What Southeast Asia needs to become a major player in artificial intelligence

What Southeast Asia needs to become a major player in artificial intelligence

By Sachin Chitturu, Diaan-Yi Lin, Kevin Sneader, Oliver Tonby, and Jonathan Woetzel
What Southeast Asia needs to become a major player in artificial intelligence

For artificial intelligence to take hold in Southeast Asia, the region needs more defined business use cases, better data ecosystems, and more concerted talent-development efforts.

Artificial intelligence (AI) is still in its early stages in Southeast Asia: the use of machine learning—an AI application in which machines are given access to data to learn from—is just beginning to have an impact on the region. If Southeast Asia wants to catch up to the United States and China, the two major hubs of AI development, it needs to coordinate efforts to put fundamental building blocks in place.

All member states of the Association of Southeast Asian Nations (ASEAN) are engaging in some level of AI research, with Singapore leading ASEAN in AI experimentation across multiple industries. While such sparks of activity are encouraging, the region requires nations to identify specific business use cases, to create more robust data ecosystems, and to better develop talent and capabilities if it wants to realize its full potential.

Properly nurtured and developed, AI research and development has the potential to bring about many positive outcomes. Machine-learning innovations can enhance credit models and financial inclusion, for example. AI solutions can also enable new types of preventive and remote healthcare, and may also improve diagnoses and accelerate drug development. In education, adaptive-learning algorithms could be used to develop individualized lesson plans and virtual classrooms.

Different sectors in ASEAN are currently at varying levels of digital maturity (exhibit). If AI development were left purely to market forces, early adopters in financial services and in high tech and telecom would be likely to extend their use of the technology. But much greater value in other sectors would remain largely untapped.

Superior profitability and sizable value pools created from AI adoption in ASEAN.

Capturing this value and realizing AI’s potential to improve social welfare will not happen organically, however. It will take structural interventions from policymakers combined with a greater commitment from industry participants. The region’s governments, for example, will need to commit to building a foundation of digital infrastructure and agree to systematize the collection and dissemination of large quantities of data. And while the marketplace ultimately will drive the development and adoption of specific AI applications, governments have a critical role in making sure that the benefits of AI—new products and services, increased productivity, and most importantly greater national income—are shared across the society.

To achieve these goals, governments would be wise to focus on three major priorities:

  1. establishing a regional policy framework to support AI development and adoption,
  2. developing AI talent and encouraging usage at the local level, and
  3. focusing public debate on ensuring that AI contributes to inclusive growth and positive social outcomes.

These interventions are primarily about guiding an inevitable wave of change to quicker and better effects. For now, Southeast Asian nations can begin to ask some of the big questions that each society must answer for itself: Is it ready to share personal data? Will the digital divide only get worse? Which innovations are worthy of public funds and partnerships?

Bringing these questions into the open is the most important step in ensuring that AI advances benefit the region’s economies and create a better society.

The report on which this article is based was produced to coincide with the Singapore Summit 2017.

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