Beat the rush and join us early for complimentary barista-made coffee and breakfast.

For many organisations, data governance still sounds like control, compliance, and bureaucracy. But in an AI-driven enterprise, governance is becoming the foundation that enables trusted data, scalable AI, and faster innovation.

This keynote explores why data governance needs a rebrand, from a cost centre to a strategic capability that helps organisations move faster with data while managing growing data and AI risk.

‍

• Discover why the current narrative around data governance is failing
• Learn how governance can enable faster AI and analytics adoption
• Explore how governance is becoming the framework for managing data and AI risk

‍

Threat volumes continue to rise, but most security teams are facing the same reality: limited resources and growing expectations. Leaders are being asked to detect threats faster, protect more sensitive data, and manage new AI-driven risks without expanding headcount or budgets. This panel brings together security and data leaders to share how they are strengthening resilience in practice, through smarter investment, targeted automation, and deeper collaboration across organisations.

‍

We’ll explore:

• Where threat intelligence sharing genuinely improves security outcomes and where it simply creates more noise
• What security teams are automating today to reduce workload without weakening oversight
• How organisations are collaborating across sectors to strengthen collective defence
• How leaders are building security cultures that enable teams to move faster under pressure

Governance, Risk, and Compliance functions face growing pressure to align with various standards and regulations. However, the diverse evidence expectations and review cycles can lead to fragmentation and heavy workloads. AI-driven approaches can now perform evidence analysis, extract relevant insights, validate control alignment, and detect gaps early, resulting in a more reliable, scalable, and high-performing GRC function that supports faster decision-making and stronger organisational resilience.

In this innovative session, attendees will be faced with a series of scenarios that they may face in their roles. Attendees will discuss the possible courses of action with their peers to consider the ramifications of each option before logging their own course of action.

‍

Results will be tallied and analysed by our session facilitator and results will impact the way the group moves through the activity.

‍

Will we collectively choose the right course of action?

‍

This session highlights how embedding privacy and security into organisational culture can drive customer trust and long-term business success beyond compliance.

‍

• Strategies for fostering a privacy-first mindset across all levels of an organisation.
• Integrating privacy by design in products and services to achieve regulatory and market differentiation.
• Empowering cross-functional teams to proactively identify and mitigate data protection risks.

Learn how organisations across sectors can integrate generative AI technologies while maintaining strong data protection and managing associated risks.

• Establishing governance frameworks and designated AI oversight roles to ensure responsible AI use.
• Implementing data classification and access controls to protect sensitive information during AI deployments.
• Collaborating with trusted AI vendors and conducting ongoing risk assessments to safeguard organisational data assets.

Select a topic of discussion and engage in an interactive roundtable discussion with a group of your like-minded peers.

Put your knowledge to the test in this fast-paced quiz covering real-world trivia, key concepts, and emerging trends. Compete for bragging rights - and a travel voucher - as the top scorer takes the crown.

‍

‍

As AI rapidly expands access to sensitive data, this session cuts through hidden exposure risks, closes governance gaps and unpacks what boards now expect regarding data minimisation and responsible AI use.

‍

• Minimising sensitive data in AI environments by reducing unnecessary collection, retention and reuse before data becomes a liability.
• Examine where traditional data protection frameworks fall short and what effective responsible AI policies look like in practice.
• Strengthening oversight, accountability and reporting to meet rising expectations around AI-driven data risk.

As AI adoption accelerates, workforce and operational data are increasingly repurposed for analytics and training models, blurring the line between what’s technically possible and what’s ethically acceptable. 

With growing scrutiny and regulations, leaders must balance innovation, compliance, and employee trust, and decide; Just because we can use the data, should we?

This interactive session puts these questions directly to the audience. Participants vote live on a series of real-world scenarios, explore the results together, and vote again as perspectives shift through the discussion.

• Can internal employee data be used to train AI models without explicit consent?
• What level of de-identification is “safe enough” for AI analytics?
• How transparent should organisations be about AI data use?
• Who should own decisions on AI data ethics and privacy?
• When innovation conflicts with privacy risk, what should win?

‍

Unwind with your peers for a couple of drinks on us!