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AI.dea is the only programme that enterprises will need before committing to full-scale AI investment and deployment. The programme focuses on practical, hands-on experimentation to help you identify what truly works for your business. We guide you to design, build and validate a real-world AI proof of concept (PoC) – reducing guesswork, risk and unnecessary cost.Ìý

By the end of the programme, you will walk away with a clear, actionable AI adoption strategy to plan: business aligned use cases, governance and risk frameworks, as well as execution playbooks that prepare your organisation for scalable, sustainable AI implementation.Ìý

What sets AI.dea apart for Enterprises

1. Real AI Proof-of Concept, Not TheoryÌý

Apply your learning directly to your own business scenario through a hands-on PoC. Test it safely in a sandbox environment before committing any major investment.Ìý

2. Curated Access to Trusted AI VendorsÌý

Gain access to a pre-vetted pool of reputable AI solution providers. We help you match with the right vendor to co-develop a PoC tailored to your specific needs.Ìý

3. Guided Strategy to Plan Journey

Leaders are guided through a structured approach to define AI ambition, assess readiness, and chart a clear, risk-aware roadmap for confident organisational adoption.

4. Built-In AI Governance, Cybersecurity & Legal Readiness

Develop a strong foundation in AI governance, risk management, cybersecurity and legal considerations, ensuring your organisation adopts AI safely and responsibly.Ìý

5. Government-Supported & Cost EfficientÌý

Benefit from significantly subsidised fees through government support, making AI experimentation affordable and accessible for enterprises.

Day 1Ìý

Module 1: AI Implementation Landscape Overview

1. The evolution from experimentation to enterprise AI maturity

2. Key industry trends in AI adoption across sectors (e.g., finance, healthcare, logistics)

3. Common implementation challenges: data quality, model integration, change resistance

4. The role of cross-functional teams in bridging the gap between strategy and execution

5. Understanding this context ensures participants can position their AI efforts within broader market realities and internal readiness.

Module 2: Understanding AI Technology and Its Lifecycle

1. Define the AI lifecycle and where project leaders fit in

2. Identify AI use case categories and business impacts

3. Understand limitations, dependencies, and system fit

Module 3: Future Trends, Security Automation & AI GovernanceÌý

1. Predictive Analytics and Deep LearningÌý

2. AI Explainability & BiasÌý

3. Ethical Frameworks (Singapore Model, OECD)Ìý

4. Building Trust and TransparencyÌý

Module 4: Risk Mitigation, Compliance & Incident Response

1. SME-Specific Compliance (PDPA, CSA)Ìý

2. Incident Response PlanningÌý

3. Cybersecurity Strategies (backups, detection, containment)Ìý

4. AI – Cyber Resilience Workshop or Role Play Exercise PlanningÌý

Day 2

Module 5: AI Project Planning and Feasibility

1. Conduct feasibility and risk analysis (technical + operational)

2. Select suitable AI techniques and tools.

3. Define value-based prioritisation.

Module 6: Data Readiness and Management

1. Assess current data maturity and availability.

2. Identify data quality, accessibility, and governance requirements.

3. Plan for sustainable data management and continuous improvement.

Module 7: Data Strategy and Preparation

1. Build a robust data sourcing, cleansing and labelling process.

2. Map data security, governance and usage rights.

Module 8: AI Model Development and Integration

1. Select and validate AI models.

2. Align model output to existing systems and workflows.

Day 3

Module 9: Execution, Monitoring, and Continuous Improvement

1. Execute AI deployments securely and ethically

2. Define KPIs and improvement protocols

Module 10: Workshop Project – Implementation Continuation

Complete the AI Blueprint by integrating technical, strategic, and governance plans into a single implementation guide.

Scenario based Simulation Exercise (AI – Cyber Resilience Workshop)

Simulate real-world cybersecurity challenges that SMEs may face when integrating AI solutions into their business processes.

Course Schedule