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Our global population continues to grow. Emerging markets are developing at breakneck speed. With our increasingly ageing population expected to grow by 2 billion by 2050², access to better and cheaper healthcare will be crucial.

Who consumes the most energy?

India isn’t the only country that needed to address its pressing energy issues. The world is consuming more energy than ever. Most of this increase is coming from emerging markets and, in particular, from Asia where sustainability is an issue.

Primary energy consumption is measured in terawatt-hours (TWh). Note that this data includes only commercially-traded fuels (coal, oil, gas), nuclear and modern renewables used in electricity production. As such, it does not include traditional biomass sources.

Source: BP Statistical Review of World Energy (2019)

AI could help increase the supply of energy across the entire energy mix

Last year Exxon Mobil* partnered with Microsoft to use AI algorithms to interpret huge amounts of data created by millions of sensors that monitor their refineries all over the globe. By improving the quality of analysis and the enhancements that can be made to achieve greater operational efficiencies, Exxon Mobil expects to generate billions in net cash flow over the decade from this partnership. Overall, these types of AI applications could help the industry operate more efficiently and with fewer carbon emissions and ensure sustainability.⁴

AI SOLUTIONS

Oil and gas

AI algorithms are used to cut operational costs, predict equipment failure and increase oil and gas output.

Wind farms and solar power plants

AI interprets historic data on voltage, temperatures and wind speeds to maximise the energy output.⁵ AI predicts and manage fluctuations in energy demand, which is a huge issue for oversized economies such as India and China.

An Indian company Climate-Connect is using AI to provide energy-load forecasts of the grid to energy companies. It is also using algorithms to predict maintenance costs and provide analysis that can ensure fewer outages and breakdowns.

 

Innovating battery storage - Markus’ story

Markus frequently charges his Tesla 3 model. Living on the outskirts of Zürich, he travels to his office every day. His only gripe is the range of the vehicle. He cannot comfortably drive it to his favourite holiday spot in the south of France without significant amount of planning.

Better battery technology will be crucial to ensure the electrification of our global road network. We are currently too slow to innovate and need better solutions for energy storage which supports sustainability. Part of the problem is that it takes time to test new battery chemistries. However, AI could speed up the testing process. For instance, Stanford University, in collaboration with researchers from Toyota, have developed AI algorithms that can slash these testing times by up to 98%.⁶

AI will also help electric vehicles become self-driving cars. This would reduce the number of accidents and save lives. Moreover, electric vehicles like Tesla are already considered to be partially autonomous cars.

 

The other development we could see is the rise of smart grids. When electricity is distributed centrally, it has to be carried over long distances which results in transmission loss. The smart grid allows energy to be produced in many places, which creates a more resilient, secure and cheaper electricity grid. However, it also becomes a lot more complex to manage. This is where AI can help. It could ensure a more sustainable, highly digitalised and dynamic energy system. In emerging markets like India, smart grids could make a huge difference in ensuring energy security and reliability.

 

AI will feed a growing and wasteful world

Rising incomes in emerging markets and growing urbanisation means the world is eating more and wasting more. Fortunately, agricultural companies like John Deere* have transformed themselves into artificial intelligence data-driven businesses that are dedicated to sustainability. Their goal is to protect crop yields from climate change, offer solutions that provide for population growth and help tackle security issues. Irrigation, weeding and spraying with the aid of sensors have been vastly improved. Plus, the excess use of water, pesticides and herbicides are being drastically reduced to protect the fertility of the soil and damage to ecosystems.⁷

By 2050, the average farm is expected to generate 4.1 million data points every day from a variety of sensors attached to farm equipment and drones, which are connected to a 5G network. This data rich environment is exactly what AI needs to add value. For instance, John Deere has already developed a cloud-based platform to collect data from these sensors so it can process AI algorithms.  Models can then be built using data provided, which can optimise water distribution using automated irrigation systems.

Data collected by both drones and embedded sensors could also enhance weeding and reduce the use of herbicides and pesticides. Data collected on the amount of sun, shade and irrigation that weeds like could help farmers create an inhospitable environment for weeds, yet an environment where crops can thrive.

This would decrease the need of herbicides, which are expensive, pollute the environment and risk contaminating the food supply. It would also reduce the amount of waste the agricultural industry produces. Consequently, AI could save farmers money as well as protect the environment and support sustainability.

AI will help humanity recycle the right way

AI is a disruptive force that will completely transform the global economy. It could also provide the technological progress we need in developed markets to boost productivity, improve sustainability and restore robust levels of economic growth. The difference between past technological innovations, however, is that AI facilitates sustainability.

It could for instance, improve how we recycle and manage resources. Smart robots, sensors and vision systems are providing huge amounts of data that AI algorithms can use to improve recycling. These technologies will help speed up the rate and accuracy of sorting:

From human resources perspective, AI solutions remove the challenges of recruiting and retaining labourers for this unpopular task. They also help improve safety as workers often come into contact with hazardous materials.

AI could help feed and clothe humanity in the future by providing greater access to healthier food and energy to meet our living needs. It could also help us reduce the cost of recycling and further contribute to achieving a sustainable economy. Effectively, it plays a major role in saving humanity.

In our next article, we will look at how AI is fast-tracking progress in healthcare, education and driving the development of medical wearables.

Thematic strategies focusing on areas of structural change and growth, under competent management, have proven to be resilient to market downturns.¹¹ The disruption from AI has only just started - annual investment into AI has grown 6x globally between 2015 and 2019¹² as it’s modernising industries, driving economic growth and even sustainability.

Disruption from AI
has only just started

• AI is rapidly developing and is here to stay
• Annual investment into AI has grown 6x globally between 2015 and 2019
• AI is changing business models and traditional ways of operating
• It has the potential to accelerate human learning and productivity
• AI could contribute USD15.7tn to the global economy by 2030

Long-term growth opportunities

• Regardles of economic climate, countries recognise that future prosperity depends on investments in innovation
• AI will be the disruptive wave that will help modernise industries and drive economic growth
• Investors can participate in the secular growth opportunities of AI with the aim of enhancing returns

Diverse universe of innovative companies

• Our research platform, analyses >1,000 innovative companies
• We look for businesses that stand to benefit from the:
  1. Deployment of AI infrastructure;
  2. Development of AI software and applications;
  3. Adoption of AI in key business processes;
• We have constructed a diversified portfolio of 40-100 holdings in companies that meet our investment criteria

References

¹ B. Zhang and D. Allan, "Artificial intelligence: American attitudes and trends," Centre of Governance of AI, future of humanity Institute, University of Oxford, Oxford, 2019.
² United Nations – Sustainable Development Goals, Hunger, 2020
³ The Government of India – Central Electricity Authority, "Installed capacity," Central Electricity Authority, Dehli, 2020.
⁴ AI Trends Staff, "Oil & gas industry transforming itself with the help of AI," AI trends, 18 June 2020. [Online]. Available: aitrends.com/ai-and-business-strategy/oil-gas-industry-transforming-itself-with-the-help-of-ai/. [Accessed 05 September 2020].
⁵ M. Frank, "Can artificial intelligence in the energy sector help solve the climate crisis?," DW, 14 May 2019. [Online]. Available: https://www.dw.com/en/can-artificial-intelligence-in-the-energy-sector-help-solve-the-climate-crisis/a-48669209. [Accessed 05 September 2020].
⁶ Stanford University, "Artificial intelligence used to the supercharged battery development for electric vehicles," SciTechDaily, 22 every 2020. [Online]. Available: scitechdaily.com. [Accessed 5 September 2020].
⁷ T. Talaviya, D. Shah, N. Patel, H. Yagnik and M. Shah, “Implementation of artificial intelligence in agriculture for optimisation of irrigation and application of pesticides and herbicides,” Artificial Intelligence in Agriculture, vol. 4, pp. 58-73, 2020.
⁸ Food and Agriculture Organization of the United Nations, Global Food Losses and Food Waste, 2011; FAOSTAT database; BCG FLOW model. 2015 findings, in 2015 dollars.
⁹ J. Kite-Powell, "This Recycling Robot Uses Artificial Intelligence To Sort Your Recyclables," Forbes, 04 April 2017. [Online]. Available: https://www.forbes.com/sites/jenniferhicks/2017/04/04/this-recycling-robot-uses-artificial-intelligence-to-sort-your-recyclables/#36f317802d35. [Accessed 16 September 2020].
¹⁰ H. Britt, "AI Could Improve Sustainability Through Smart Recycling Sorting," Thomas Net, 2013 March 2020. [Online]. Available: https://www.thomasnet.com/insights/ai-could-improve-sustainability-through-smart-recycling-sorting/#register. [Accessed 16 September 2020].
¹¹ A performance of the strategy is not guaranteed and losses remain possible.
¹² https://www.venturescanner.com/2020/03/12/ai-2019-funding-achieved-banner-year/

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