In an email interview with e27, Elevandi Executive Director Pat Patel explains that the integration of AI in Southeast Asia (SEA) has become a transformative force for businesses in various sectors. Its reach extends across verticals from e-commerce to agriculture. However, he stresses that “the brush strokes” of AI adoption in SEA are neither uniform nor simplistic.

“The speed, scale, and scope of AI adoption are influenced by a multitude of factors, from the technological infrastructure to talent availability, varying significantly from one SEA country to another,” he says.

“A further testament to AI’s growing influence is its increasing visibility at industry-specific platforms, such as the Singapore FinTech Festival, which seeks to bring together the industry leaders at the nexus of policy, finance and technology to drive the opportunities and align on the challenges. From healthcare to automotive sectors, AI solutions are being showcased in applications ranging from medical diagnostics to autonomous vehicles, underscoring its broad-based adoption and ongoing evolution.”

Despite its pervasiveness, the spread of AI in SEA is not without its own challenges.

“Talent scarcity tops the list; companies like Grab have found it challenging to attract AI and machine learning specialists, prompting them to initiate partnerships with academic institutions to cultivate local talent,” Patel says.

“Then comes the elephant in the room—data privacy. For fintech companies like Singapore’s GoBear, safeguarding sensitive financial data while complying with stringent regulations such as GDPR presents a monumental challenge.”

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Financial constraints add another layer of complexity, according to Patel.

“Companies like Tokopedia have had to invest heavily in foundational technology like cloud computing and data centres, significantly inflating operational costs. Market fragmentation, evidenced by the need for platforms like Lazada to customise AI models to suit varying consumer behaviours across countries, complicates implementation,” he elaborates.

“Moreover, in sectors like finance, ethical considerations around AI-based models become a convoluted territory to navigate, as seen with Malaysia’s CIMB Group, which has invested in transparent risk assessment mechanisms to alleviate ethical concerns.”

Getting SEA businesses to embrace AI

In order for SEA businesses to fully integrate AI in their operations, according to Patel, there are “a myriad of” strategies that they can implement. It all started with having the regulation to support that.

“Given AI’s dynamic landscape, governments must continually revise and adapt their regulatory frameworks, which should ideally offer crystal-clear guidelines on ethical AI usage. They need to stay ahead of the curve and not just follow technological advancements — anticipation and collaboration are key to harnessing AI’s full potential regionally,” he says.

“Second, data privacy laws akin to Europe’s GDPR or Singapore’s PDPA are non-negotiable for the credibility of AI. This isn’t merely a legal requirement but a trust-building mechanism. Ethics should not be an afterthought but a foundational element in AI implementation—ensuring fairness, transparency, and accountability.”

Patel also highlights the importance of workforce development and AI literacy as well as building a sufficient technology infrastructure. But expanding further on his point on regulation, Patel stresses that the concept of a monolithic, region-wide AI policy for SEA is enticing but fraught with complexities.

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“Given that the region is emerging as a significant player in the fintech sector and is poised to be the world’s fourth-largest economy, it is tempting to advocate for uniform regulations. However, the socio-political heterogeneity of SEA makes such a policy an uphill endeavour,” he explains.

“For example, ASEAN’s current framework for AI serves more as a guiding beacon rather than a set of enforceable laws. While each country within the region has a moral imperative to uphold these principles, the non-binding nature of this framework highlights the difficulties of implementing a singular, regional approach to AI governance.”

But this does not mean that the region is absolved from its responsibility to act collectively. Given the borderless nature of AI, Patel highlights that a vulnerability in one jurisdiction could reverberate throughout the region, creating a domino effect with potentially devastating implications on a global scale.

“Instead of aspiring for a one-size-fits-all policy, the region should place greater emphasis on two pivotal areas. The first is up-skilling its already technologically skilled workforce — creating a deep reservoir of AI talent that can serve as the intellectual cornerstone for the decades to come. The second focus should be on establishing robust platforms for regional dialogues. These platforms should serve as melting pots of innovation, fostering cross-pollination of ideas between technologists, policymakers, and financial experts — groups that have historically operated in silos,” he elaborates.

“SEA shares some common vulnerabilities and characteristics, especially in areas like climate change, labour migration, and infrastructural development. A cooperative approach in these areas could demonstrate how AI can be a force for collective good across varying national landscapes.”

This is why a balancing act between innovation and regulation in the context of AI is a delicate matter without a one-size-fits-all solution.

Patel points out that while Europe’s AI Act is comprehensive, its long-term impact on AI innovation remains to be seen. On the other hand, Singapore’s National AI Strategy exemplifies that through close and fruitful public-private collaborations, it is possible to steer responsible AI usage without the need for hard and fast enforcement.

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“There are also a number of cross-industry initiatives that the Monetary Authority of Singapore is driving, such as Project MindForge, which seeks to examine the risks and opportunities for Generative AI use cases for the financial sector; Project Veritas which seeks to strengthen the financial sectors governance of AI management and data use, and lastly, Project NovA! which is an AI utility to help financial institutions to generate prompt and actionable insights using structured and unstructured datasets and advanced computing,” he says.

What is coming up in 2024

Elevandi is a not-for-profit entity set up by the MAS to foster an open dialogue between the public and private sectors to advance fintech globally with Singapore as the centre of gravity. The organisation works closely with governments, founders, investors, and corporate leaders to drive collaboration, education, and new sources of value at the industry and national levels.

As we are getting closer to the end of 2023, we asked Patel about what AI trends are going to arise in the near future.

“Taking a cue from the EU’s AI Act, one indisputable trend that we can anticipate is the continued roll-out of AI frameworks. These will span the spectrum from entirely voluntary to legally binding regulations, signalling a global recognition of the pivotal role AI is set to play in all facets of our social fabric,” he says.

He points out several key themes that are going to be dominant and will be captured in the upcoming Singapore Fintech Festival:

GenAI beyond text

ChatGPT may have stolen the spotlight in 2023, but according to Patel, it is just the “tip of the iceberg” when it comes to GenAI tools.

“Following the lead of Diffusion, Midjourney, and Dall-E, a plethora of tools will soon emerge, allowing users to generate images, videos, and more within seconds. The ramifications of such advancements will stretch beyond the creative industries, affecting everything from copyright law to the proliferation of disinformation.”

The explosion of data availability

“Back in 2018, the International Data Corporation predicted that by 2025, worldwide data will grow 61 per cent to 175 zettabytes, with 75 per cent of the world’s population interacting with data daily. That was before the meteoric rise of AI,” Patel points out.

“Particularly, in the last year, we have seen a surge in high-quality data sets, complemented by emerging technologies, such as quantum computing and cloud storage — which have spurred widespread experimentation in the AI sector. While these developments have led to more accurate and hyper-personalised AI applications, they have also birthed new inefficiencies and biases that are not yet fully understood.”

Enhanced human-AI cooperation

Patel acknowledges the recent discourse on the potential for AI to replace human roles across various professions. However, he sees that the immediate impact of such a shift is unlikely to materialise within the next year.

“This provides an opportune moment to refocus the conversation on how AI can augment human capabilities in the workplace, allowing us to delegate menial tasks and concentrate on the type of strategic thinking that makes us distinctly human.”

As a closing, he states that if we can reasonably anticipate these developments within the next year, the future landscape of AI innovation and its profound societal impacts are beyond imagination.

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Image Credit: Elevandi

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