectors) and superior growth, which will be further aided by AI tailwinds.

General purpose technologies such as AI impact most sectors, not just technology companies. Business use cases among those that stand to benefit the most from AI fall across four areas: customer operations, marketing and sales, software engineering, and R&D – functions that span the vast majority of companies across industries.

Life sciences is a sector that could see the biggest impact as a percentage of revenues. For example, drugs could be discovered and validated much faster using AI. Meanwhile, AI prompts are also helping to drive digital sales for consumer-facing brands such as McDonald’s, and the role of virtual assistants present meaningful opportunities for customer-engagement heavy platforms like Airbnb.

The Magnificent 7 companies are at the forefront of AI. Having suffered significant stock price declines in 2022, they had a strong 2023 as the new technology cycle began. While it is rare for the leaders of a previous cycle to transition successfully into the next one, these companies are well-positioned to benefit from AI due to their leveraging of the internet, mobile and cloud, and their access to data, capital and innovative capabilities.

Yet, the opportunities in AI extend beyond the tech giants. AI will have broad and transformative effects. We expect companies far below the Magnificent 7 to compete in many different ways. Their agility and ability to start from scratch, alongside the open-source nature of AI tools, allow them to focus on niche AI areas, develop unique applications, or solve specific problems.

Generative AI is a significant step forward in AI capabilities. While standard AI uses data to make predictions, such as recommendations for consumers based on data on their previous and other activity, generative AI uses data to create original content, in the fields of language, imagery, sounds and video.

The increased capabilities of generative AI over and above those of standard AI lie crucially in its ability to contextualise text and other data. This in turn has been enabled by rapid progress in computing power and methodological developments in handling natural language in all its complexity, particularly the introduction of the Transformer model in 2017.

The emergence of generative AI means that AI has become applicable to a much larger range of tasks than before and is likely to have much larger effects on economic activity.

Businesses that delay AI adoption risk falling behind competitors that do not delay. Conversely, embracing AI brings its own set of challenges, including the need for significant investment in technology and talent, the high energy intensity associated with accelerated computing, potential biases in algorithms, and navigating data privacy and ethical use.

From a social perspective, risks include the misuse of AI by bad actors, such as in cybersecurity breaches, deepfake creation, and digital scams, underscoring the need for robust ethical and safety regulations. AI is likely to displace jobs but also drive economic growth and create new opportunities.