Agenda - Day 2

Gain insight into today’s sessions so you can get the most out of your conference experience.

As organizations increasingly rely on data-driven strategies and AI-powered tools, the ability to effectively manage data assets has never been more critical. This presentation will explore what Transport Canada has been doing to deploy an enterprise approach to data and analytics. Walk away with tactics on how to:

• Build robust data asset management practices that can significantly enhance analytical insights and unlock the full potential of artificial intelligence.
• Avoid data silos and inconsistent metadata, and build organizational data governance through better data cataloging, lineage tracking, and quality controls.
• Align data management practices with business goals and AI strategies to drive innovation and operational efficiency.

Enable faster AI model development, improved accuracy, and greater scalability with well-managed data environments

Enhance client outcomes and efficiency by fostering a culture of data literacy. Empower employees and increase the effectiveness of data-driven initiatives. Source practical tips to:

• Assess current employee data literacy and identify training needs.
• Develop effective training programs to enhance data literacy across all levels of the organization.
• Promote a collaborative environment where employees feel comfortable engaging with data and AI technologies and contributing to project success.

Improve data literacy to unlock its full potential within your organization.

Take a deep dive down the innovation rabbit hole in one of our roundtable discussions. Share common challenges and best practices with your data peers on a topic of your choosing:

1. Generative AI in Government: Explore how public sector organizations are evolving from pilots to production with GenAI, while addressing risks related to transparency, bias, and accountability.
2. Data Ecosystems & Intergovernmental Collaboration: Discuss strategies for building data-sharing ecosystems across agencies and jurisdictions, including federated models and secure data exchange frameworks.
3. Indigenous Data Sovereignty: Learn how governments are partnering with Indigenous communities to support data governance, respect OCAP® principles, and enable ethical data practices that support self-determination.
4. AI-Powered Service Personalization: Examine how advanced analytics and machine learning are enabling more personalized, responsive public services — while prioritizing equity, accessibility, and privacy.
5. Real-Time Data for Resilience & Response: Explore how real-time data and geospatial intelligence are being leveraged to respond to emergencies, monitor environmental threats, and inform proactive policy decisions.
6. Privacy Engineering & Digital Trust: Delve into emerging techniques such as synthetic data, anonymization, and privacy-by-design to enable secure, ethical, and scalable data use across the public sector.

As AI continues to evolve, so must the teams responsible for building and governing it. Delivering ethical AI at scale requires more than just technical expertise, it demands diverse perspectives, clear accountability, and a culture of continuous reflection. Master the success factors to:

• Assemble cross-functional teams that combine data science, ethics, policy, and subject matter expertise.
• Develop clear systems for enabling
• Define roles and responsibilities to ensure transparency, fairness, and effective governance across AI initiatives.
• Embed ethical considerations into daily decisions through targeted training, thoughtful incentives, and leadership alignment.

Transform your team’s structure to meet growing expectations for responsible AI — and ensure your technology works for people, not just performance

In this interactive session, the team will showcase groundbreaking projects brought to life through live demonstrations—featuring real-time climate analytics, anomaly detection, and immersive scenario planning simulations.

Walk away with technical roadmaps to:

• Building AI/ML models to predict the impact of climate-related events on health care resource use.
• Expand analytical capabilities with non-traditional data such as images.
• Enhance stakeholder buy-in with interactive dashboards and animations using real and projected data.

Discover how advanced analytics is not just informing the future of healthcare—it’s shaping it.

Non-profit and not-for-profit have the same operational analytics needs as for-profit companies, including financial, HR, and marketing data. But they also need types of data that are far less common in for-profit environments, while operating with far less funding investment and staffing for data experts than most for-profit organizations. Leave with tactic to:

• Define success: Quantifying progress towards the organization’s core mission
• Optimize data governance: Meeting disparate and often contradictory information requirements from funding and regulatory bodies
• Data capture, consent and confidentiality: working in challenging settings, and with vulnerable clients where informed consent is critical

Strategies and real-world examples of how to provide the best analytical value possible given operational constraints.

Canada’s renewed commitment to meeting NATO’s defense spending target — £150 billion — marks a national shift toward a more industrialized, defense-oriented economy. But this isn’t just about tanks and troops. From healthcare to infrastructure, a large portion of military investment will directly shape civil society. Data and analytics will play a crucial role in ensuring military expansion also drives national benefit.

• Reframe defense investment as a civic opportunity, with real examples of contracts contributing to local benefit across all agencies
• Explore how Canada’s public sector can retain talent and prevent brain drain by aligning with national priorities

Modernize and integrate your agency into a more connected civil service through Canada’s larger nationalization and militarization efforts.

Data is essential infrastructure in a modern, world-class health system. Patients need their data to travel alongside them as they go through their care journeys. And, when combined together, data is the powerful driver required to manage and improve the health care system for the benefit of all. As Canada’s health data leader, CIHI is leading the changes needed to break down the many data silos that currently exist and safely unlock the power of our health data, including enabling AI. Learn about:

• The transformation underway of Canada’s health data ecosystem and the importance of health data stewardship
• How data stewardship is tackling the human, organizational and governance barriers to improve the access, sharing and use of health data.
• The importance of building public trust, ensuring the safe and ethical use of health data, advancing health equity and respecting Indigenous data governance and sovereignty.

As higher education institutions face increasing pressure to demonstrate impact and alignment with institutional priorities, the University of Toronto Communications team recognized a critical gap: the absence of consistent data practices. Move from anecdotal success stories to evidence-based decision making — beginning with a call to measure value, track performance, and unify data across channels. Enhance your strategy by:

• Breaking down silos and unify disparate data streams
• Aligning storytelling with institutional goals using data insights
• Building the case for new roles and resourcing in support of data maturity

Develop a value adding data strategy that supports storytelling, strategic alignment, and organizational visibility.

Review the key solutions and takeaways from the conference. Source a summary of action points to implement in your work.