CDAO Canada Public Sector schedule

In the highly competitive age of digital transformation financial service organizations are facing accelerated urgency to improve their customer and employee experience while simultaneously reducing operating costs, and managing risk and compliance.

To meet these competing demands on their business, these organizations are racing to deploy deep learning to achieve a new competitive edge by optimizing their back office operations with intelligent document processing, personalizing their customer experience with cutting edge NLP models, and reducing fraud and risk using state-of-the-art deep learning.

AI is here and delivering new capabilities to help businesses solve large and complicated challenges. Join Bob Gaines to learn what that means for your business and how deep learning is helping organizations:

• Achieve higher compliance, faster and with lower costs • Dramatically improve Customer Experience • Reduce time to value from years to weeks

Sergio Rego is a customer engineer at SambaNova Systems where he helps clients deploy purpose-built, deep learning solutions in weeks rather than years. Sergio started his career in financial services, where he worked in strategy; active and index management; and product design and management. Sergio also served as a senior data scientist and team manager for a system integrator where he helped federal government agencies deploy ML and AI solutions.

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

As generative AI (GenAI) becomes one of the most disruptive technologies of our time, the public sector stands at a pivotal crossroads. This keynote explores not just the what and how of GenAI, but more importantly, the why — and the responsibilities that come with it. 

• How can GenAI reduce administrative burden, personalize citizen services, and streamline processes like grant applications, benefits, and tax queries? 

• How might ministries use GenAI to co-create policy with stakeholders or pressure-test decisions before implementation? 

• What does “authentic” engagement look like when responses are AI-augmented? 

• Where does helpful automation turn into harmful hallucination or bias reinforcement? 

• What happens when GenAI outputs are taken as fact — and who is accountable? 

This session will delve into the transformative power of real-time data in the public sector and explore its critical role in advancing government effectiveness and resilience. 

• How are real-time analytics transforming emergency response, environmental monitoring, and regulatory compliance? 

• What infrastructure upgrades are needed to operationalize real-time insights at scale in government? 

• What lessons can be learned from pilots or full-scale implementations across federal and provincial agencies? 

In an era where algorithms increasingly drive public services and policy, ensuring that these systems operate fairly, transparently, and inclusively is critical. 

• What operational frameworks are proving effective for managing algorithmic fairness and privacy? 

• How are Canadian agencies applying Bill C-27 and GDPR-inspired practices in real-world contexts? 

• Which tools can proactively detect and mitigate algorithmic bias? 

• How can data teams work with legal, accessibility, and DEI units to operationalize trust? 

Celio Oliveira, AI Executive Director – Government of Canada 

Nish Anjaria, Vice President Technology Innovation, Strategy & Enterprise Architecture - Canada Post 

David Dunwoody, CAF Advisor on AI – Department of National Defence 

Digital twin technology is revolutionizing how cities manage and optimize urban planning, infrastructure, and public services. By creating virtual replicas of physical environments, digital twins enable real-time monitoring and predictive analytics that can enhance everything from traffic management to disaster response. How can digital twins improve the efficiency and sustainability of urban infrastructure management? What challenges do cities face when implementing digital twin technology, especially in terms of funding and scalability? 

• How is geospatial and sensor data being used to inform climate adaptation and sustainable urban development? 

• What collaborations between municipal, provincial, and Indigenous leaders are moving the dial? 

• What are the tools for monitoring environmental impact in real-time? 

• What are the key features of a resilient public sector data infrastructure? 

• How can agencies ensure real-time data access during system disruptions or high-demand events? 

• What role does cloud, hybrid architecture, or decentralized storage play in data continuity? 
• How should governments approach scenario planning and testing for data infrastructure under stress? 

James Lindsay, Senior AI Architect and Engineer - Department of National Defence

The growing importance of data in government decision-making means that data literacy is a critical skill for civil servants. The goal is to build a data-driven culture that empowers public sector workers to make more informed, evidence-based decisions. We’ll explore models for effective training, the obstacles to embedding a data culture in legacy institutions, and how governments can evaluate the ROI of their data literacy programs to ensure they are meeting objectives and driving real impact. What are the most effective approaches for upskilling civil servants in data analytics and storytelling? What barriers exist when embedding a data-driven culture in legacy institutions, and how can they be overcome? How can public sector leaders measure the effectiveness of their data literacy programs? 

• How is data integration reshaping vaccine rollout, public health surveillance, and population health planning? 

• What data quality and interoperability challenges persist across healthcare jurisdictions? 

• What privacy measures are essential when handling health-related datasets? 

• How can governments quantify and communicate the value of their data assets? 

• What are the pros and cons of public-private data partnerships — and how can they be structured responsibly? 

• What role can anonymized or aggregated datasets play in supporting innovation and research? 

• How do data licensing, APIs, and open standards affect long-term data value creation? 

Aneesh Joshi, Director Technology Advisory - Infrastructure Ontario   

Ahmed Shalaby, Executive Director Enterprise Information Management - Service Canada   

More TBC 

What does it really take to lead data transformation from a vision to reality? This candid fireside chat features leaders who’ve moved beyond policy mandates to create lasting data-driven change.  

• How are data strategies being translated into measurable outcomes that matter to citizens? 

• What are the most unexpected challenges leaders have faced—and how did they overcome them? 

• How do they balance political expectations with operational realities and citizen demands? 

• What’s the next bold move in data-driven leadership? 

Moderator: Ben Dick, Senior Data Analytics Strategist - City of Ottawa 

David Collister, Manager, Data Governance - Fisheries and Oceans Canada 

Nish Anjaria, Vice President Technology Innovation, Strategy & Enterprise Architecture - Canada Post 

As data volumes and computing power grow, predictive analytics is emerging as a transformative force in designing policies that are not just reactive but forward-looking. From forecasting housing demand and social service needs to anticipating public health trends, predictive models are reshaping how institutions allocate resources and deliver value. 

• How can predictive modeling improve policy decisions in areas like social services, housing, and education? 

• What risks must be addressed to avoid overreliance on models in policy? 

• How can a government balance proactive services with reactive accountability? 

• How do we ensure transparency and explainability in predictive models used for public decision-making? 

• What cross-sector partnerships are proving most effective in advancing predictive analytics initiatives? 

• What challenges or opportunities led to the decision to build centralized service dashboards in your organization? 

• How can public sector teams foster cross-departmental collaboration when developing integrated dashboards? 

• In what ways can data partnerships be leveraged to enhance BI reporting across different service lines? 

• What are the most effective strategies for presenting complex data clearly and impactfully to senior leadership? 

• How do you establish governance structures and build trust in the accuracy and integrity of dashboard data? 

• What lessons have been learned through early iterations, and how have they informed improvements? 

• How can dashboard initiatives scale beyond initial use cases to support strategic goals across the organization? 

• How can inclusive design principles be baked into data visualizations and tools? 

• What metrics and KPIs help track equity outcomes in digital services? 

• How can analytics teams partner with accessibility and DEI leads for inclusive innovation? 

As AI continues to redefine the digital landscape, the path forward for public services requires more than adoption—it demands intentional design, ethical foresight, and strategic collaboration. This session explores how data and AI can be harnessed to build responsive, inclusive, and resilient systems that meet the evolving needs of society. 

💬 Format: Open-dialogue roundtable with moderator-led prompts and participant Q&A. 

• What does a future-ready public service look like in an AI-native world? 

• How can governments shape the ethical and technological standards that will guide society? 

• What role will cross-sector partnerships play in accelerating innovation while safeguarding equity? 

• How can governments future-proof data infrastructure for real-time responsiveness and adaptability? 

• What are the most promising areas for AI to solve systemic public challenges by 2030? 

Aneesh Joshi, Director Technology Advisory - Infrastructure Ontario   

James Lindsay, Senior AI Architect and Engineer - Department of National Defence 

Michael Mohammed, Manager, Policy & Legislation – Government of Canada 

As data becomes the cornerstone of decision-making and service delivery, Chief Data Officers and public sector leaders face mounting pressure to safeguard public trust, protect sensitive information, and ensure that innovation doesn’t outpace regulation. 

• How can leaders design data strategies that drive innovation while actively mitigating the risks of cyber threats and data breaches? 

• What practical steps can organizations take to build transparency and public trust in how data is collected, used, and safeguarded? 

• How can ethical AI and robust cybersecurity protocols be seamlessly integrated into broader data governance models? 

• Which ethical frameworks are most effective for managing sensitive data, particularly in the face of privacy challenges and potential algorithmic bias? 

• What role can government and public institutions play in setting the standard for responsible, inclusive, and forward-thinking use of AI and analytics? 

With global momentum building around algorithmic accountability and data ethics, public sector data teams are entering a new era—one where compliance isn’t just legal housekeeping, it’s foundational to public trust. 

• Key highlights of Canada’s DCIA: automated decision-making disclosures, the right to explanation, and algorithmic impact assessments. 

• How does this legislation compare to Quebec's Law 25 (e.g., mandatory privacy impact assessments, consent requirements, and role of the privacy officer)? 

• What can Canada learn from how the EU implemented and enforced GDPR, especially in the public sphere? 

• What practical resources are helping teams comply — AI impact assessment forms, consent logs, data minimization checklists, and documentation templates? 

• What roles are becoming critical? (e.g., privacy engineers, AI ethics leads, compliance officers embedded in data science teams) 

How can microdata reshape the way Canada delivers public services? 

• Join an open and candid AMA session with a public sector leader working at the intersection of community-level data, national policy, and ethical governance. This expert will explore how hyper-local insights—down to the neighborhood or community level—are shaping strategic decisions in housing, Indigenous services, and public health. 

• Drawing from real-world collaborations, regional data trusts, and integration efforts across jurisdictions, this session offers practical insight into building interoperable, privacy-conscious microdata ecosystems that serve both local and national goals. 

Key Focus Areas: 

Community-level data integration for federal impact, Intergovernmental data sharing and governance models, Privacy, data sovereignty, and Indigenous data frameworks, technical foundations for scalable microdata use, aligning funding and programs with on-the-ground realities. 

Even the most advanced data tools can fail if they don't reflect the diversity of those they serve. This session explores how governments are rethinking dashboards, interfaces, and data reporting through a human-centered design lens. 

We’ll look at how analytics can be made more accessible for multilingual audiences, people with disabilities, and digitally vulnerable populations—shifting toward inclusive data experiences, not just outcomes. 

Key Questions: 

• What does "inclusive analytics" look like in practice across different government services? 

• How can tools be designed to accommodate linguistic, cultural, and digital literacy barriers? 

• What co-design strategies are proving effective in building data tools with underserved populations? 

Blending behavioral economics with predictive analytics is opening new frontiers for government policy design. This session explores how public sector teams are testing nudges, simulations, and interventions based on real-time behavioral data. 

We'll unpack successful case studies from service uptake to climate behaviors—along with the ethical considerations of using behavioral data at scale. 

• How can governments design experiments using behavioral science and machine learning to drive better outcomes? 

• What kinds of "nudges" are being tested to increase uptake in public health, taxes, or education? 

• Where is the line between ethical influence and manipulation when using behavioral insights? 

David Collister, Manager, Data Governance - Fisheries and Oceans Canada 

As public sector organizations face growing complexity in health, environmental, and regulatory challenges, data is becoming the backbone of smarter, faster, and more ethical decision-making. This panel brings together leaders from across government science, policy, and data functions to explore how advanced methodologies are reshaping the future of risk assessment. 

Speakers will discuss real-world applications, the infrastructure needed to support innovation, and how collaboration between scientists, data professionals, and policymakers is unlocking a new era of public sector impact. 

Key Discussion Topics: 

• Real-world use cases of data in regulatory science and risk assessment 

• Infrastructure and governance for cross-disciplinary collaboration 

• Lessons learned in integrating advanced modeling and analytics 

• The role of public sector leadership in adopting data-driven innovation 

Moderator:  Dr. Yad Bhuller, Executive Advisor – Health Canada 

Panelists: 

Dr. Marc Avey, Director of Standards - Canadian Council on Animal Care 

Dr. Charu Chandrasekera, Founder & Executive Director - Canadian Centre for Alternatives to Animal Methods 

David K. Lee, Chief Regulatory Officer - Health Products and Food Branch 

Nadine Huggins, Senior Assistant Deputy Minister - Corporate Services Branch, Health Canada, and Public Health Agency of Canada 

Dr. Valerie H. Taylor, Department Chair, Psychiatry - University of Calgary, Departmental Science Advisor, Health Canada 

Dr. Ranjana Sharma, Chief Scientist - Natural Resources Canada, Government of Canada 

Adapting fast. Deciding wisely. Collaborating better. 

In today’s unpredictable world, data leaders in the public sector must be ready to respond to complex, fast-moving crises—from natural disasters and public health emergencies to cyberattacks and humanitarian shocks. But how do you lead with data when timelines are short, the stakes are high, and the information is incomplete? 

This closing roundtable brings together cross-sector experts who’ve been at the data frontlines during critical moments. We’ll explore the human, technical, and leadership dimensions of crisis-driven analytics—sharing candid lessons, practical frameworks, and collaborative models for navigating what’s next. 

💬 Format: Open-dialogue roundtable with moderator-led prompts and participant Q&A. 

Key Discussion Prompts: 

• How can data leaders embed agility into their teams and tools before a crisis hits? 

• What real-world examples highlight how analytics shaped decision-making in emergencies? 

• How do we balance speed with governance, ethics, and data accuracy in high-pressure scenarios? 

• What role does cross-government and cross-sector data sharing play during crisis response? 

• How can leaders debrief and build institutional learning after a major disruption? 

• What’s one innovation or lesson from the last crisis that should be institutionalized for the next? 

Aneesh Joshi, Director Technology Advisory - Infrastructure Ontario   

David Dunwoody, CAF Advisor on AI – Department of National Defence