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19 sep 2018

5 surprising companies investing in AI

 

What is Artificial Intelligence? Put simply, it’s a computer system aiming to match – or exceed – our own cognitive capabilities. No longer the preserve of science fiction, AI is increasingly pervasive in our daily lives – often in ways we’re not even aware of. As a result, market revenues are set to grow rapidly creating what could be a very significant investment opportunity indeed. Adding the right Robotics & AI exposure could help keep your portfolio on the right side of this change.

 It’s no surprise tech giants like Google, Microsoft and Intel are leading the way, with 77% of total AI investment in 2016 coming from big tech – about $20-30bn worth.1 But what may surprise you is the growing list of less likely contenders, often from sectors outside of technology, harnessing the power of AI to improve their business models and the way they look after their customers. Here are five champions of change:

1 – Alibaba

The Chinese government is committed to becoming the largest AI player in the world, to the benefit of companies like Alibaba. In late 2017, the e-commerce giant announced its plans to invest $15bn over three years in a global research and development programme, with projects focusing on data intelligence, machine learning, the Internet of Things, and natural language processing.

This is by no means Alibaba’s first foray into AI. The company has transformed around a million physical ‘mom-and-pop’ shops and 100 superstores into “smart stores” by decking them out with AI-backed apps and heat sensors tracking foot traffic to better manage inventory and boost sales.

Another example of Alibaba’s command of AI is its “City Brain” traffic project in Hangzhou. Using a cloud-based system, the technology stores and processes data about the movements of everyone in the city. AI algorithms can then help reduce traffic jams, and better respond to accidents and crimes.

 

2 – Netflix

Netflix has come a long way since its early days as a mail-based DVD rental service. It now not only distributes third party content online, it also streams its own movies and shows. The Netflix name may have become synonymous with a quiet night in but the importance of AI to its business model is far less familiar.

Netflix uses machine learning algorithms to make personalised viewing recommendations. It compares the collective feedback of a group of subscribers who have watched a film or show with your past viewing habits. If your taste matches that of the group, the film or show they watched will pop up as a suggestion for you. Netflix claims over 80% of TV shows people watch are a direct result of a recommendation they make.

Another underrated way in which Netflix leverages AI lies in its actual streaming technology. The company’s main goal is to deliver as much content as possible to its customers, within the limits imposed by internet providers (e.g. bandwidth speed, data caps…etc). To achieve this, Netflix recently re-encoded its entire library of content with an AI-powered video optimiser that aims to maximise image quality and minimise bandwidth consumption. The result? A growing, happy subscriber base capable of enjoying content without wiping out their data plans.

 

3 – TripAdvisor

According to a comScore report commissioned by travel website TripAdvisor, they were the most visited pre-transaction travel site in the world over the second and third quarters of 2017. As such, its influence over travelers around the world is hard to dispute.

One reason for their success lies in their ability to deliver the right reviews to the right customers at the right time, depending on where they are in their holiday planning. To do this, their recommendation technology employs a machine learning technique called ‘collaborative filtering’. The idea is to match users with specific interests to reviews with relevant content.

In its view, “not every millennial wants to live like a local; not every family wants to live like a tourist.” By tapping into the website’s massive data sets and giving users a personalised experience, AI can really make a difference.

 

4 – Salesforce.com

US software behemoth Salesforce.com is known for its cloud-based client relationship management product. And one of its self-proclaimed missions is to democratise AI, which it kick-started in 2016 with its announcement of ‘Einstein’, a programme which empowers Salesforce users with AI.

Salesforce is mainly used by salespeople to manage their prospects. Where Einstein can help is by prioritising leads based on their likelihood to close, for example. It effectively automates time-consuming tasks so the seller can focus on their hotter prospects. Marketers can also benefit by sorting recipients in large mailing lists by their likelihood to open an e-mail.

This goes beyond simple filters – Einstein studies historical customer data such as e-mail threads and behavioural patterns to keep getting smarter over time. The result is a powerful and predictive customer experience designed to maximise sales figures. In its latest upgrade, Einstein has also become a chatbot, minimising the need for costly customer service centres.

 

5 – Tesla

Despite the eccentric antics of visionary frontman Elon Musk in recent months, the Tesla story remains intact and that story is founded on big data and AI. The company is desperate to win the race to build and market fully automated, driverless cars and doing so requires data – the thousands of Tesla-built cars on the road already mean they have a huge head start.

Data is extracted from every vehicle (as well as their drivers) and used to generate very detailed maps showing everything from the average increase in traffic speed over a stretch of road to the location of hazards which cause drivers to take action. Machine-learning in the cloud then educates the entire fleet, while edge computing decides what action any given individual car needs to take right now. Cars can form networks with other Tesla vehicles nearby to share local information and insights.

If and when autonomous cars become as widespread as Musk maintains, these networks will be able to interface with cars from other manufacturers as well as other systems such as traffic cameras, road-based sensors or mobile phones.

 

Capture the theme with our new Robotics and AI ETF

Embracing the AI and robotics revolution could help future-proof your portfolio. Our ETF gives you exposure to 150 companies – at least 50% more than other competing products2 – harnessing the power of AI, whether for themselves or their customers. It is unique in three ways:

  • Better balanced :
    Our ETF is more heavily weighted to AI leaders than competing European products, but it doesn’t ignore the benefits robotics can bring2.
  • More capable of capturing change :
    We look beyond industrials and technology to AI innovators in areas such as retail, health care, energy and finance to better capture the theme.
  • More likely to evolve
    We’ve introduced a new way of classifying what constitutes a robotics or AI company – a combination of big data analytics and human expertise – ensuring our ETF won’t get left behind as the industry evolves.

While some of the stocks we track in our ETF do overlap with other like-for-like products in Europe, 64 (or around 40%) of them are unique to us. In our view, this helps us capture the trend more broadly and accurately than other strategies. All the companies highlighted in this blog are in our underlying index and are, at least in terms of blended robotics and AI portfolios, entirely unique to us. Three of the five can’t even be found in a new pure play AI ETF.2

Find out more about the Lyxor Robotics and AI UCITS ETF 

This article is for informative purposes only, and should not be taken as investment advice. Lyxor ETF does not in any way endorse or promote the companies mentioned in this article. Capital at risk. Please read our Risk Warning below.

1Source: McKinsey Global Institute, June 2017.
2Source: Lyxor International Asset Management, as of 20/06/2018. Peer comparison made with European listed ETFs focused on Robotics and Automation, as well as a new ETF focused purely on AI.


Other sources:
https://www.forbes.com/sites/bernardmarr/2018/07/23/the-amazing-ways-chinese-tech-giant-alibaba-uses-artificial-intelligence-and-machine-learning/#ab2d9b5117a9
https://www.wired.co.uk/article/how-do-netflixs-algorithms-work-machine-learning-helps-to-predict-what-viewers-will-like
https://venturebeat.com/2017/10/26/deep-learning-algorithms-could-secure-the-future-of-4k-streaming/
https://www.phocuswire.com/TripAdvisor-AI-reviews
https://www.wired.com/story/inside-salesforces-quest-to-bring-artificial-intelligence-to-everyone/
https://markets.businessinsider.com/news/stocks/nvidia-stock-price-worth-valuation-self-driving-cars-2018-5-1025022947

Risk Warning​

This document is for the exclusive use of investors acting on their own account and categorized either as “Eligible Counterparties” or “Professional Clients” within the meaning of Markets in Financial Instruments Directive 2004/39/EC. These products comply with the UCITS Directive (2009/65/EC). Société Générale and Lyxor International Asset Management (LIAM) recommend that investors read carefully the “investment risks” section of the product’s documentation (prospectus and KIID). The prospectus and KIID are available free of charge on www.lyxoretf.com, and upon request to client-services-etf@lyxor.com..

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Lyxor International Asset Management (“LIAM”) or its employees may have or maintain business relationships with companies covered in its research reports. As a result, investors should be aware that LIAM and its employees 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. Please see appendix at the end of this report for the analyst(s) certification(s), important disclosures and disclaimers. Alternatively, visit our global research disclosure website www.lyxoretf.com/compliance.

Conflicts of interest 

This research contains the views, opinions and recommendations of Lyxor International Asset Management (“LIAM”) Cross Asset and ETF research analysts and/or strategists. To the extent that this research contains trade ideas based on macro views of economic market conditions or relative value, it may differ from the fundamental Cross Asset and ETF Research opinions and recommendations contained in Cross Asset and ETF Research sector or company research reports and from the views and opinions of other departments of LIAM and its affiliates. Lyxor Cross Asset and ETF research analysts and/or strategists routinely consult with LIAM sales and portfolio management personnel regarding market information including, but not limited to, pricing, spread levels and trading activity of ETFs tracking equity, fixed income and commodity indices. Trading desks may trade, or have traded, as principal on the basis of the research analyst(s) views and reports. Lyxor has mandatory research policies and procedures that are reasonably designed to (i) ensure that purported facts in research reports are based on reliable information and (ii) to prevent improper selective or tiered dissemination of research reports. In addition, research analysts receive compensation based, in part, on the quality and accuracy of their analysis, client feedback, competitive factors and LIAM’s total revenues including revenues from management fees and investment advisory fees and distribution fees.

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