AI Deployment and Trust

In this video episode of Singapore Budget 2025 Insights by KPMG in Singapore, Sandrine Ah-Fa, Director, Managed Services, spoke to Lee Bo Han, Partner, R&D and Incentive Advisory, and James Wilson, Partner, Technology Consulting, Advisory, to discuss the recommendations for governance and standards, technology deployment, as Singapore undergoes digital transformation.

Read video transcript below.

One recommendation in this year's Singapore Budget 2025 Proposal is to raise awareness of the ethical use of AI by offering grants for AI governance training and certification and to fund AI governance research and development. What benefits would the above potentially bring?

Lee Bo Han: Ethical use of AI, like many wonderful inventions before it, may require careful and constant deliberation. Drawing comparisons to genetic modifications when it was first introduced, the considerations of when, where and how we should still use it has remained a contentious topic.

Ethics encompasses issues surrounding fairness, transparency and the ability to explain an AI’s decisions. The above are not necessarily attributed to the AI technology itself. Humans play a vital role in deciding whether the input and output of AI is fair, transparent and justifiable. As we all know, the ultimate weak link in cybersecurity could still be just one human being.

Therefore, more support for companies that invest in comprehensive AI governance training and certification programmes for their employees will be welcomed. To help humans in this process, we can also place increased emphasis on supporting R&D in AI governance technologies, including bias detection, data privacy solutions and transparent AI decision-making frameworks – just like what we did for cybersecurity R&D.

Technology is redefining economic and operational boundaries, including supply chains. AI is proving instrumental in addressing supply chain bottlenecks and enhancing efficiency. Could you elaborate on how businesses can leverage AI to bolster the resilience and sustainability of their supply chains? Additionally, what role would incentives and grants play in driving this transformation?

Lee Bo Han: AI has always been a potential game-changer for supply chain management. It was the accessibility of technology, data and computing performance that held back its potential.

There are advances in AI where now, we have large-scale pre-trained AI models that are more accessible. Having companies progress in their digital transformation with data being more accessible and structured, the overlay of AI models such as generative AI can help process vast datasets. AI can identify patterns and predict potential disruptions in supply chains such as delays, shortages or even geopolitical issues. It can optimise routes, manage inventory levels and streamline transportation processes. In all, it can reduce cost and improve efficiency and AI can help dynamically adjust plans based on real-time data which is incredibly powerful. To help optimise costs, AI can analyse market trends, supplier performance and pricing data. This allows businesses to negotiate better deals and identify alternative suppliers.

Saying all that, the above are not new ideas for supply chain management, but we are of the view that AI can now supercharge this transformation like some of the examples we are seeing in the healthcare sector. These capabilities will not only strengthen resilience but also help with sustainability. That said, navigating effective use cases of AI on supply chain specifically within each industry could be challenging for businesses. One way to expedite this form of transformation is to curate support schemes to adopt AI, again, specifically for supply chains within each industry transformation map.

As the backbone of our economy, SMEs play a crucial role in Singapore's success. Yet, they may be under-resourced to effectively scale and implement effective solutions. How can we ensure they thrive in the next phase of digital transformation and effectively integrate AI solutions to boost their competitiveness and innovation?
 

James Wilson: Most organisations face challenges when it comes to deploying new technologies and SMEs suffer from that more than anyone. Success requires access to a skilled talent pool, robust digital infrastructure and an effective innovation ecosystem. That is really hard for SMEs, so we recommend several key strategies. First, we encourage the adoption of government-built technology enablers and grants to accelerate AI adoption. SMEs often face financial, infrastructure and talent constraints that hinder their ability to adopt AI. Encouraging the use of technology enablers and enhancing and expanding existing grant programmes will help SMEs implement AI solutions without incurring the significant capital expenditure that they might think is there. Second, there should be increased funding for collaborative efforts to develop AI standards and governance. Establishing these will be essential for providing businesses with the necessary reassurance to invest in AI technologies.

Funding collaborative efforts between private and public sectors to set national standards for AI governance can also run alongside incentives to upskill the digital workforce. Providing substantial funding for AI governance research and development and promoting the utilisation of R&D for AI governance tools and methodologies will drive innovation in how business can tackle the complexities of AI deployment.

Finding skilled AI talent is also a challenge across all organisations. What are some ways to develop AI skills within Singapore’s workforce to support the digital transformation of its economy?
 

James Wilson: AI is a relatively new and really fast-evolving field. Finding skilled talent can be a challenge for all organisations. Developing AI skills within Singapore’s workforce can be really daunting but there are some key areas that can support this transformation. First, funding programmes for upskilling and developing tech literacy across all levels of the workforce is crucial. This would include investments for building soft skills that enable workers to remain adaptable in the face of technological change. Additionally, it should include know-hows on integrating AI into business processes and drive change and innovation management.

Second, incentivising firms and institutions to invest in short-term certification programmes can help boost talent in high-demand areas such as AI. Micro-credentials provide flexibility and may be more cost-effective compared to traditional degrees, which can make it easier for both employees and employers to address immediate skills gaps. Firms can be incentivised via grants to support employees in gaining AI credentials and be further encouraged to create reward programmes for certifications in critical areas such as AI and digital transformation.

Finally, offering grants for AI governance training and certification programmes is essential to ensuring that AI activities remain ethical and compliant. Financial incentives such as grants will encourage businesses to provide continuous learning opportunities to staff. It will help employees to be well equipped to adopt ethical AI practices and then better integrate them into the work culture. This will also ensure that employees are more effective partners to the business and align their efforts with business goals.