Lead with clarity, control, and foresight. This training enables leaders to unlock business value, ensure compliance, and build trusted foundations for AI adoption in a rapidly evolving global data ecosystem.
Data has been dubbed as “the new oil”, employing a metaphor to highlight its importance to power businesses as well as its risks to get burned and pollute its environment. While there is an awareness of the value of data, especially in the age of AI, it also has been recognised that data can be sensitive, costly to maintain, and negatively impact the interests of individuals, business, and society. It is estimated that data accounts for 40% of overall data centre costs, while over 80% of that managed data is considered stale as it does not yield any business value.
While data legislation has historically been perceived as an economic burden and innovation inhibitor, recent strategic policy shifts aim to reduce barriers of data sharing to benefit society. For example, the EU Data Act, which was enforced in September 2025. It increases the incentives of data holders to voluntarily enter into data sharing agreements, reduces the legal uncertainty, levels imbalances in power, and mandates technical interoperability.
This course condenses the knowledge leaders need to navigate data strategy in the age of AI. It provides a concise overview of the global data ecosystem, current and emerging policies, and practical guidance to identify business opportunities, assess risks, and validate strategic decisions. The focus is on strategic decision-making, not technical execution, empowering executives to guide their organisations with confidence.
Dr Saerbeck brings over two decades of experience in AI, digital innovation, and risk management, specialising in building AI solutions that meet rigorous standards for safety, security, and compliance. As CTO and Co-Founder of AIQURIS, a TUV SUD Venture, he drives the mission to enable organisations to deploy AI in high-stakes environments with confidence. His work has been instrumental in establishing the TUV SUD AI Quality Framework, now a benchmark for AI auditing and certification across industries such as manufacturing, healthcare, and aerospace.
| Topic | Description |
|---|---|
| Introduction and motivation (20 minutes) |
|
| Core concepts of the data ecosystem (30 mins) |
|
| Regulatory landscape, policy approaches and industry best practices (120 mins) |
|
| Data opportunities and costs (40 mins) |
|
| The data trust architecture (30 mins) |
|
| Data risk mitigation (30 mins) |
|
| Practical data governance use-case exercise (40 mins) | |
| Develop and validate a compliance strategy (30 mins) |
|
| Summary and Q&A (20 mins) |
Clear understanding of key roles, responsibilities, and terminology related to data and dataspaces
Strategic awareness of data ecosystems and business value of trusted data sharing
Insight into regulatory principles and global best practices
Actionable strategies to assess organisational maturity, investment priorities, and risk
Practical guidance to draft, validate, and improve your data strategy
This training is ideal for leaders shaping data and AI strategy in their organisations:
CIOs, CDOs, and Chief AI Officers
AI governance leads, compliance officers, and risk managers
CTOs, DPOs, and data protection leads
Strategy, procurement, and transformation executives
Duration: 1 full day or 2 x half days
Delivery Options: Virtual instructor-led or on-site in Singapore
Led by Senior Thought Leaders: Active contributors to the global regulatory and data governance ecosystem
