CDAO Singapore schedule

During this 5-minute networking session, the aim of the game is to go and meet three people you don't already know. Have fun!

• How leaders can drive organisational alignment to treat data as a strategic asset, not an afterthought
• Building trusted, accurate, and well-governed datasets that form the foundation for advanced analytics and AI
• Preparing infrastructure, talent, and processes to leverage emerging AI capabilities at scale

• Ensuring rapid AI adoption does not compromise privacy, fairness, or societal trust
• Practical governance models to maintain transparency, compliance, and explainability at scale
• Making ethical data use a shared value across leadership, teams, and technology partners

• Navigating evolving regional and global data regulations to stay ahead of compliance requirements
• Managing the complexities of cross-border data flows while safeguarding privacy and security
• Addressing industry-specific governance challenges with adaptable, future-ready frameworks

Panellists

Chen Huaxing Head, Group Wholesale Data Analytics UOB

Amaresh Mohan Chief Risk Officer Flutterwave

Rahul Patil ED, Head of Data Governance Office Sumitomo Mitsui Banking Corporation

• How agentic AI can automate entire business processes end-to-end, beyond isolated use cases
• Helping business leaders understand what AI can (and can’t) do to ensure relevant, high-impact applications
• Balancing rapid AI innovation with governance, ethics, and measurable business value

Moderator

Tarun Samtani Advisory Board Member IAPP  

Panellists

Tahir Zafar Global Head of Data & AI Strategy Nomura

Ankita Gupta Data, Analytics and AI Leader Standard Chartered

Natz Que CIO & CDO Kenvue

Yitong Chen VP Data Scientist & Analytics Validus

• Preparing teams to adapt and excel in fast-changing, high-scale environments
• Fostering a culture that embraces innovation, agility, and continuous learning
• Aligning people strategies with organisational growth and transformation goals

Speakers

Cher Jing Ting Head of Data Science SP Group

Anurag Chauhan Head of Data & AI Summit Global

Shobana Ravisankar Director, Data & Analytics PSA International

• Creating clean, accessible, and contextual data sets to power AI initiatives
• Ensuring data quality, governance, and interoperability across the organisation
• Translating data readiness into measurable business outcomes and strategic advantage

• Embedding governance at every stage of the AI lifecycle to ensure trust and compliance
• Defining clear policies, accountability, and ethical guardrails for AI initiatives
• Aligning AI governance with business objectives to drive responsible and measurable impact

• Implementing proactive strategies to safeguard data in a hyper-connected environment
• Establishing robust incident response plans for swift and effective mitigation

• Aligning privacy and protection measures with regulatory requirements and business objectives

• Translating organisational values into practical, verifiable AI safeguards
• Implementing frameworks that ensure fairness, accountability, and transparency
• Making ethical AI a measurable and actionable part of operations

• Demonstrating how strong governance drives not just compliance but strategic advantage
• Quantifying the impact of policies, controls, and oversight on business outcomes
• Linking governance practices to measurable value and competitive differentiation

• Showcasing how robust data foundations speed up AI adoption and innovation
• Highlighting case studies where data readiness drove measurable business outcomes
• Translating strong data practices into faster, more confident decision-making

This session explores how Gen AI case studies—across financial services, corporates, and beyond—are transforming decision-making, risk management, and competitive intelligence. Learn how to supercharge your AI models and turn information into impact.

• Enabling experimentation and rapid insights while maintaining compliance
• Implementing frameworks that balance creativity, privacy, and regulatory requirements
• Translating responsible data practices into sustainable business advantage

• Enabling large-scale analytics and AI experimentation without compromising oversight
• Balancing agility, innovation, and risk through structured frameworks
• Translating experimental insights into actionable, business-aligned outcomes 

• Exploring how leaders can foster creativity while maintaining control and oversight
• Sharing strategies to align innovation with governance and risk frameworks
• Highlighting real-world examples of balancing agility with compliance

Panellists

Cher Jing Ting Head of Data Science SP Group

Sankara Prasad Kondareddy Head of AI & Data Science Amplify Health

• Re-architecting legacy systems to support cloud, hybrid, and next-gen workloads
• Balancing performance, cost, and security while modernising data foundations
• Enabling future-ready platforms that accelerate AI adoption and business transformation

Speakers

Wouter van Groenestijn Data & Analytics Lead, APAC Cargill

Dinesh Ramchandani Director, Data & Analytics Unilever

Presentation of She Loves Data’s latest report on women’s participation in technology sector.

Presentation of She Loves Data’s latest report on women’s participation in technology sector.

•  Designing scalable, flexible data platforms that evolve with business and AI demand

• Implementing architecture principles that support long-term agility and performance
• Translating platform scalability into measurable business and innovation outcomes

• Turning technology and data spend into quantifiable value for the organisation
• Implementing strategies to optimise efficiency, impact, and business alignment
• Measuring and communicating the returns of data investments to key stakeholders

• Assigning accountability for delivering business outcomes from data investments
• Bridging the gap between data leadership and financial leadership
• Should value realisation sit with business units, not central teams?

Moderator

Ban Horng Tan Head of Data Platform Solutions OCBC Bank

Panellists

Soumyajit Sarcar Head of Data & Analytics Product Development, Chief Data Office Nomura

Manish Kumar Head of Data Manulife

Bharath K. Sr. Director of Data & Analytics Delivery Hero

• Identifying how poor data quality drives hidden costs across operations, compliance, and customer experience
• Demonstrating the ROI of data readiness through reduced errors, faster decision-making, and stronger AI outcomes
• Building executive buy-in by linking data quality investments directly to business growth and risk reduction

Moderator

Shobana Ravisankar Director, Data & Analytics PSA International

Panellists

Monica Srinivasan ED, Data Conduct - Data Quality Standard Chartered

Soumyajit Sarcar Head of Data & Analytics Product Development, Chief Data Office Nomura

Sankara Prasad Kondareddy Head of AI & Data Science Amplify Health

• Tackling data consistency and governance challenges across multi-cloud, hybrid, and edge environments
• Ensuring accessibility and performance without compromising security or compliance
• Applying best practices to integrate, monitor, and optimise data flows across distributed architectures 

With AI accelerating rapidly, analytics remains the backbone of trusted decision-making. This session unpacks how teams can safeguard data accuracy, generate deeper insights, and evolve their capabilities to make high-quality data accessible for AI-driven use cases.

• Understanding the risks and inefficiencies created by fragmented and siloed data environments
• Exploring strategies and technologies to unify, integrate, and govern data across business units and systems
• Turning fragmented data into a strategic asset that drives accuracy, accessibility, and actionable insights

• Exploring operational and financial challenges of scaling data platforms
• Sharing practical approaches to optimise efficiency, reduce waste, and manage risk
• Highlighting lessons learned from organisations navigating rapid growth

Speakers

Hou Kiat Chao Deputy Group Head, Digital & AI Office SBS Transit Rail

Seong Per Lee Head of Data & AI StraitX

Leaders ask a business question in plain English and receive a trusted chart, brief explanation, and next best action, without writing SQL. This session shares a governed, business-friendly approach that improves decision velocity while keeping data safe and costs in check.

• Exploring the concept of monetising data and analytics directly
• Lessons from organisations that generate revenue from their data
• Is this a future every enterprise can realistically pursue?

• Turning organisational values into concrete, ethical data management practices that build trust
• Embedding transparency, fairness, and accountability into every stage of data governance
• Ensuring responsible data practices drive both credibility and long-term impact

• Scaling reusable, modular data assets to accelerate business initiatives
• Driving agility and faster insights through well-structured data products
• Aligning data strategies with organisational goals to unlock measurable innovation

• Balancing pressure for quick ROI with building sustainable capabilities
• Risk of chasing shiny objects vs. investing in long-term foundations
• What trade-offs are data leaders making today—and what should they change?

Presentation of She Loves Data’s latest report on women’s participation in technology sector.