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. 

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. 

What sets AI.dea apart for Enterprises

1. Real AI Proof-of Concept, Not Theory 

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. 

2. Curated Access to Trusted AI Vendors 

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. 

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. Buit-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. 

5. Government-Supported & Cost Efficient 

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

Day 1

Module 1: AI Adoption in the Business Process Landscape – Overview for Leaders

1. Aligning AI with organisational goals, identifying high value use cases.

2. Managing change, upskilling teams, and addressing resistance.

3. Ensuring readiness of data systems, platforms, and integrations.

4. Addressing ethics, legal requirements, and cybersecurity safeguards.

5. Tracking KPIs, performance, and planning future roadmaps.

Module 2: Aligning AI with Business Strategy

1. Define and prioritise AI use cases based on strategic needs

2. Translate AI opportunities into tangible business outcomes

3. Identify cost-benefit parameters linked to AI

Workshop Project: AI Solution Trial Introductions

1. 2-3 AI Solution partners to present their solutions

2. Project teams are to take note and gather information for assessment to their company’s needs requirements

Module 3: Introduction to Cybersecurity for AI

1. Cybersecurity Overview 

2. Cyber Risks in SMEs 

3. Basics of AI and Machine Learning 

4. AI and Cybersecurity Synergy 

Module 4: Cyber Threats and SME Vulnerabilities

1. Common Threats: Phishing, Malware, Insider Threats 

2. Vulnerability Identification 

3. Risk Assessment Basics 

4. Real-World Case Studies 

Day 2

Module 5: AI Cybersecurity and Risk Management

1. Identify risks across data pipelines and AI models

2. Design safeguards for AI system integrity.

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: Infrastructure and Systems Integration

1. Audit current IT capabilities for AI compatibility

2. Define data integration and platform requirements

Workshop Project: Mapping Strategy to Plan – Execution & KPI Alignment

Review the various outputs from each module, including information from AI Solution providers and identify gaps or refinements for business needs, considerations and requirements.

Day 3

Module 8: Organisational Change and Workforce Enablement

1. Design a people-first change management roadmap

2. Create training plans and communication strategies

Module 9: Blueprint Synthesis Workshop

1. Align all AI initiatives into a cohesive business blueprint

2. Identify any gaps and overlaps across strategic, technical, and governance dimensions

3. Prepare a stakeholder-ready narrative and documentation pack

Module 10: Workshop Project – AI Implementation Planning Simulation

Project Brief: Teams will create a comprehensive AI Implementation Blueprint, including:

1. Business-aligned AI use case

2. Maturity assessment and capability gap plan

3. Legal and cybersecurity requirements

4. Infrastructure, resources, and cost plan

5. Change management and workforce enablement strategy

Course Schedule