Already, AI is more widespread than many of us may realise. Spotify, Netflix and Amazon all use it to assist in the way they target their products to consumers—while Amazon has also used it to reduce labour costs, effectively replacing six humans with one robot.
In this article, we take a look at how investors should think about AI, how widespread it is, and why this thematic is likely to have a far-reaching impact on economies and markets. We also examine why those companies that are embracing AI are likely to be able to both disrupt and deliver real value to their shareholders.
At a company level, the ability to implement and leverage AI will become one of the key differentiators over the next decade. Management teams that don’t focus on AI risk missing out on the inevitable product innovation, labour efficiencies and capital leverage that it will bring. The corollary to this is that companies will need to invest in new technologies to stay competitive, which will drive a surge in demand for the talent, services, and hardware underlying AI.
While investors will invariably be interested in who the likely AI winners are, just as much attention needs to focus on where and how AI will disrupt business models, industries and societies.
Disruption is not a new phenomenon, and mechanisation has thus far occurred without AI. When Henry Ford introduced the assembly line, the time it took to assemble the Ford Model T fell from 12 hours to around 90 minutes. The difference now is that AI is gradually expanding the realm of physical automation because it relates largely to robotics.
As such, current disruptive developments appear to be much more global and wide-ranging in nature than in the past—and the implementation of AI is likely to span social, political, legal and security issues that the world is only now starting to analyse.
According to management consultant, McKinsey & Company, countries that establish themselves as AI leaders (mostly developed economies to date) could capture an additional 20-25% in economic benefits over time compared with today. Emerging economies (which tend to have other ways to improve their productivity, including catching up with best practices) may capture only half their AI upside, given less of an incentive to push into AI. The ability of countries, companies and individuals who are leaders to reinvest their AI gains is likely to foster conspicuous winners over the decades ahead.
In 2013, researchers from the University of Oxford estimated that 47% of all jobs could be replaced by AI automation (or robotics). In a 2016 report, the Organisation for Economic Co-operation and Development put the number at 9%. But even 9% would place enormous financial stress on the global economy—not to mention the psychological toll on displaced labour.
Looking forward, automation will mostly affect clerical work, sales, customer service and support functions. Minor claims in insurance can be processed without human intervention, most incoming customer queries could be answered automatically, and many customer calls deflected. In finance, ‘robo-advisors’ are already available in the market, and computers can quickly sift through millions of emails and dramatically cut the cost of legal investigations.
Thematic investing is a style of investing that focuses on strong and emerging secular trends that identify sustainable long-term growth themes. AI, along with automation and robotics where it finds much of its application, is one of these thematics. As noted by McKinsey in 2017, “AI has the potential to accelerate shifts in market share, revenue, and profit pools—all hallmarks of digitally disrupted sectors” . The ability to implement and leverage AI will become one of the key differentiators over the next decade.
Given the sheer scope of AI, identifying opportunities can appear overwhelming—but by breaking down the AI stack into the various attributes needed to develop AI capabilities, this can provide investors with a more manageable framework for identifying opportunities:
For now, many investors are likely to focus on the mega-caps (Google, Amazon, Microsoft, Alibaba, Tencent etc) as the main way to gain exposure, with domestic stocks like Appen offering exposure to human-interpreted data sets for machine learning applications. As well as AI-enablers, there are early-adopters who are likely to gain a sustainable competitive advantage. There are many companies in this space, such as Monsanto (now Bayer), Ping An Insurance, Illumina and Siemens to name a few.
Exchange-traded funds (ETFs) are another option for those looking to gain a broad exposure to this thematic. Some examples would include ROBO Global Robotics and Automation ETF (ROBO), the Global X Robotics and Artificial Intelligence Thematic ETF (BOTZ), the BetaShares Global Robotics and AI ETF or the iShares Robotics and AI ETF.
As AI becomes more mainstream and the benefits of early adoption become more tangible, the investment selection process will undoubtedly become more nuanced.
Todd Hoare, Crestone Wealth Management Global Equities Specialist
