Responsible technology.
Meaningful conversations.

Artificial intelligence can create significant business value, but sustainable adoption depends on trust.

This session explains the foundations of trustworthy AI and the responsibilities organisations should address when designing, procuring or deploying AI systems.

Topics can include:

• Accountability and ownership
• Transparency and explainability
• Privacy and data protection
• AI security
• Human oversight
• Fairness and bias
• Risk assessment
• Ongoing monitoring
• Responsible innovation

Audience outcome: Participants will understand the key elements of trustworthy AI and the practical questions their organisations should ask before and after adopting AI.

Many organisations have established responsible AI principles but have not yet developed the processes required to implement them.

This session explains how AI principles can be translated into a practical governance operating model.

Topics can include:

• AI governance roles and committees
• AI policies and standards
• AI use-case inventories
• Risk classification
• AI impact and risk assessments
• Management reporting
• Documentation requirements
• Performance and risk monitoring
• AI incident management

Audience outcome: Participants will understand the core components of an operational AI governance programme and how those components fit together.

Data governance and AI governance are closely connected, but they are not the same.

This session explains the relationship between the two disciplines and why responsible AI cannot be achieved without reliable data governance.

Topics can include:

• Data quality and AI performance
• Data ownership and accountability
• Data lineage and traceability
• Privacy and lawful data use
• Training-data considerations
• Model-specific risks
• Human oversight
• Coordination between data and AI governance teams

Audience outcome: Participants will understand where data and AI governance overlap, where they differ and how organisations can coordinate the two.

AI risk does not begin when a model is deployed.

Risks can arise during strategy development, use-case selection, data preparation, model development, procurement, testing, deployment and ongoing operation.

This session presents a lifecycle-based approach to identifying and managing AI risk.

Topics can include:

• AI strategy and planning
• Use-case selection
• Data sourcing and preparation
• Model development or procurement
• Testing and validation
• Deployment and integration
• Human oversight
• Performance monitoring
• Model changes
• Retirement and decommissioning

Audience outcome: Participants will be able to identify where AI risks can emerge and where governance controls should be introduced.

Privacy by design requires organisations to address personal-data risks before implementing a new project, system, product or service.

This session explains how privacy requirements can be integrated into business and technology projects from the beginning.

Topics can include:

• Identifying personal data
• Defining processing purposes
• Data minimisation
• Access control
• Data retention and deletion
• Third-party processing
• Privacy impact assessments
• Security requirements
• Collaboration between privacy, business and technology teams

Audience outcome: Participants will understand how to identify privacy risks early and convert privacy requirements into practical project actions.

Data protection expectations are developing rapidly across the GCC, requiring organisations to establish clear governance, accountability and operational controls.

Drawing on my practical consulting experience, this session discusses how organisations can approach privacy implementation in Bahrain and Saudi Arabia.

Topics can include:

• Privacy governance structures
• Data ownership
• Records of processing activities
• Data-subject rights
• Privacy impact assessments
• Retention and deletion
• Third-party management
• Policies and procedures
• Training and awareness
• Implementation roadmaps

Audience outcome: Participants will gain a practical understanding of the organisational capabilities required to implement a sustainable privacy programme.

Privacy, cybersecurity, data governance and AI governance are often managed separately, even though they address interconnected risks.

This session explains how these disciplines can be brought together under a broader digital trust approach.

Topics can include:

• The foundations of digital trust
• Privacy and security dependencies
• The role of data governance
• AI-related trust risks
• Organisational accountability
• Customer and stakeholder confidence
• Regulatory preparedness
• Coordinated governance and reporting

Audience outcome: Participants will understand why fragmented governance creates risk and how a coordinated approach can strengthen trust and resilience.

Policies establish direction, but policies alone do not create effective governance.

This session explains how organisations can convert regulatory requirements and internal policies into practical operating mechanisms.

Topics can include:

• Roles and responsibilities
• Procedures and workflows
• Internal controls
• Assessments and checklists
• Evidence requirements
• Performance indicators
• Management dashboards
• Training and awareness
• Compliance monitoring
• Continuous improvement

Audience outcome: Participants will understand how to move from written requirements to measurable and sustainable implementation.

My career has progressed across software development, enterprise systems, IT management, information security, privacy, data governance and responsible AI.

In this career-focused session, I share practical lessons for students and technology professionals interested in building a multidisciplinary career across technology and governance.

Topics can include:

• Moving from technical roles into governance
• Developing multidisciplinary expertise
• Selecting relevant professional certifications
• Building business and communication skills
• Learning through project experience
• Developing professional visibility
• Identifying a long-term specialisation

Audience outcome: Participants will gain a practical perspective on building a career across technology, risk, security and governance.