How Singapore Overcame AI Governance Challenges: A Guide to Effective Solutions

On January 22, Singapore made an important move in AI governance. The Infocomm Media Development Authority (IMDA) released the Model AI Governance Framework for Agentic AI. This is the first of its kind—a guide for autonomous AI systems that don’t just help but actually take action.

While other regions like Brussels and Washington are still debating regulations, Singapore has stepped up to show a new approach. It’s a clear message for developing countries: you don’t have to wait for the “perfect” rules. You can adapt and evolve.

Governments everywhere face a common challenge—technology changes faster than policies can keep up. Consultations take time, and by the time regulations are drafted, the tech may have already advanced. Instead of rushing to legislate, Singapore’s framework encourages a more flexible approach. It’s designed to evolve, allowing for quick iterations every six months.

This iterative model makes sense in a fast-paced AI world. Comprehensive laws can become outdated before they even take effect. By focusing on practical guidelines, this framework targets four key areas:

• Capability-Based Risk Framing: It differentiates AI systems based on what they can do and how independently they can act. This helps determine risks better.
• Addressing Automation Bias: As AI becomes smarter, human oversight is crucial. The framework suggests practical ways to maintain effective monitoring.
• Technical Controls with Actual Specs: It lays out precise testing requirements for AI performance, making it easier for agencies without extensive AI expertise.
• Tiered Transparency: Citizens and employees need different information about AI systems. This helps to keep everyone informed.

Countries with fewer resources can actually turn this situation into an advantage. If constant monitoring isn’t feasible, they can design AI to operate effectively without it. This approach encourages better design from the outset.

Singapore is already putting this framework into practice. They’re testing systems in controlled environments, focusing on how AI can efficiently process data before rolling out citizen-facing services. This method allows them to learn and refine their approach continuously.

Typically, governments wait for the private sector to lead, deploying technology first and regulating later. But Singapore flips the script. By prioritizing government implementation, they build real expertise in how AI systems perform, leading to more informed regulations.

As countries build their digital systems, now is a prime time to integrate AI governance. It’s less costly to include good governance principles early than to fix issues later. Trust is essential here; a poorly functioning system can set back public confidence in technology for years. Singapore emphasizes human accountability and transparency, which can help build that trust.

Aligning with global standards like the OECD AI Principles can also help developing nations gain a competitive edge, especially when trying to access regional markets. By demonstrating alignment with recognized frameworks, they can attract investment and collaborations.

The IMDA is seeking real-world feedback to keep evolving this governance strategy, making it collaborative and adaptable. For those ready to move fast, the framework provides a clear path: adapt, test, and then deploy.

Ultimately, Singapore shows that moving quickly and responsibly isn’t a contradiction—it’s an achievable goal. The questions remain: will other governments follow suit? More importantly, can they match the pace of change in technology? Singapore’s model suggests that it’s not just possible; it’s a necessity.

Read also:
Why Asian governments are measuring the wrong things, Jan 26, 2026

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Mohamed Shareef is a former Minister of State for Environment, Climate Change, and Technology in the Maldives.

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