Navigating cultural differences and digital-savvy customers will be key to scaling AI adoption in Asia, tech executives say
For example, Asian companies tend to hire lots of narrowly focused knowledge workers, unlike the U.S., noted Thinking Machines founder Stephanie Sy.
The sudden explosion of generative AI, starting with the release of ChatGPT in late 2022, has sent business leaders scrambling to adopt the new technology. Almost three-quarters of companies surveyed by Accenture in 2023 reported they were prioritizing AI over all other digital initiatives.
Yet surveys of middle managers find that employees are more unsure than their bosses whether their workplaces are ready to adopt this new technology.
On Tuesday, business leaders speaking at the Fortune Brainstorm AI Singapore conference shared how to best roll out AI in Asian markets, a different environment from what’s happening in the U.S. (Accenture is a founding partner of the Brainstorm AI conference series).
Businesses in Asia will hire people to solve their problems instead of applying technology, which means the “nature of knowledge work is very different,” said Stephanie Sy, founder of the Manila, Philippines–based data tech consultancy Thinking Machines. That means Asian organizations will have a large pool of knowledge workers who are narrowly focused on particular tasks, compared to their U.S. peers.
For adoption to happen, management needs to think about how AI applications will complement workers and follow through on implementation, rather than just viewng technology as a silver bullet, she explained.
Still, many Asians are very familiar with technology, noted Suthen Thomas Paradatheth, chief technology officer at Grab. Southeast Asia’s young population is very mobile-phone-friendly, and “pervasive interactions” on those mobile devices means a company can really “spin the data flywheel.”
More data means more opportunities to fine-tune an AI application, and that means encouraging people to use these services more, which means companies will need to “put customers first” when developing AI applications and try to “solve customer problems,” Paradatheth says.
Speakers on Tuesday noted that scaling would also require developers to account for cultural differences, particularly around language.
“The power of AI comes from its ability to understand language, more data, and more information,” said Arvind Jain, cofounder and CEO of Glean, a startup that uses AI to help companies search their own knowledge base.
The size of the U.S and Chinese economies mean that much of AI development is geared toward an English- or Mandarin Chinese–speaking audience, leaving other languages and dialects behind, but that means there’s also opportunity for other players to step in and fill the gap.
Ahmed Mazhari, president of Microsoft Asia, cited an app geared toward farmers in rural India. A farmer could “speak into WhatsApp, which would then translate it, voice-to-text, [a phrase like] ‘go and search for subsidies,’ and return [the answer] back to the farmer in the local language.” Mazhari added that the app was available just six weeks after the release of OpenAI’s GPT 3.5 model in 2023.
Sy suggested that developers start to integrate the nuances when people of different social standings communicate in languages like Thai or Bahasa Indonesia.
“Once you add that next layer on top of it, you’re going to get people loving [AI] even more,” she said. “Wanting to use [AI] every single day is the number one ranking factor in scalable adoption.”
