AI GUIDE FOR BOARDS IN SINGAPORE Section V: Organisational Resilience and Capability
9.2 Scaling AI
• Insu cient workforce preparedness increases the likelihood of operational errors, misuse and governance failures. Digital resilience is the organisation’s ability to prevent, withstand, respond to and recover from disruptions while maintaining critical business operations and AI-enabled services. Employees and business units are more likely to adopt AI con dently and responsibly when there is clarity around how data is handled, what controls are in place, and how AI aligns with existing governance and operating standards. e ability to deploy AI securely, govern its use eectively, and maintain reliable access to trusted enterprise information enables AI adoption to move beyond isolated pilots into scalable enterprise capability.
Digital resilience is integral to successful AI strategy.
Large-scale AI deployment requires resilience and governance across multiple interconnected layers, including: • Data: Data lineage, privacy protections, access controls and safeguards against data poisoning. • Model: Model evaluation, adversarial testing, guardrails and monitoring for dri and misuse. • Infrastructure: High-availability compute environments, redundancy and operational continuity measures. • Operations: Continuous monitoring, incident response and human oversight mechanisms to maintain accountability and governance. AI ampli es existing enterprise weaknesses through the following ways. • Poor data quality produces unreliable outputs. • Weak cyber security controls expose sensitive data, models and systems to adversarial threats. • Fragile infrastructure increases the risk of service disruption.
Boards should view resilience and trust as practical enablers of AI value creation rather than purely compliance obligations.
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