How artificial intelligence can help Asean
Use of AI in South-east Asia remains in its infancy
Artificial intelligence (AI) is still in its infancy in South-east Asia: the use of one common type of AI - machine learning, where machines are fed data to learn from - is just beginning to have an impact on the region.
If AI development were left purely to market forces, early adopters in financial services, high-tech and telecommunications would be likely to extend their use of the technology. But greater value in other sectors, such as retail and healthcare, would remain largely untapped.
We already see AI radically altering the way online retailers fulfil orders, how manufacturers make parts and assemble them, and the way doctors decide how to battle some diseases. And change will only accelerate as the drivers of AI growth - shrinking computing costs and growing databases - improve.
In South-east Asia, companies in the most digitally savvy industries after high-tech - banking and telecoms - have already launched initiatives, but have faced difficulty in scaling up, often because their workforces lack critical skills in data science and business translation or they lack sufficient data.
The region's financial-services firms have thus far adopted AI primarily to improve the customer experience. Hong Leong Bank of Malaysia, for example, uses AI to detect callers' emotions by the way they speak on the phone.
CompareAsiaGroup, a Hong Kong-based start-up, uses machine learning to choose the most economical financial, telecoms and utility services for clients in five Asean member countries.
For AI to have a broad, long-term effect on the sector, South-east Asian banks could integrate AI deeper into their organisations, into functions such as credit scoring, dynamic pricing and digital marketing.
Few Asean banks have scaled up these types of applications.
Taking advantage of this opportunity will need established banks to develop new skills and fintech start-ups - there are already 300 in the region - to innovate.
AI can enable manufacturers to manage their factories remotely, make real-time decisions and improve efficiency. However, this will rely on real-time data from machines equipped with sensors and linked digitally - the so-called Internet of Things (IoT).
McKinsey Global Institute research concluded that expanding data use in healthcare could yield more than US$300 billion (S$408.8 billion) in value annually around the world.
At the same time, AI can improve care, especially in large countries with relatively few doctors and specialists. For example, Indonesia, a country of 250 million people, had only 41 radiation oncologists in 2014.
Despite the potential benefits, common use of AI in patient care remains years away in Asean.
The region lacks enough consolidated data to support the use of advanced analytics, let alone AI. Hospitals have data, but usually on paper, and they have little incentive to share it.
Most Asean countries require data to stay "onshore", hobbling efforts to build region-wide data sets that could improve AI analysis.
Governments have a role to play, too. Well-crafted strategies and policies can turn today's innovation into sustainable growth for Asean over the longer term, and AI can provide a major boost to productivity.
The writers are from McKinsey & Company. Mr Chitturu is an associate partner based in Singapore and Mr Grijpink is a senior partner and managing partner for McKinsey's Telecommunications, High-Tech and Media Practices in South-east Asia. This article was published in The Business Times yesterday.