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Kearney Study: AI Adoption in Southeast Asia Still Slow
October 12, 2020 News

 

In the Terminator movie series, Skynet is a fictional, artificial, neural network-based, conscious group mind and artificial general superintelligence system that becomes self-aware and decides to wipe out all humans. Whilst this is science-fiction, with the advancement in AI technology it’s not totally unbelievable, however, Nikolai Dobberstein, Asia Pacific Head of Communication, Media and Technology and Partner at Kearney believes we are still a long way before any of this can happen.

“AI is integral to the future, especially in Southeast Asia but is still only in an inception stage today”, said Nikolai at a Kearney virtual media briefing, together with EDBI, the investment arm of Singapore Economic Development Board, who are jointly studying the state of AI in Southeast Asia.

Highlighting the important and significant changes AI can bring to businesses in the region, Nikolai pointed out that while the study showed increasing investment in AI in the region, only Singapore was doing it faster and was way ahead of other ASEAN nations.

The study showed that the current focus of AI investments covers four key areas which include Machine Learning (ML), Robotic Process Automation (RPA), language-based AI and intelligent operations.

Interestingly, compared to the main AI global hubs like the US and China – ASEAN states are still lagging distinctly behind by a two or three-year gap. The region received just US$ 2 million per capita of investments in AI between 2015 and 2019. This is dwarfed by the per capita investments of US$ 155 million and US$ 21 million respectively for the United States and China. Singapore is the region’s standout with US$ 68 million.

At the same time, more than 70% of survey respondents see AI as crucial to Southeast Asia’s future and point out that AI adoption needs to be accelerated. They feel that AI solutions need to be focused on specific use cases that solve business pain points and deliver economic value in the near term.

According to Dr Basil Lui, Managing Partner at EDBI Investments and Soon Ghee Chua, a partner at Kearney as well, while the benefits from AI are transformative, capturing them requires a razor-sharp focus on value-creating use cases. As such, businesses need to be able to use AI to solve their pain points.

For example, an airline company using an AI-based chatbot to respond to customer queries. The AI can only give responses based on what information it has and the data provided. In most cases, customers end up being frustrated. The reason for this is simply because there is not enough data for the AI to process and generate the desired outcome.

In Southeast Asia, there are five issues that are impacting the adoption and proliferation of AI:

  • Overemphasised concern for talent gap: Local AI capabilities are sparse, especially outside Singapore, but actual technical skill requirements for developing and implementing AI solutions have become less specialised, given the increasing availability of ready-made AI models
  • Fragmented and nascent AI ecosystem: the fragmented and immature ecosystem in SEA, especially outside of Singapore, is making it hard for most companies to find and work with suitable AI providers. Hence, companies are less willing to experiment with use cases and AI providers to develop new applications.
  • Evolving data governance and infrastructure: Inadequacy of quality within a company’s data, infrastructure and governance are seen as challenges in harmonising and extracting data.
  • New regulations: Especially in Indonesia, Vietnam and the Philippines, regulatory constraints are an understandable yet significant bottleneck. A more harmonised set of regulations across SEA will accelerate AI investments, hence adoption rate, facilitating cross-border data flows for interconnected businesses and value chains.
  • User resistance to AI adoption: AI will impact jobs and the pace of change can be worrisome for some. 33% of our survey respondents are concerned over a likely employee backlash from job displacement, be it by gradual replacement or a catalytic displacement.

All these challenges can be solved in the long run once businesses understand the full potential, they are able to achieve with AI. Understanding AI use cases will only lead to more investments in AI.

While there will surely be potential user resistance to AI adoption, organisations and also governments need to have the right mindset in understanding the technology, especially in how they drive AI adoption. This includes clear business ownership, agile ways of working, aggregation of feature sets to scale use cases and linkage of AI-models to automated workflows.

Although the ecosystem in Southeast Asia is still in nascent stages, applying AI has become easier for many businesses. There are more off-the-shelf technology solutions and the skills required to work successfully in AI are less specialised.

In enabling an ecosystem, national AI strategies and skill-building programs are a good start but AI users and providers need to be more focused on business impact and investors can play a more active role in disseminating AI across their portfolio companies.

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