AI is rapidly transforming industries across the globe, with Singapore at the forefront of the digital revolution in the Asia-Pacific region. According to the IDC, the potential for AI to reshape businesses is immense, with AI and generative AI investments projected to reach an astounding US$110 billion by 2028, growing at an impressive 24% annually. Through initiatives like the National AI Strategy and Smart Nation 2.0, Singapore is positioning itself as a global AI leader and a hub for responsible innovation. However, as AI becomes more embedded in the fabric of business and society, the need for robust data and AI governance becomes ever more critical.
The promise of AI is undeniably vast. Yet, with great power comes great responsibility. As organisations in Singapore embrace AI, they face significant hurdles such as data privacy concerns, biases in AI models, and the risk of misleading AI outputs, known as “hallucinations.” These challenges highlight the urgent need for ethical, transparent, and responsible data and AI governance to maximise the technology’s benefits while mitigating risks.
The urgent need for strong data and AI governance
Singapore’s commitment to a robust framework for AI is evident in the launch of the Model AI Governance Framework in January 2024, developed in collaboration with the Infocomm Media Development Authority (IMDA) and the AI Verify Foundation. This framework ensures AI development aligns with high ethical standards, safeguarding data privacy and security while maintaining public trust and global relevance.
As a result of the government’s clear commitment, it is now time for the private sector to take initiative. Business and technology leaders, compliance and data protection officers, and boardroom executives must prioritise data and AI governance to:
Navigate regulatory and compliance requirements
The framework introduces nine essential dimensions for managing AI systems. Among these, accountability stands out as a cornerstone, ensuring that all players across the AI development lifecycle take responsibility for the outcomes affecting customers. Maintaining data quality is critical for addressing challenges such as bias and inconsistencies in training data. Failure to do so will result in unreliable models and a lack of baseline safety measures.
In sectors like finance, where algorithms assess creditworthiness, this unreliability may lead to unfair decisions, denying customers access to essential services.
This regulatory initiative builds on Singapore’s Personal Data Protection Act 2012 (PDPA), which mandates that organisations appoint a Data Protection Officer. By enforcing such regulations, Singapore ensures its data protection framework aligns with global standards and enables organisations to responsibly manage AI’s impact on data security and privacy.
AI governance is vital for managing risks associated with the technology. Key features, such as an agent registry, are pivotal in overseeing enterprise AI agents, safeguarding sensitive data, and ensuring regulatory compliance. For example, the Australian Red Cross implemented an in-house AI governance framework that integrates transparent monitoring, accountability, and automated audit trails, providing a practical way to balance trust and compliance. These initiatives demonstrate that, with strong governance, organisations can meet regulatory requirements, avoid penalties, and cultivate a culture of trust.
Mitigate AI risks and protect business integrity
Poor-quality data can amplify biases in AI models, producing skewed outcomes. Inaccuracies — or hallucinations — in AI outputs also threaten decision-making reliability. Human oversight, combined with robust testing frameworks, enhances AI’s accuracy, reduces risks, and increases productivity. Ensuring high-quality, representative data is essential for AI systems to make fair, accurate recommendations and inform the right decisions.
In addition to data issues, governance and security concerns continue to complicate the adoption of AI. A report by Boomi, “A Playbook for Crafting AI Strategy,” produced in partnership with MIT Technology Review Insights, found that 45% of organisations view governance, security, and privacy issues as significant barriers to rapid AI deployment.
Despite the pressure to accelerate AI adoption, 98% of respondents stated they would delay implementation to ensure safe and secure deployment. This underscores the growing recognition among businesses that AI governance is not merely a regulatory necessity but also a strategic advantage.
Achieve effective data and AI governance
The successful deployment of AI hinges on strong data governance. Organisations must address key challenges, such as ensuring data liquidity — the ability to seamlessly access and analyse data from diverse sources — and maintaining data quality, as legacy systems often compromise accuracy. Poor-quality data not only limits AI’s potential but also increases operational risks, making strategic data management essential for success.
To unlock the full potential of AI, organisations must manage robust data ecosystems and adopt sound governance practices. This involves ensuring data integrity and transparency to support accurate, autonomous decisions, embedding ethical practices into automated workflows, and engaging board-level leadership to align AI integration with organisational goals and broader societal values.
Even smaller enterprises, despite limited resources, can achieve effective AI governance through partnerships with tech providers and the public sector, as well as through educational initiatives. However, they must carefully assess the risks of public AI models and ensure they use only data they can afford to lose, to safeguard their operations and long-term sustainability.
In the digital age, organisations must lead with responsibility, sustainability, and vision, placing AI and data governance at the heart of their strategy. Embracing human oversight and robust testing frameworks enhances AI’s accuracy, reduces risks, and increases productivity. By adopting technologies that facilitate governance, organisations can fuel long-term growth, benefiting both business and society.