How is AI benefiting industries throughout Southeast Asia?

What impact is AI enabled technology having on six industries throughout ASEAN?

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In recent years, different industries around the world have seen a proliferation of applications in artificial intelligence (AI). The impact of the technology is so strong that is drastically changing the way we work, communicate and even live.

AI has the potential to create large productivity gains, including in low-skilled sectors, which could improve the work and lives of people in developing regions across Southeast Asia.

Although the hubs for AI are in the US and China, Singapore is starting to catch up – living up to its reputation as a nation at the cutting edge of technological advancements. In fact, this year the Singaporean government announced it was working with the World Economic Forum’s Centre for Fourth Industrial Revolution (WEF C4IR) to help drive the ethical and responsible deployment of artificially intelligent technologies.

Throughout the rest of the ASEAN region, apart from Vietnam and Malaysia where some progress has been made, adoption rates have thus far been slow. Many countries realise the potential the technology has to offer but lack the critical infrastructure to properly capitalise on the benefits.

But, with startups continuing to flock to the region, a large millennial population and regional-wide commitments from governments to invest in and legislate for the Fourth Industrial Revolution (Industry 4.0); real change is on the horizon.

Adoption rates for AI have already grew from 8% to 14% in 2017, according to a report by IDC.

Here, we take a look at the impact artificial intelligence is having across six key sectors in the ASEAN bloc.


E-commerce is big business in Southeast Asia, with Singapore, Malaysia, the Philippines, Indonesia and Thailand generating US$14.8 billion in online sales throughout 2016. In the same year, Lazada Group - a Singaporean online marketplace that is Southeast Asia’s answer to Amazon – reported US$1.36 billion in annual sales and is now the biggest eCommerce operator in Malaysia, Vietnam, Thailand and the Philippines.

Like their counterparts in the West, both online and offline retailers are keen to move with the times and offer their customers a new shopping experience that reflects the digital age we now live in.

With 97 million mobile phones in circulation throughout Thailand, it’s unsurprising that consumers are used to turning to their phones for help, instead of seeking out a real person. Smart phones now come fully equipped with AI assistants and every retailer from Starbucks to supermarkets now use chatbots to engage with their customers.

Gartner predicts that 25% of customer questions will be handled by AI by the year 2020, freeing up today’s human sales assistants from the monotony of answering the same query 30 times a day. AI can also be used to predict questions before they’ve been asked and ultimately improve the customer service experience for most shoppers.

Within the retail sector, AI can personalise purchasing recommendations for customers whilst helping retailers to optimise pricing and discount strategies, alongside demand forecasting.

Last year, Lazada launched an AI driven app that takes away the emphasis from pre-set categories and instead uses machine-learning algorithms to show off products that the user might be interested in based on purchase and viewing history.


Agriculture is the economic backbone of most ASEAN countries, therefore a sensible implementation of AI could greatly help boosting the sector. Increasing consumption and rising requirement of better yield of crops are estimated to be one of the major factors that is fueling the demand of robots in agriculture.

AI in agriculture is mainly used for precision farming, livestock monitoring, drone analytics and agriculture robots. Precision farming was the most widely used application in 2018, taking up about 35.6% of the global total. However, agriculture robots are expected to have a bigger share in the future.

Speaking at a recent seminar titled “Connecting Manufacturing Industry with AI Technology”, Dr Siridej Boonsaeng, Dean of the College of Advanced Manufacturing Innovation, King Mongkut's Institute of Technology Ladkrabang, said that AI is presenting the agricultural sector in Thailand with great opportunities.

"Self-driving farm vehicles and the process of sorting and grading agricultural products which involve complicated factors of random shape and variation are suitable tasks for AI to replace human when required," he said.

During last year’s Grow Asia Forum, Vietnam’s Deputy Prime Minister Trịnh Đình Dũng called for the private sector to get more involved with cutting edge technologies in the 4.0 revolution in a bid to transform the agriculture industry of Southeast Asian countries.

Startups in the region are also developing innovative AI solutions to some of the most impending issues affecting farmers and other agriculture sector workers, including sustainable crop management and financing. For example, Sero, a Vietnam-based agriculture startup, provides farmers with crop intelligence by leveraging on AI analytics of imagery and in-field data.

Financial services

Much like the retail sector, organisations operating within the financial services have primarily been using AI to improve the customer service experience. One such example is the deployment of IBM Watson in Hong Leong Bank of Malaysia to analyse the emotion of customers by the way they speak on the telephone.

While Singapore is leading the technological charge in this arena, the ASEAN bloc has been slow on the uptake when it comes to some of the more advanced use cases for artificial intelligence.

Financial institutes throughout America and China have already started to develop AI that can be applied to functions such as credit scoring and investment predictions.

Some argue that emerging technology on that level is best left to the fintech startups that the region is continuing to attract.

Singapore based startup CashShield, for example, uses real-time high-frequency algorithms with biometric analysis and pattern recognition to help companies manage the risk of fraudulent accounts and payments.

Claiming to be the world’s only fully machine automated fraud management system, its algorithm trains itself in real time, functioning without the need for any data scientist or fraud analyst.

However, not every country in the bloc is as technological savvy as Singapore, with most first needing to accelerate basic digitisation efforts; streamlining their data collection, management and analytics processes before than can start feeding the information into complex AI algorithms.

Ultimately, most of the AI developments in the financial services will emerge from fintech startups, it’s up to the established institutions throughout the region to keep up with these developments or risk losing their business to digital disruption.


Last year, ride-hailing startup Grab and the National University of Singapore (NUS) launched an AI laboratory with the aim to develop solutions that can transform urban transport and prepare for “smarter” cities in Southeast Asia.

The ‘Grab-NUS AI Lab’, which has been set up with a joint initial investment of S$6 million, is Grab’s first major AI laboratory and NUS’ first AI laboratory with a commercial partner.

Through the use of AI algorithms, Grab’s is using data from its rides to build richer maps, understand passengers’ preferences, modelling of traffic conditions, analysing driver behaviour and detecting real-time traffic events.

By combining this data with NUS’ research and development (R&D) expertise in the field of AI, and under the supervision of senior Grab research scientists and NUS faculty members, the Grab-NUS AI Lab will map out traffic patterns and identify ways to directly impact mobility and livability of cities across Southeast Asia.

Then there’s of course the application of AI on the automotive industry. One of the most valued features that AI brings to autonomous vehicles (AVs) is the prediction of objects in the travel path through AI deep-learning algorithms. In this feature we reviewed the state of AVs in the ASEAN bloc.


Across the globe, the potential for AI in healthcare has already been demonstrated to the public. Complex machine learning algorithms have helped to speed up how long it takes to review data relating to serious illnesses, allowing doctors to diagnose and treat patients more efficiently than ever before.

Healthcare in Southeast Asia varies from country to country but on the whole combines state funded care with private, insurance-led options. One of the biggest healthcare insurers in Singapore, NTUC Income, has already deployed IBM Watson to digitally process almost 15,000 monthly claims.

Private medical group Parkway Pantai has been using AI since November 2018 to generate accurate hospital bill estimates.Using AI and machine learning algorithms from Singapore-based startup UCARE.AI, Mount Elizabeth, Mount Elizabeth Novena, Gleneagles and Parkway East hospitals are now able to generate personalised bill estimates based on parameters such as the patient’s medical condition and medical practices. It also takes into account the patient’s current age, revisit frequency and existing conditions like high blood pressure or diabetes.

The uses of AI have also been embraced by the government in Singapore, with one state agency using the technology to analyse patient data that has been inputted from a number of different healthcare systems. The system should help to improve diagnostic outcomes and generate greater insights into potential treatments.

Malaysia is to healthcare startups what Singapore is to fintech, with many of these emerging companies developing AI-based solutions to help improve the access people have to healthcare professionals. Getdoc, Door2Door Doctor, Teleme, HomeGP, Healthmetrics, and BookDoc are all Malaysian healthcare startups that use AI algorithms to help predict your medical needs, customise your healthcare plan and increase your access to medical advice.

However, similar to the financial services industry, the majority of healthcare institutions throughout Southeast Asia still rely heavily on legacy systems and are often unable to cope with the data demands needed to successfully implement AI technologies.


While progress is still slow in the education sector, the potential that exists within it for AI is unquestionable. Globally, 5% of GDP is being spent on education and those in the know are already predicting that investment in edtech will reach $250 billion by 2020.

Once again, AI chatbots and even artificially intelligent classroom assistants are proving useful in this sector, removing some of the pressure form teachers and allowing them to focus more on the job of teaching and less on monotonous and repetitive tasks.

In the field of AI analytics, universities in Singapore and Malaysia have started to experiment with predictive algorithms designed to reduce the number of dropouts by allowing for earlier interventions.

Once again, there are only a select few countries throughout the ASEAN region that have really started to embrace the potential for AI in the education sector. One of the biggest current hindrances is a lack of consistent quality in IT infrastructure throughout the bloc, with some reports showing that large numbers of the ASEAN population still don’t have access to the internet.

Consequently, it’s important for these countries to focus on how the technology that is already available can be enhanced, rather than replaced by AI; leading to an improvement in not only the quality of education but also who can access it.

Additional reporting by Cristina Lago

Copyright © 2019 IDG Communications, Inc.

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