We use cookies to collect statistics. By clicking OK you accept the use of statistic cookies. You can decline the use of statistic cookies by clicking here. Find out more about our cookie policy here.OK

Showcasing AI Portfolio Exposure

View PDF

Key Takeaways
• AI’s transformative potential is increasingly evident across different sectors and industries.
• The future winners in AI are yet to be discovered.
• We have broad exposure and are well-positioned in our portfolios to leading companies exploiting AI technology.
• The question is: When will AI repeat the pattern of internet development in terms of earnings growth?


Artificial intelligence (AI) has experienced a significant amount of hype and has, understandably, accelerated rapidly throughout society and the business world. AI has the potential to revolutionise the way businesses and society operate, and it’s already doing so in many ways. For companies specifically, the advantages of developing and applying AI are numerous and potentially far-reaching. From enhancing data analysis and personalising customer experiences to optimising operations and boosting efficiency, AI is a powerful technology tool that can transform businesses across various industries. As AI technologies evolve and become more accessible, companies that harness their capabilities will be better equipped to thrive in a competitive, datadriven, and rapidly evolving business world. Businesses must embrace AI and invest in its potential to unlock new opportunities and gain a competitive edge. Let’s take a brief look at the many opportunities that AI addresses:


1. Increased productivity
AI can automate repetitive and time-consuming tasks, enabling employees to focus on more strategic work. For example, AI can automate customer service inquiries, generate reports, write speeches and articles, and treat invoices. AI can, in other words, streamline various operational processes, reducing the need for human intervention. This can lead to significant cost
savings and increased productivity.

2. Improved decision-making
AI can analyse large amounts of data to identify patterns and trends that would be difficult or impossible for humans to detect. Traditional data analysis methods often fall short when dealing with large datasets, but AI algorithms can process, categorise, and extract valuable insights from mountains of information in real time. This can help companies make better decisions about everything from pricing and marketing to product development and risk management.

3. Enhanced customer experiences
AI can be used to personalise customer experiences, providing them with the information and products they are most likely to want. AI can also provide 24/7 customer support and resolve issues quickly and efficiently. By leveraging AI-driven recommendation systems, chatbots, and predictive analytics, companies can tailor their products and services to individual customer preferences. This not only increases customer satisfaction but also boosts customer retention and loyalty.

4. Intelligent manufacturing and healthcare
Manufacturing companies can integrate AI into machines and robots to automate tasks, increase energy efficiency, improve quality control, and predict maintenance needs. AI can also be used to develop new products and processes and will, in one way or another, become indispensable in the factory of the future. In healthcare, AI can be used (and is already used) to improve patient care, analyse medical images, diagnose diseases, and develop personalised treatment plans.


Interesting for investors
These are just a few examples of the implications of AI’s accelerated arrival, both now and in the future. AI will likely rapidly transform the business landscape, and companies adopting AI technologies will gain a competitive advantage. For investors, it, therefore, makes sense to be positively disposed towards AI in the portfolio.

Here, we will focus on our Global Equities strategy – a high-conviction, concentrated portfolio of 30 carefully selected high-quality stocks from around the globe. As seen in figure 1 below, several companies in the portfolio are exposed to developing and leveraging AI on various levels such as semiconductor chips, infrastructure, data, and applications.


Semiconductor chips
In this segment, we find company exposures to HOYA, ASML, Samsung, and TSMC. Let’s highlight TSMC (Taiwan Semiconductor Manufacturing Company), the world’s largest contract manufacturer of semiconductor chips that power our phones, laptops, cars, watches, refrigerators and more. Semiconductor chips are a fundamental component of AI hardware, including graphics processing units (GPUs) and application-specific integrated circuits (ASICs) designed for AI and machine learning tasks. Companies involved in AI research and development often rely on semiconductor manufacturers like TSMC to produce high-performance chips that power AI systems. TSMC’s advanced semiconductor manufacturing processes contribute to producing powerful and energyefficient chips, making them valuable for AI applications. AI technologies, profound learning, and neural networks demand significant computational power, and TSMC plays a vital role in meeting this demand.


Infrastructure
Amazon, Alphabet, and Microsoft are examples of portfolio company exposures. Here we will highlight Alphabet, Google’s parent company. In its efforts to develop better search solutions, Google uses AI algorithms extensively in its search engine and advertising systems. Machine learning helps improve search results and enables more targeted and personalised advertisements based on user behaviour. Alphabet is also involved in quantum computing through its “Quantum AI lab” (source: Alphabet.com). Quantum computing has the potential to accelerate AI computations significantly.


Data
In this segment, we find S&P Global, Aon, and Adobe. Aon is a professional services and management consulting firm offering a range of risk-mitigation products. Financial institutions are uniquely positioned to realise value from AI, given their vast data stores. For Aon specifically, it uses AI tools to analyse vast amounts of data and identify patterns that can help the company better assess and manage client risk (source: AON. com). For instance, Aon uses AI models to break down historical claims data, current market conditions, and emerging trends to predict potential risks and develop tailored risk mitigation strategies. AI is also employed to detect and prevent fraudulent activities, protecting Aon’s clients and their assets. AI models can analyse transaction patterns, identify anomalies and flag potentially fraudulent activities for further investigation.


Applications
Here, portfolio companies include Microsoft, Keyence, and again Adobe. Adobe, specifically, integrates AI in various ways in its products and services. One of the examples is Adobe Firefly, a generative AI tool that lets you create images, text effects, and color palettes from simple text prompts in over 100 languages. You can use Firefly with Adobe Photoshop, Illustrator, and other Creative Cloud apps to enhance creativity and explore new possibilities. Adobe Sensei, the company’s AI and machine learning platform, is used to power many of Adobe’s products and services. For example, Adobe Sensei automatically tags and organises images in Adobe Lightroom. Adobe Sensei also automatically generates alt text for images in Adobe Experience Manager.

Like Microsoft’s Co-Pilot, Adobe has developed an AI-powered virtual assistant called Adobe Assistant. It is designed to help users navigate Adobe’s products and services more efficiently. In that way, AI functions almost like Gyro Gearloose’s little helper, as many may remember from the Donald Duck universe.


Industrial AI with purpose
Regarding the triangle illustration in figure 1 (please see PDF), we only talk about the lower part of the food chain. Several other companies in the portfolio (if not all) are expected to implement AI at various levels throughout their corporation. Just think of Siemens with its digital industries and innovative infrastructure divisions. The company has developed “Siemens Lab,” an exploration platform that leverages the potential of Responsible AI to validate and implement “Industrial AI with purpose”
solutions (source: Siemens.com).

An example from the world of healthcare is Novo Nordisk. The company aims to utilise large amounts of data and artificial intelligence to discover new groundbreaking treatments for lifestyle diseases. The pharmaceutical giant announced in a press release (25th of September 2023) that it has entered into a collaboration agreement with the American tech company Valo, with an initial value of USD 60 million. Depending on the success of the collaboration, the agreement could potentially reach up to USD 2.7 billion. Valo possesses an AI-based platform that leverages patient data to discover and develop new ways to treat diseases.


Waiting for the AI breakthrough
Many industry experts have predicted that AI will be as revolutionary as the advent of the internet was over 20 years ago. The question arises whether AI will be Internet 1.0 or 2.0 regarding corporate earnings.

As seen in Fig. 2 (please see PDF), ten years transpired before the internet truly made an earnings impact, and a multitude of companies could leverage its benefits to outperform the market in terms of earnings. Although the roll-out of the Internet during the first 10 years brought about significant changes, Internet 1.0 did not materially impact the corporate earnings landscape. It was only in the second decade, Internet 2.0, when companies like Netflix, Spotify, and Amazon, just to mention a few, leveraging the Internet to create disruptive business models that left others as a dying breed: think of Blockbuster and record stores, for example.

The profitability path of AI toward a potential increase in corporate earnings seems to be shorter compared to the development of the internet. However, many AI platforms like ChatGPT, Bard, or Bing have mainly incurred costs so far in their buildout phases. The real profitability test will come when they leverage the built intelligence and data to create value and generate earnings. Therefore, the real winners and beneficiaries in the AI race are yet to be found.

Progress over the next few years will be fast-paced, and it will be interesting to see how the landscape unfolds and what innovative business models will emerge with AI at the core. Given the rapid development within AI forecasts about the future trajectory are inherently uncertain, but as illustrated in Figure 1 (please see PDF), several of our portfolio companies are already well-positioned within the AI landscape, and we expect them to be at the forefront of capitalising on also top-line growth and enhancing their earnings growth profiles.

You might also find this interesting: