AI is changing the way organizations innovate and transform digitally. What does this paradigm shift spell for businesses in Asia Pacific?
All across the Asia Pacific, generative AI and other applications of AI are the talk of the town. Many organizations list AI among the top technologies they are exploring or investing in this year.
In this age of AI, the digital innovation and business transformation journey is taking on a new turn, leading into unchartered territories and new milestones.
To gather key insights into AI trends, challenges and best practices, DigiconAsia engaged in a Q&A with KC Yeoh, Chief Executive Officer, Temus, which has recently partnered with AISG to develop AI talent and skills.
How has the relationship between business and technology changed in the age of AI?
Yeoh: Business models have evolved, from production and marketing to relationship and intelligence. Artificial intelligence (AI) has fundamentally changed how innovations and inventions can impact businesses.
Today, to compete effectively, organizations need to adopt the characteristics of an AI factory to ingest large quantities of data sets and develop data-driven solutions to augment any part of the business. Tech giants like Google, Facebook, and Alibaba, are relying more on the value delivered by algorithms than on processes run by employees.
This points to an interesting trend: software is now at the core of the enterprise while humans are moved to the edge; fully automated machines run processes that are designed, coded, and monitored by humans. Implemented well, the AI factory can free firms from traditional operating constraints and enable them to compete in unprecedented ways.
What are the key challenges organizations face in implementing and scaling AI initiative?
Yeoh: Many companies and sectors still lag in AI adoption. Formulating a viable AI strategy can be as complex as the technology itself. The three biggest challenges are:
Shortage of talent: There are insufficient AI professionals with the experience and training needed to implement the required infrastructure and organizational change. This is a real and pressing problem for most businesses wanting to digitally transform and adopt AI as part of their roadmap.
This skills gap is one that Temus aims to bridge through our partnership with AISG. Apprentices under AISG’s AI Apprenticeship Programme (AIAP) will gain more opportunities to work on real-world AI development and deployment projects, in turn accumulating more experience and training.
Overcoming silos: A common issue with organizations is that their infrastructure exists in silos. They are often not integrated, resulting in fewer people being able to access the data, compared to an organization that invests in modern cloud-based infrastructure.
Cultural change: Digital transformation starts with a mindset shift. Leaders must inspire their teams to view digital transformation not merely as something to achieve and then forget, but as a constant process of mastery and adaptation for an uncertain digital future.
We see these challenges extend beyond companies to the public sector, as governments like Singapore’s look to push the envelope for innovation and become more digitally driven. Singapore’s refreshed Industry Transformation Map 2025 (ITM) will play an important role in strengthening the nation’s competitiveness, with the government, industry players and research institutions working hand-in-hand to create new ventures that generates new revenue pathways.
As part of our partnership with AISG and their 100 Experiments (100E) programme, Temus’ end-to-end digital transformation capabilities looks to draw on this interconnectivity to help Singapore enterprises become AI-ready – both in terms of their infrastructure and people.
What are some emerging AI trends in Asia Pacific?
Yeoh: Broadly, we see two clear drivers for AI adoption in the region:
- Hyper-automation will revolutionize work
Hyper-automation will encourage a new form of enterprise growth as it takes a holistic approach in optimizing and integrating processes at scale to optimize productivity. In recent years, the Asia Pacific (APAC) region has witnessed many businesses marrying several point solutions including AI, Robotic Process Automation (RPA), and machine learning (ML) to tackle friction points in their operations. - AI democratization will continue The goal of democratization is to level the playing field so that both individuals and organizations can benefit from AI. At present, 90% of APAC enterprises are using or planning to use AI or ML applications over the next 12 months, according to an IDC report.
How should organizations leverage AI to create long-term value? What are the key factors driving successful AI transformation for an organization, especially in unlocking both economic and social impact?
Yeoh: AI is a game-changer that makes businesses more efficient and responsive, increasing productivity and innovation, and improving our overall quality of life. However, to fully extract the value of AI, organizations should adopt an incremental rather than a transformative approach to developing and implementing AI. This can be done by focusing on augmenting rather than replacing human capabilities.
AI can support three important business needs: automating business processes, gaining insight through data analysis, and engaging with customers and employees. To get the most out of AI, organizations must first understand which technologies perform what types of tasks, create a prioritized portfolio of projects based on business needs, and develop plans to scale up across the company.
Ultimately, the key to leveraging AI today is recognizing what it is and what it is not.
It is critical that enterprises do not fall into the trap of replacing too large of a workflow with AI algorithms. Human judgement is still by far the best approach to many business tasks. Human tasks which are primarily based on pattern recognition or perception are ripe for AI solutions. If businesses can focus AI on what it does well, achieving breakthroughs and scaling new heights can be a reality, ultimately unlocking both economic and societal impact.
Is there a way for organizations to strike the right balance in using AI ethically and responsibly? And how do human skills and empathy fit into this equation?
Yeoh: The challenge lies in developing systems that are trustworthy and transparent.
Besides equitable data collection, responsible data sharing is also key in building trust in AI. The collection, usage and distribution of data today require different levels of compliance to protect user privacy and prevent misuse. Ultimately, it is about respecting user consent and trust.
If an organization ensures that they are doing things for the benefit and with the agreement of users, ethical and responsible AI usage will come naturally.
Human skills and empathy are also vital components in the usage of AI. However, one must see AI as a way to enhance human skill, not as an attempt to replace humanity. As we begin sharing the workforce with more machines, human soft skills such as empathy will be at a premium and a moral responsibility.
All in all, developing trustworthy AI solutions and embracing responsible AI frameworks will not only help organizations build stronger infrastructure, but also improve business reputation and competitiveness in the long run.
