CDAO Canada schedule

For the keynote, step into the shoes of Scott Hallworth as he shares HP's transformative "way of working" journey by integrating AI and what he’s learned throughout his career in multiple industries. Scott will share how HP is embedding AI into its internal operations and end-to-end processes. Join him to discover how HP’s multi-tiered approach unlocks unparalleled digital capabilities, pushing boundaries and setting new standards in an AI-powered transformation.

• Leveraging AI for real-time monitoring and decision-making
• How does AI improve the efficiency and accuracy of predictive analytics?
• How do AI-powered tools automate data-related tasks, and what impact does this have on business processes?

Moderated by:

Shahzad Salim, Head of Analytics Platform with AI Solutions, GOOGLE CLOUD

Panelists:

Kartik Pant, VP and Head of Data and AI, Manufacturing & Supply, SANOFI

Alan Khalil, Director, AI & Data Product, BELL

Murat Beshtoev, Head of Analytics & Innovation, BAYER

Or Zabludowski, Chief Executive Officer & Founder, FLEXOR.AI

While nearly all the public data is represented in LLMs today, we are seeing only ~1% of enterprise data represented. Expectations have skyrocketed but leaders are constantly balancing scaling generative AI and having quality data to support each use case from existing processes and a tech stack not designed for these workloads. Furthermore, the success of generative AI hinges on the ability to harness both structured and unstructured data. Learn how leading organizations today are implementing an open and trusted data foundation to access siloed data across hybrid cloud, cost-optimize growing data workloads, and secure, govern, prepare and deliver high-quality, governed data for AI.

Data is at the heart of decision-making, yet many firms struggle to fully realize GenAI's potential due to the ever-changing nature of their information. While traditional Retrieval Augmented Generation (RAG) grounds AI in enterprise data, it often falls short with rapidly evolving datasets. Enter Query RAG—a revolutionary approach that equips large language models (LLMs) with real-time, dynamic data to deliver accurate, context-rich insights. Discover how Query RAG drives precision, agility, and actionable intelligence to keep your organization competitive in an AI-driven world.

 Tailored for leaders and innovators, this session will explore how to:

• Overcome challenges with integrating AI and real-time, evolving your data
• Apply Query RAG to structured data for accurate, actionable AI insights
• Ensure data security and compliance in AI-driven solutions

Empower your organization to lead with innovation and efficiency. Transform your data strategy to unlock new competitive advantages and drive success in the evolving landscape.

• Designing scalable data & AI architecture to support growing data needs and AI capabilities, ensuring flexibility for future growth and seamless scalability
• Ensuring seamless integration and interoperability across diverse data sources, facilitating smooth data flow, and driving actionable insights
• Setting clear, achievable goals for data and AI strategy that are aligned with business objectives to deliver tangible, measurable results and impact

• Strategies to generate revenue from data, such as through data products, services, insights, or a modern data- and analytics platform
• How a modern data infrastructure and technologies supports the business strategy
• Strategies and experience with fostering a culture where data is valued and used effectively by all employees

• Enabling transformation and decision making with trusted data
• Ensuring data quality, consistency, and integration
• Improving the quality and speed of decision-making at scale by automating administrative tasks

Moderated by:

Stella Cabrera, Member Services – Canada, EDM COUNCIL

Panelists:

Ankei Yau, Senior Manager, Cargo AI and Transformation, AIR CANADA

Eugene Y. Wen, MD. DrPH., Vice President & Global Chief Data Scientist, MANULIFE

Palash Thakur, VP, Head of Data Analytics & Fraud (CDO), INTERAC CORP. 

Rahat Yasir, Head of Data Quality and Analytics, INTERNATIONAL AIR TRANSPORT ASSOCIATION

• Developing a workforce with strong analytical skills
• Investing in data literacy training for employees at all levels
• Reinforcing the importance of innovation

• Roles and responsibilities within data governance structure
• Developing policies for data quality, security, and privacy
• Designing processes for data collection, storage, and management
• Best practices for data integration and interoperability

• Fostering a culture of collaboration and open data sharing
• Reduction in barriers to make data more accessible
• Implementing data integration practices, ensuring that data from various sources is consolidated into a unified view
  

Moderated by:

Paul Childerhose, Regional Advocate, EDM COUNCIL

Panelists:

Alexander Chan, Director of Analytics, RBCX

Mo Bayan, Director, Business Intelligence and Data Enablement, SUN LIFE

Jasper Cannon, Strategy Consultant, CANNON STRATEGY CONSULTING

• Key principles of product management applied to analytics
• Understanding user needs and pain points
• Designing intuitive and actionable analytics solutions

• Empowering decision-makers with AI-driven insights for more informed and timely decisions
• Enhancing marketing campaigns with AI-powered tools for better targeting and engagement
• Leveraging AI to deliver personalized recommendations and experiences based on customer data

• Implementing AI models to uncover hidden patterns
• Creating intuitive and interactive dashboards
• Using visualization tools to communicate insights effectively

• Regulatory challenges and opportunities with LLMs in finance and government
• Best practices for aligning LLM deployment with compliance and risk management
• Strategies for driving efficiency without compromising security or regulatory standards

• What are the key benefits of integrating AI into your data strategy?
• How can AI enhance data-driven decision-making processes?
• How can you ensure your AI models are accurate and reliable?

• How can data democratization drive innovation and efficiency?
• How can you design effective training programs for employees to use data and analytics tools?
• How can you maintain data quality while democratizing access?

Moderated by:

Papa Nguer, Associate Director, Technical Sales, INFORMATICA

• How can transparency in performance data build trust within the team?
• What are the best practices for sharing performance data openly?
• What role does data play in driving strategic improvements

Contributors:

Rohin Bansal, Director, Data Governance & Enablement, TELUS DATA & TRUST OFFICE

AI adoption varies widely across organizations—some are just starting, while others are scaling enterprise-wide. But what defines true AI maturity, and how can companies accelerate their journey?

This executive roundtable brings together VP and C-level data and analytics leaders for an open discussion on AI strategies, challenges, and best practices. Key topics include:

• Defining AI Maturity: How do organizations measure progress?
• Operationalizing AI: What drives successful AI deployments?
• The Future of AI: What trends will shape AI adoption?

Join us to exchange insights, benchmark against peers, and explore AI’s evolving role in the enterprise. 

Moderated by:

Jason Bishop, AI North America Lead, QLIK

• How can AI enhance the efficiency and effectiveness of the bids and proposals process?
• How can organizations ensure their data is clean, relevant, and ready for AI applications?
• How can organizations track the ROI of their AI investments in this area?

• Gaining access to valuable insights to give your business a competitive advantage
• Understanding customer needs to develop unique data sets
• Measuring the financial value of your data sets

Moderated by:

Stella Cabrera, Member Services – Canada, EDM COUNCIL

Panelists:

Nikita Medvedev, Director of Advanced Analytics, COCA-COLA CANADA BOTTLING

Olga Tsubiks, Director, Strategic Analytics and Data Science, RBC

Jasper Cannon, Strategy Consultant, CANNON STRATEGY CONSULTING

• How can AI be leveraged to transform customer experiences and operations?
• In what ways can AI drive innovation in products and services?
• What are the data value drivers to make AI opportunities work well?

• Aligning data initiatives with business goals and driving innovation through AI adoption
• Understanding their roles and responsibilities in the context of AI
• Addressing security and privacy concerns

• Ensuring that your organization has reliable data storage, processing, and retrieval systems
• Enhancing data quality and accuracy
• Fostering data literacy through training
• Democratizing data and sharing insights across the organization

• Establish the primary goals of your data governance initiative to align the team’s efforts
• Implement measures to comply with data privacy and security regulations
• Create a structured framework that outlines policies, procedures, and standards for data management

• Developing specific metrics to measure the success and impact of your responsible AI efforts
• Ensuring you have the infrastructure and personnel to support the program long-term
• Create a detailed plan outlining the steps and milestones for implementing responsible AI

Moderated by:

Stella Cabrera, Member Services – Canada, EDM COUNCIL

Panelists:

Aneta Osmola, Data and AI Risk Director, Global Risk Management, SCOTIABANK

Huzaifa Noman, Global Head of Data & AI, COLLIERS

• What are the main challenges you face when collaborating with technical, data, and business teams?
• How do you align business goals with technical and data capabilities?
• How do you measure the success of collaborative efforts?

Moderated by:

Stella Cabrera, Member Services – Canada, EDM COUNCIL

Panelists:

Roma Kojima, Senior Director, Enterprise Audience Data & AI, CBC/RADIO-CANADA

Oleksiy Okrushko, Director, Head of Data & Analytics, Global Transaction Banking, TD SECURITIES

Jasper Cannon, Strategy Consultant, CANNON STRATEGY CONSULTING

• What are the main challenges organizations face when trying to adopt a data-driven culture?
• What strategies can be employed to develop a workforce that is proficient in data analytics?
• How can organizations ensure that their data analytics efforts align with their strategic goals?

• How can AI perpetuate biases present in training data, and what are the implications for privacy?
• How can AI help ensure compliance with data protection regulations?
• What are the challenges in maintaining data security and privacy in AI-driven environments?

• Strategies for data leaders to drive positive impact through AI initiatives
• Enhancing data literacy across organizations to support AI-driven decision-making
• Exploring new AI technologies and their potential for positive impact