Why UAE investors should start looking to AI
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Why UAE investors should start looking to AI

Why UAE investors should start looking to AI

Alexandre Mouthon explores the growing influence of AI

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Artificial intelligence is one of the fastest-growing areas of digital technology – set to transform our lives, and our investment portfolios.

The latest devices from the likes of Amazon, Microsoft and Google already enable us to switch on the lights, check the weather forecast, consult our diaries, listen to music, boil the kettle or book a taxi – all by voice command.

Soon, AI will be able to achieve much more, supported by investment from digital companies who now see machine-learning systems as a major source of future growth. The UAE has the potential to lead this growth in the Middle East due to bold new legislation, a network of talent and the growing numbers of start-ups that are creating unique data sets to solve problems that are ripe for machine learning.

The AI market is forecast to balloon to $127bn by 2025 from $2bn in 2015, with the US and China leading the way so far and the bulk of the investment coming from high tech, telecom and financial services sectors within those countries.

For the global economy that could mean trillions of dollars of extra growth, through both increased productivity and via a boost to consumption as people spend money on new or improved goods and services. AI is a pervasive enabling technology that will boost the fortunes of companies across multiple industries, but cause the demise of others.

The difference between commercial success and failure could be how effectively and how quickly firms deploy AI and how effectively they are able to analyse a lot of data. The annual amount of data we produce is forecast to reach 163 trillion gigabytes in 2025 – 10 times more than in 2016.

Through machine learning, algorithms can use historical data to spot patterns and predict what might happen in the future. Next comes deep learning, where computers learn from their mistakes and refine predictions with each new fragment of information, becoming increasingly adept at recognising images and speech, as well as at natural language processing (NLP) – understanding spoken and written words just as humans do and responding within context.

There are two direct ways for investors to access AI investments. One is through hardware – the physical devices used in machines. The other route is through software – the collection of code installed into a computer’s hard drive.
On the hardware side, demand for powerful graphics processors (GPUs), which can enable computers to analyse and make use of vast quantities of data, is fuelled by the processing power required for deep learning.

Driverless cars, for example, have a lot of learning to do: both on their immediate environment and how to react to different situations. To better accommodate this, Tesla recently used new GPUs to upgrade the processing power of its autopilot system by 40 times. Any further tech developments are likely to be met with strong appetite from manufacturers.

Given that most GPU chip production is outsourced (with GPU companies mainly focusing on the design rather than manufacturing), this should lead to better growth prospects in the foundry and outsourced semiconductor assembly and test (OSAT) industries.

The more sophisticated AI machines get, the more memory they will likely require to function. Just one second of autonomous driving can generate as much as 1GB of data, for example. All that information needs to be stored somehow, somewhere; creating demand for memory chips, as well as for cloud storage solutions.

AI could account for around 25 per cent of total semiconductor demand by 2020, from 10-15 per cent today.

The AI-driven transformation in software is arguably progressing even faster. Digital software companies will benefit the most from the AI era as they can extract recurring revenue from subscriptions as well as new products. This is in contrast to semiconductor companies that will mostly profit from a one-time purchase cycle.

Companies such as Facebook, Baidu, Salesforce.com or Medidata have access to massive amounts of consumer or enterprise data in their respective fields and are able to offer value-added services based on AI to their customers.

The scope for what data-crunching AI software can do is virtually limitless, and companies are feeling the benefits already. Netflix, for example, estimates that it is preventing over $1bn of potential revenue loss per year from cancelled subscriptions by offering tailored search results and recommendations. Amazon managed to reduce its warehouse operating costs by at least a fifth by employing autonomous robots.

Ultimately, the key to corporate success in the digital world will be the ability to harness data and turn it into business opportunities. For investors, one of the most direct ways to tap into AI is by identifying the tech specialists who are delivering the best hardware and software. Only by embracing the robotic revolution can we stay ahead of the game.

Alexandre Mouthon is senior product specialist at Pictet Asset Management


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