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Q-Series Equities Global Research 3 December 2018 Q-Series Equities Where are incumbents under the greatest threat Global from AI? Technology Michael Briest Analyst [email protected] Helping investors connect the dots and understand AI’s ripple effects +44-20-7568 8367 AI promises to have a transformative impact on the world in the years ahead, creating Hubert Jeaneau, CFA both opportunities and threats for investors. Investors need to consider not just AI's Analyst direct impact, but its second-order effects: For instance, logistics companies that adopt [email protected] autonomous vehicles may reduce their labour costs, but their customers' smarter +44-20-7568 3496 procurement planning may reduce wastage and demand for their services, in turn Hannes Leitner reducing fuel demand and fleet "wear-and-tear". Analyst [email protected] A top-down framework for considering the impact of AI +44-20-7568 7085 To connect the dots, we created a framework to systematically assess AI's impact, David Mulholland, CFA working with 29 sectors to understand who could win or lose from AI. To support the Analyst investigation we provided data on relative profitability and capital intensity. We also [email protected] looked at the employment profile of each sector to better understand which sectors are +44-20-7568 4069 more exposed to automation or substitution effects from "co-bots" and autonomous John Roy, Ph.D. vehicles. We looked at the data "intensity" of sectors to understand which sectors are Analyst more IT-intensive and data-rich. Finally, UBS Evidence Lab Data Science analysed [email protected] corporate commentary around AI to identify which sectors are most actively discussing +1-212-713 9440 the theme, and in what form. There is also an interactive model for investors to model Francois-Xavier Bouvignies the possible impact of AI on sales and profits by sector. Analyst [email protected] A bottom-up view: Cost opportunities abound, but so does higher competition +44-20-7568 7105 UBS analysts identified cost reduction opportunities from the application of AI in 27 out of 29 sectors, and better revenue opportunities from, for example, personalisation, new services and smarter pricing, in 18. However, they also saw competition intensifying in 18 sectors – both from new entrants and from competitors leveraging AI. Picking the potential winners and losers AI's impact is still in its infancy. With the caveat that the margin of error in making predictions is wide at such a stage, we see Aerospace & Defence, Automotive, Banks, Luxury, Media, Retail, Support Services, Technology, Telecoms and Transport as the sectors potentially most impacted. At an individual equity level, it is even harder to anticipate the winners and losers. Nonetheless, UBS analysts identified over 100 companies they believe are or will be impacted, both positively and negatively. www.ubs.com/investmentresearch This report has been prepared by UBS Limited. ANALYST CERTIFICATION AND REQUIRED DISCLOSURES BEGIN ON PAGE 146. UBS does and seeks to do business with companies covered in its research reports. As a result, investors should be aware that the firm may have a conflict of interest that could affect the objectivity of this report. Investors should consider this report as only a single factor in making their investment decision. Contents Michael Briest Analyst [email protected] Executive summary .......................................................................... 3 +44-20-7568 8367 AI – a summary ............................................................................... 17 Hubert Jeaneau, CFA Analyst Machine learning ....................................................................................... 19 [email protected] +44-20-7568 3496 Computer vision ........................................................................................ 20 Hannes Leitner Analyst Collaborative robots .................................................................................. 21 [email protected] +44-20-7568 7085 Autonomous vehicles ................................................................................. 22 David Mulholland, CFA Analyst Predictive analytics ..................................................................................... 23 [email protected] +44-20-7568 4069 Natural language processing ...................................................................... 24 John Roy, Ph.D. Virtual agents ............................................................................................ 25 Analyst [email protected] How big an effect will AI have? .................................................... 26 +1-212-713 9440 Francois-Xavier Bouvignies What are companies saying about AI? ......................................... 35 Analyst [email protected] The sectoral impact of AI ............................................................... 40 +44-20-7568 7105 (1) Data "intensity" ................................................................................... 40 (2) Measures of value-add .......................................................................... 42 (3) Occupation profiles by sector ................................................................ 43 Sectoral conclusions ....................................................................... 49 Consumer Discretionary ................................................................ 50 Consumer Staples ........................................................................... 62 Energy ............................................................................................. 70 Financials ........................................................................................ 74 Healthcare....................................................................................... 87 Industrials ....................................................................................... 93 Technology ................................................................................... 108 Materials ....................................................................................... 119 Telecoms ....................................................................................... 130 Utilities .......................................................................................... 132 Appendix: a brief history of AI ................................................... 135 Recent milestones – in pictures ................................................................ 136 An overview of key AI techniques ............................................................ 137 Why now? ............................................................................................... 140 Funding, patents and investments ............................................. 142 Other UBS reports on AI .............................................................. 144 Q -Series 3 December 2018 2 Executive summary AI promises to have a transformative impact on the world in the years ahead. We provide a framework for There are many implications, but for investors it creates both opportunities and investors to analyse the impact of threats. The ability of computers to interact with the world is fundamentally AI on sectors and companies changing, given significant advances in computing power and the explosion in data with which to train algorithms – using neural networks to observe and interpret patterns and learn from experience. Here, we provide a framework for investors to analyse different sectors according to their operating characteristics. Our sector analysts have explored where they see opportunities for AI to add value or create disruption, and report on what they are already seeing. We also provide an interactive model that investors can use to flex assumptions around revenues, costs and capital intensity to model the possible impact that AI may have on profits. The bottom-up view AI will deliver value – and disruption – in different ways in different sectors. We Considering the impact of AI in asked our analysts to consider AI's impact in its "pure form" of machine learning, the form of machine learning, but also as applied in computer vision, collaborative robots, autonomous vehicles, computer vision, collaborative predictive analytics, natural language processing (NLP), and virtual agents. In reality robots, autonomous vehicles, the building blocks of all of these technologies are shared, but we believe they are predictive analytics, NLP and readily understood as applied forms of AI. The analysts considered the following virtual agents key questions in evaluating the possible impact of AI: . What are the revenue opportunities? AI has the power to increase revenues via improved selling (as companies understand their customers better), faster time-to-market (shorter development cycles), or by creating completely new revenue streams (e.g. insurance services provided by manufacturers leveraging predictive maintenance). What are the cost opportunities? Many tasks will be subject to automation, and predictable tasks in the back office, on the production floor and in transportation are especially vulnerable. That is not to say that highly paid jobs in finance (such as underwriting), the law and medicine (e.g. radiology) are immune. AI also has the potential to reduce capital intensity, as assets are sweated more intensively and for longer, or used more efficiently through reducing energy usage or wear-and-tear. However, one sector's cost saving may well
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