Brian Jones

Poor upstream quality sabotages AI efforts, compliance, and customer experience; reactive fixes simply inflate cost and time resources. Equally, bad quality downstream flow hinders data team efforts by forcing endless cleaning loops, ad-hoc pipeline patches, and manual fixes every time a report or model misfires. Before organisations can even explore safe and efficient use of AI, data architecture and quality need to get in check. Proactive, contract-level standards are essential, and only CDOs that get their data in line will unlock true value. 

•  Learn how to embed uniform data-quality service level agreements into every vendor and internal business unit contract.
• Use critical-data-element catalogues to assign clear ownership and accountability.
• Discover how to automate quality tests, replace manual sampling, and streamline quality. 

Sampling-based checks still miss opaque anomalies while analysts reconcile spreadsheets to appease regulators. As data volumes increase and breach exposure intensifies, CDOs are being pushed to swap periodic evidencing for always-on, AI-driven assurance. Continuous monitoring promises earlier breach detection, leaner control and immutable audit trails - provided models are trained on quality data and wrapped in transparent governance. With DORA, the EU AI Act, BCBS 239, GDPR, SS1/24 and other strict rules in effect, navigating innovation without setting off compliance tripwires has never been harder. The CDOs that will navigate this with emerging models are the ones that will become compliance champions.

• Examine how to benchmark your anomaly-detection models on control logs to flag compliance breaches proactively.
• Explore how the shift from periodic sampling to real-time attestation is the way forward.
• Learn how to ensure alerts are addressed in real time.

Generic Q&As never kill a live blocker. Submit one thorny issue pre-arrival – either through the email that will be sent to you prior to the conference, or during our question collection during the pre-event pub quiz. In five-minute rotations, peers dissect your problem, share fixes and volunteer follow-up contacts. You leave with an action plan and the contacts to get you through it

Open Banking APIs and data marketplaces promise new revenue streams which boards are more than keen to explore – but few have managed to monetise data assets to their full extent just yet. Poor data quality, uncertainty over which data can be repackaged into profitable products, privacy concerns, and fragmented data architecture are common inhibitors. Adding to these blockers, Consumer Duty and GDPR slap fines on any hint of misuse, further paralyzing CDOs who would rather play it safe. Pilot revenues are often menial as legal and risk teams veto bold moves. CDOs must now prove a model that grows profit share without triggering customer backlash or regulatory scrutiny.

• Explore commercial frameworks that share upside with partners, protect from liability, and align with your consumer duty and regulatory commitments.
• Learn how to develop the infrastructure for secure data sharing, advanced analytics, and product development and capitalize on underutilized data assets.
• Create convincing narratives that persuade customers to opt in rather than out.

Legacy cores often underpin your most critical data stores, but cobbling together modern analytics on a fractured, unsupported stack kills velocity and trust. CDOs need a clear framework to decide what to retire, test safely and reinvest savings into modern data products.

• Learn to rank applications by their impact on data quality, operational risk and team expertise to decide your sunset roadmap.

• See how peers run parallel tests to validate decommissions without disrupting live reporting.

• Find out how to channel freed-up budget into high-impact analytics and AI initiatives.

A cyber espionage scandal triggers a data sovereignty standoff. Washington, Brussels and Beijing each rush through emergency measures to safeguard citizen data and critical AI. Overnight, companies see cross border data flows pipes taxed, throttled and scrutinised.

Imagine this:

• U.S. & EU impose a $0.10 per GB “Data Integrity Levy” on all outbound traffic; traffic must transit new government inspection gateways, adding ≥ 200 ms latency.

• China & India retaliate with a 12 % “Digital Export Duty,” plus in country processing rules for any personal or transaction data.

• The Basel IV “Sovereign Data Addendum” now demands proof that you can run core workloads locally within 60 days or face capital surcharges.

• Rules take effect in 30 calendar days; non compliance fines reach 4% of global turnover.

Split into three teams - your scenarios:

• Blue Team: Your CEO is already under investigation for previous data privacy breaches.

• Green Team: A marquee GenAI wealth management launch is scheduled across all regions in 90 days.

• Yellow Team: Your CFO orders a 30 % cut to group wide storage costs to offset new tariffs.

Each team has to:

1. Identify the first systems to break when tariffs and latency hit.

2. Draft one board ready action ensuring legal and technical readiness within the 60 day window.

3. Vote on the most urgent cross team fix.

Each table’s nominated leader shares their findings with the room, so every CDO walks out with a single, concrete next step, before the new levies land.