Gerry Chng:
Hi Wendy and Bo Han, how have you been?
Wendy Lim:
I’m great, and I’m glad to be here today.
Lee Bo Han:
Hi Gerry, looking forward to our conversation today.
Gerry Chng:
Today, we are tackling a critical question: How can Budget 2026 prepare enterprises for an AI-driven future in the Intelligent Age?
The reality is this – AI adoption can be a game changer, but many enterprises are not ready. Governance gaps, leadership capability gaps, and weak data foundations are holding them back. If we want businesses to innovate responsibly and competitively, we need to help them get there. So, what should Budget 2026 prioritise?
Wendy Lim:
Thanks, Gerry. You’re absolutely right. AI readiness isn’t about deploying technology. It’s about embedding trust and accountability into every layer of our enterprise, and it starts with three things.
First, building public trust. Singapore has done well with the Model AI Governance Framework, but the next step is about a regional Trusted AI mark. This isn’t just another logo – it’s a recognised assurance that AI systems have rigorous governance and ethical standards. For businesses, it means smoother cross-border operations and faster innovation. For partners and consumers, it means confidence in fairness, safety, and transparency.
Gerry Chng:
That’s a good point. In a digital economy, trust needs to be verifiable. A Trusted AI mark could become the gold standard for ASEAN, enabling mutual recognition and reducing compliance friction. The Trusted AI mark would also allow firms to deploy AI solutions across the region without having to worry about multiple regulatory requirements.
Lee Bo Han:
Yes, Gerry. It’s about creating a platform for alignment on ethical standards, data governance, and assurance tools across the region. This mark should be underpinned by Trusted AI by Design principles – embedding governance, risk management, and ethical considerations into AI systems from the ground up.
It’s not about retrofitting compliance. It’s about building trust into the architecture of AI solutions. And that trust is what accelerates trade and collaboration.
Gerry Chng:
Now, beyond trust, we also need to think about leadership. AI governance cannot sit solely within the CTO function. So, what are we recommending here that will help enterprises?
Lee Bo Han:
Yes, not just the CTO. Boards and senior executives should understand not just how to use AI applications, but corporate governance for AI. This includes areas like ethical deployment, risk oversight, and change management of the workforce.
So, our recommendation is a budget fund for AI governance and board-readiness. And this goes beyond just awareness of AI as a technology. It’s about equipping leaders to steer enterprise-wide transformation responsibly.
To accelerate readiness, Singapore should introduce a dedicated academy where global experts in leadership with innovation, can lead structured upskilling and governance programmes, transferring the best knowledge, practices, and also mentoring local boards.
Wendy Lim:
To add to Bo Han’s point, to make this sustainable, any incentives that can include tax benefits, grants, or fast-track work-pass renewals should be tied to measurable outcomes. These could be the numbers of executives trained, boards certified, and governance frameworks implemented.
A workforce marketplace could match these “master trainers” with firms that require their expertise, whether full-time, part-time or even on a project basis.
Gerry Chng:
Agreed. Closing capability gaps starts at the boardroom. And here’s why this matters. Board-level leadership is crucial for driving trust, adaptability and sustained value creation from the top to the bottom. Having that buy-in at the highest levels fosters a culture of innovation and collaboration.
Boards and senior management also need the right training in emerging technologies, not just on how AI works, but how it can be applied strategically to the business. This capability helps them to lead innovation and changes within their organisations and reduces the communication and understanding gap with the business units that are driving those transformations.
Without this alignment, from my experience, transformation is far more difficult.
And that brings us to the third pillar, data governance.
Wendy Lim:
Yes, data governance is often discussed, but for AI, it’s non-negotiable. Without clean, integrated tech data, AI outputs are flawed, and trust collapses. Poor data quality compromises everything, including your Trusted AI mark.
So our final recommendation is for Budget 2026 to help businesses by introducing a guided data governance framework toolkit. This will be a practical baseline for firms to ensure data quality, integrity, and compliance.
Gerry Chng:
This toolkit will provide clarity on best practices for data governance, AI governance, and risk management, so businesses can confidently deploy AI solutions. It also enables measurable improvements in data quality and accuracy, which fuels innovation and sustainable growth. The toolkit could mirror the SG Cyber Safe Programme, incorporating trust marks to recognise firms that meet predefined governance and quality standards.
Lee Bo Han:
Agree, Wendy and Gerry. Such recognition is important to promote accountability, transparency, and public confidence in the ethical use of AI – while motivating businesses to continue strengthening their data governance and management practices.
Robust data governance is the foundation for building AI use cases to drive innovation, process improvements and operational efficiencies. Without robust data governance, enterprises cannot scale AI responsibly or competitively.
Wendy Lim:
To sum up, public trust, leadership capability, and data integrity are the cornerstones of AI readiness. Budget 2026 is an opportunity to anchor innovation in accountability and long-term resilience. If we get this right, Singapore can lead the region into the Intelligent Age with confidence.
Gerry and Bo Han, thank you for your insights today.
Lee Bo Han:
Thank you.
Gerry Chng:
Thank you, Wendy.
