Much continues to be made of artificial intelligence’s (AI) capabilities, and it has proven its value in business in areas from driving innovation and uncovering new revenue streams to cost-cutting and efficiency. Southeast Asia is home not only to technology hubs like Singapore, but also to large B2C organizations like Grab, Shopee, GoJek and Tokopedia. These fast-growing consumer businesses naturally generate large amounts of data, making technology like AI vital to leverage that data to better serve customers. This means that for the remainder of 2020 and into 2021 we will continue to see steady progression towards artificial intelligence (AI) adoption in the region.
The race for digital transformation
Business leaders continue to understand that AI is a critical part of transforming and staying competitive, though many will face challenges as they find that AI adoption and implementation is harder than they have been led to believe. Critical research into business processes and problems- and the right AI solutions for each one- will be required for success with AI.
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The right talent is also vital for successful AI adoption. Governments and schools must continue to encourage people to focus on interdisciplinary educations that include both technical expertise- such as computer science and statistics- and how that expertise is applied in the real world, particularly in a business setting. The most sought-after technical talent are people who can translate technology application into business results. Business leaders should also focus on training current employees on AI trends and techniques to help speed up their digital transformation using resources they already have.
Specific applications of AI
AI will undoubtedly transform businesses of all sizes and across all industries, however in some regions and fields it already has very clear applications. Let’s take a look at the large B2C organizations like those mentioned earlier, such as Grab and GoJek, and how they might apply AI. Consumers consistently expect services on-demand, customized to their specific needs such as taxis, meals or groceries at their doorsteps. The companies providing these services have an opportunity to apply AI to personalize their products at a large scale, something that is often challenging simply due to difficulties bringing data together or managing multiple communication channels.
For many marketers, data remains siloed, so the first thing AI can do is pull multiple data sources into a single place. These sources might include website and app activity, loyalty program information, search engine traffic and so forth. Combined, the data provides complete profiles. With these profiles, AI can quickly pinpoint specific needs and interests. AI can also inform marketers about the best channel to reach the customer, with which product, and when. For example, over the weekend it might be a deal received on a tablet, and on Monday morning, a push notification on a smartphone. With AI, marketers can also quickly adapt messages to individual customers at a much greater scale than they can manually, including text, images and specific product features.
Financial services is another example where AI can play a critical role. The financial industry is big in Southeast Asia, given its home to banking hubs, and the ambition of several startups to address large populations of unbanked or underbanked people. Many of these organizations want to help provide non-traditional loans and credit to people who are not typically able to access these services. AI can be useful for helping to figure out credit ratings or risk for non-standard borrowers, particularly in fast-growing Southeast Asian economies such as Philippines, Indonesia, and Vietnam.
Consumers consistently provide data about themselves, and AI improves over time as it has more data to learn from. It will continue to uncover more hidden insights and patterns that businesses- whether they be banks, retailers or anything else- can’t find manually. Using AI to better understand and consistently anticipate the needs of customers to deliver relevant content, goods and services leads to meaningful, long-term relationships that translate to business growth.
Expecting more from AI
Generally, AI will also continue to solve more sophisticated problems, particularly as we see advancements in deep learning, the most advanced branch of AI technology. The ability to collect and process huge amounts of data will be vital for maintaining momentum in this area, and ‘data readiness’ will be a key focus for Southeast Asia in the coming years. This has been made increasingly clear during the pandemic- consumer needs have changed rapidly and businesses providing products and services need to be able to analyze data quickly to keep up with and anticipate what their customers will need and when.
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Overall, as AI adoption spreads, the bar for what it can deliver keeps going up and users- particularly in business settings- are expecting it to be able to do a lot more. Many things that were once considered technological breakthroughs- calculators, for example, followed by computers that could play chess (and win!), the ability to identify spam email and so on- are now baseline. This means AI solution providers must be able to not only meet but exceed and anticipate user expectations to help their customers remain relevant, nimble, and ahead of the competition.
Ensuring successful AI adoption
Businesses in Southeast Asia should therefore be bold about AI adoption. It’s because of rising expectations about what AI can do that businesses should be actively exploring ways it can help them. This also means approaching the journey of AI adoption realistically- it requires research, investment, experimentation and often some organizational change management as people get used to working alongside technology systems. Executives should expect their technology partners and providers to verify their solutions and demonstrate transparency, particularly as consumers everywhere become more vigilant about how brands and services use their data. In turn, these businesses need to be assured that any AI tools they employ or data experts they hire will be equally careful and responsible with personal data, while at the same time optimizing it to increase relevance and timeliness for customers.
In 2020 and beyond therefore, the biggest impact of AI will not come from large-scale applications such as self-driving cars. Long before things like autonomous vehicles become mainstream, many of us are likely to increasingly find ourselves working alongside AI, helping us to be more efficient and effective in our jobs. We can expect continued advancements and developments that will see AI further grow as an invisible and powerful force in business and in people’s everyday lives.
Contributed by Charles Ng, VP of Enterprise AI, Appier
About the author
Charles Ng is Vice President of Enterprise Artificial Intelligence at Appier, where he leads a team of AI scientists and engineers that are developing the next generation of Enterprise AI solutions.
An experienced data science leader with a successful track record of building solutions based on forecasting, optimization, and machine learning techniques to tackle complex real-world problems, Charles was previously the Chief Data Scientist of Coupang, Korea’s leading e-commerce company.
Charles has close to 15 years experience in his data science career working in companies such as IBM, DemandTec and Vivecon.
Charles has a PhD in Management Science and Engineering from Stanford University and a Bachelor of Science degree in Actuarial Science and Mathematics from Purdue University.