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Southeast Asia is becoming the next battlefield for high-tech innovation. The forecast suggests that AI could add USD 1 trillion to the local economy by 2030.
A key benefit of this transformation is AI native, a new generation of rising. These are individuals who grew up in this technology and are already familiar with AI and its benefits. However, in the Asia-Pacific region (APAC) region, these AI natives report that nearly 75% of organizations are lagging behind adoption of generated AI.
AI offers immeasurable possibilities, but success requires not only investing, but also managing employee expectations when it comes to hiring AI. For businesses to stay on their forehead, they need to rethink the process, start with the basics and rethink how they can be set up for success in AI.
Three important steps companies should consider
Like major investment decisions, it is important that the organization is first set up for AI success or ensure the risk of wasted effort and resources. The same IDC study found that in the broader Asia-Pacific region (APAC) region, half of the organizations surveyed have failed up to 29% of AI or machine learning projects over the past year, citing challenges such as internal skills gaps. These challenges often arise from AI implementations that occur in silos.
Organizations need to recognize that successful implementation of AI requires an organization-wide approach and that shared responsibility must be incorporated throughout the company.
– Lucas Lu, Asia Head, Zoom
From human resources (HR), security and data protection to responsible AI and legal teams, every department must work together to develop an implementation framework. For example, HRs need to start building relevant training programs designed for different age groups and expertise levels, as well as hire the right people to drive AI development and maintenance beyond initial implementation.
This has a direct impact on AI success. Deloitte's 2024 report found that APAC organizations with a more mature AI governance framework had an increase in return by nearly 5%.
- Make AI decisions based on business impact
AI technology isn't perfect for all sizes. Rather than simply following what others are doing, organizations need to have clear answers about the need for AI and why it helps them target a very specific business need. Different use cases require different approaches to implementation.
For example, organizations seeking to deal with immediate talent constraints may try to leverage AI-powered chatbots. This helps reduce reliance on human agents while maintaining the same level of customer service. Teams can also utilize AI-powered translation and transcription capabilities to serve customers in other markets, even if there are no local representatives who speak the language.
This is especially important for linguistically diverse businesses in the Southeast Asian region. In such a scenario, an organization can begin the implementation process by identifying and integrating the associated AI applications into the platform that is already using.
With AI journeys, businesses may also want to consider building an AI-first total experience across the organization, reducing the experience of both employees and customers. The same platform helps agents provide real-time, accurate responses to customers by intelligently integrating information across departments, helping employees become more productive with their AI assistants.
This can disrupt or overhaul existing methods of working, but it can ultimately be more cost-effective and lead to strong returns on revenue.
Regardless of the approach, the early stages of implementation involve a lot of learning and experimentation. During this time, leaders should understand the barriers to adoption on ways that can further improve AI deployment, and always seek feedback from early users.
- Teach employees to work with AI rather than compete with AI
An equally important step is to build a team of internal AI ambassadors. However, this is a continuing shortage of many organizations in Southeast Asia.
A recent study reveals that Singapore's Gen Z professionals are more interested in job safety in an AI-driven future than any other age group.
This is concerning for two reasons. First, it emphasizes that this problem persists in more mature markets like Singapore. Second, Gen Z – or simply the AI-Native generation – is the most unsettling. This indicates a broader lack of trust by organizational employees to equip them for the future of AI.
Technical training programs that showcase AI use cases are a good start, but these programs need to be able to evolve alongside AI advances. Companies can also use AI natives to become supporters within their teams. The team is just becoming more and more multi-generational.
This helps to promote a culture of continuous learning. Leaders should also be proactive in addressing employee concerns about AI. This can be done through a regular town hall or resource hub with a repository of case studies on how AI expands, rather than replacing human contributions.
AI is constantly evolving and never static
Ultimately, adoption of AI in Southeast Asia remains a goal of corporate movement as its capabilities and real-world applications continue to evolve at the speed of change. Organizations need to move from a reactive attitude to a proactive approach, starting with embracing an AI-first mindset that keeps people at the core of their strategy.
This includes not only laying the foundation for AI implementation, but also actively preparing the workforce in the AI era. Taking an AI-first approach ensures that Southeast Asian organizations are equipped to accommodate the next wave of AI innovation.
Lucas Lu is Zoom, head of Asia
