Why Invest in Automation and Artificial Intelligence?
Artificial intelligence (AI) has the potential to be the next general-purpose technology around which much of the world will be reordered. The integration of AI, automation and massive connectivity into industrial processes, will power the next industrial innovation cycle, commonly referred to as Industry 4.0. These once-in-a-generation developments are starting to power societal change, ecological improvement and corporate returns, and it is around these themes that the Polar Capital Automation & Artificial Intelligence Fund positions itself.
AI has been a nascent technology for many years but is beginning to pervade all aspects of life. With progress accelerating due to unprecedented access to computational power, near-limitless data generation and exponential improvements in deep neural networks, we are seeing benefits expand beyond the technology universe into everyday and non-conventional settings. Hence, the opportunity to invest in stocks undergoing significant growth cycles and business model change is also expanding dramatically.
There are four key themes in the AI and automation value chain around which the Fund invests: Industrial automation; robotics; AI and machine learning (AI/ML); and material sciences. Industrial automation and robotics are two well-established technologies, but they have the bandwidth to grow significantly. As much as 90% of the 60 million machines installed globally are not currently connected1 and the potential insight that could be gained from the data generated is lost. The development of technologies around the Internet of Things (IoT) – web-enabled devices that can connect to each other and share data across platforms – means that this value can be recaptured, driving improvements from the factory floor right up to product innovation. The industrial IoT is the cycle of innovation that will revolutionise 20th century robotics and industrial technology to meet the demands of the 21st century. With unplanned downtime in the automotive sector costing $22,000 per minute, the cost saving opportunities of connecting robots and utilising predictive maintenance to minimise breakage is just one example of the potential on offer.
We look for the downstream beneficiaries of these technologies, those outside the traditional technology universe that stand to grow their profitability as these generational changes come to fruition.
AI and machine learning allow companies to move to a new standard of analysing data and extracting value from their assets, both physical and digital. The evolution of trade from the buying and selling of physical goods to an increasingly digital economy has created a vast trove of data covering all aspects of commerce and operations. The next step is to take these rapidly growing datasets and utilise them to drive innovation, increase efficiency and empower this data as a source of societal and corporate profit.
Google has been one of the most successful and well-known developers and users of AI, both internally and externally, and has been a testing bed for capabilities that later emerge as commercial ventures. Cooling the datacentres that power vast swathes of the internet has long been a complex and energy-intensive problem, given that the physical interactions involved react in non-linear ways that are hard to model. By applying their DeepMind machine learning to their own datacentres, Google was able to reduce energy consumption of the cooling systems by 40%2.
This is just one of the most tangible breakthroughs of the past few years, but we are seeing use cases emerging across a wide range of settings. Our preferred exposure through public equities to date has been focussed on the enablers, companies whose products are used in the training and inference processes. Going forward we see great opportunity in the beneficiaries, non-tech companies whose business models can be enriched or dramatically changed by AI adoption.
Certainly, the intent to embrace these technologies already exists and is growing; in a 2019 survey, AI and ML implementation was the second highest priority IT spend for companies3, behind only cloud computing deployment. More than half (56%) of enterprise CIOs intended to implement AI/ML in some form and this has been increasing 5% per annum.
Our final overarching theme, material science, encompasses all the leading-edge science and materials that power these transformational technologies. We see many opportunities for companies that have the complimentary capabilities required, whether they are more traditional technology players or those that are leveraging existing but previously unrelated technical capabilities to power a new wave of material development. We look for inflection points for new materials, whether through accelerated adoption or widening the scope of applications. Specialist lightweight materials and those geared toward 5G implementation have been key themes to date.
As a result of these emergent technologies, we are seeing longstanding and traditional business models be disrupted. We look for the downstream beneficiaries of these technologies, those outside the traditional technology universe that stand to grow their profitability as these generational changes come to fruition. Whether it is wholesale strategic shifts driving profit growth or more subtle changes in earnings cyclicality, there are numerous opportunities to profit from the changes that these companies are undergoing.
Alongside companies that are seeing outright earnings growth from novel demand or technology-enabled advancements, many companies are seeing their product and earnings cycles rebase as one or more secular drivers power growth, crucially providing companies with lower demand troughs and smaller peak-to-trough variations than in previous cycles. These developments should lead to reduced earnings volatility and a more predictable earnings pattern, something we would expect the market to reward with a rerating to higher multiples for these stocks.
With the support of one of the largest dedicated technology investing teams in Europe, our expertise and experience helps us to identify and invest in these companies that stand to benefit, while avoiding those unable – or unwilling – to adapt to avoid impending disruption. Beyond the traditional, core technology companies, we also have knowledge of the supply chains, customer bases and materials providers, all of whom fall into this wider investable universe. This ability to invest in the downstream technology beneficiaries across all sectors globally is what sets us apart from other technology-oriented funds.
As the breadth and depth of adoption of AI and automation in the corporate world expands, the benefits of these technologies will expand well beyond the tech sector and penetrate further into our investable universe. Over time we expect to see a minority of companies seize the majority of gains and the Fund is positioned to capture the growth created by these long-term transformational themes.
To view the latest portfolio breakdown and performance for the Automation & Artificial Intelligence Fund, visit our fund page.
1. Making Machines More Connected, Cisco White Paper; http://www.globiots.com/wp-content/uploads/2015/11/C11-735862.pdf
3. Morgan Stanley 3Q19 CIO Survey