Citizens interact with government across web, mobile, phone, and in-person touchpoints, but fragmented systems create frustration and drop-offs. This session will show you how to deliver seamless, omni-channel journeys with consistent hand-offs so your users can complete tasks on their terms without repeating information.

• Transform disconnected touchpoints into unified journeys by mapping end-to-end citizen experiences and identifying friction points across channels.
• Advance mobile-first design with 24/7 digital-by-default transactions while maintaining assisted pathways for vulnerable groups.
• Reduce abandonment rates by enabling shared profiles and consent-based data reuse that eliminates redundant forms and verification steps.
• Optimize hand-offs between channels using open APIs and interoperable identity standards that preserve context and history.
• Improve outcomes with real-time performance dashboards that track completion rates, time saved, and satisfaction across every journey stage.

This session aims to ground the audiences understanding of AI in the Alberta context - understanding where Albertans, and the GOA are choosing to engage and leverage in this "emerging" technology. Everyone is talking about AI models, computing power, and infrastructure — but the provinces and nations that will actually win the AI era are the ones applying it to the industries they already own. Alberta has world-class strength in energy, agri-tech, aerospace and defence, health, and manufacturing. The question is not whether to engage with AI. It’s whether Alberta will direct that engagement toward applied outcomes in its core sectors — or watch others do it first.

• Understand what AI actually does at a provincial scale
• Separate the AI myths as organizations redesign themselves around higher-value work
• Learn the seven pillars of an applied AI ecosystem - data, domain expertise, talent, research, infrastructure, access to capital, and access to market, and understand why any ecosystem that is missing one of these will stall, regardless of how strong the others are

As organizations move beyond the hype of generative AI, the practical goal is clear: building a digital partner that meaningfully lightens the load and improves decision quality.

This session dives into an AI‑Empowered Chief of Staff (CoS) - a systems‑thinking partner that learns how you work, connects the dots across priorities, and helps surface blind spots. The decision still rests with us, but an AI‑CoS can provide informed options, recommendations, and execution support. What was once a capability reserved for senior leaders can now be made accessible across the workforce with the right design, guardrails, and adoption approach.

Governments have widely adopted design thinking to improve services and better understand citizen needs. But the landscape is shifting. AI and emerging agentic technologies can now generate ideas, prototypes and outputs at speed. As these tools evolve, the role of service design teams must also evolve. The real advantage now lies in how teams frame problems, ask better questions and guide technology toward meaningful public service outcomes.This session will explore how government and industry leaders are advancing design thinking practices to deliver stronger citizen outcomes. This session will help you apply new approaches on how you can strengthen your team’s capability, frame better problems and transform how your organisation delivers human-centred services.

• Advance design thinking practices beyond traditional tools and workshops
• Improve how teams define complex service problems and citizen needs
• Transform how teams work alongside AI and emerging technologies
• Apply practical methods to frame better questions and guide better outcomes
• Learn applied lessons from government and industry service design leaders Normative

Governments need trusted data to improve mental health and addiction outcomes at scale. This session will show how you can apply new approaches on how you can build a secure, privacy-first data environment that enables cross-ministry insights and supports better program evaluation.

• Achieve secure data integration across ministries using cloud platforms
• Strengthen privacy with tokenization and unique identifier design
• Improve trust through early engagement with privacy regulators
• Optimize data governance to enable scalable analytics and evaluation
• Prepare for future AI adoption to enhance population health insights

AI adoption depends on people who understand the technology, can apply it ethically, and know when to rely on human judgment. This panel will showcase how Alberta's AI Academy is upskilling the Alberta Public Service through masterclasses and hands-on practice so you can build AI capability at scale without waiting for formal training programs.

- Explore Alberta's AI Academy model, which uses leadership-led masterclasses featuring Deputy Ministers and domain experts to build literacy in prompt engineering, AI ethics, and automation across the public service.

- Advance practical skills through 30-day practice moves such as piloting one AI tool, running a bias audit, or co-designing a use case with frontline staff to build confidence and capability.

- Reduce resistance by creating accessible guidance, role-specific use cases, and peer learning communities that make AI adoption less intimidating for diverse job functions.

- Optimize ethical readiness by embedding responsible AI principles, privacy impact assessments, and redress design into training and delivery practice from day one.

- Improve adoption by measuring skill development, tool usage, and productivity outcomes to demonstrate the Academy's impact and refine curriculum based on real needs.

The Ministry is blending program design, policy, and digital delivery from day one. The initiative and its supporting technology is being stood up in parallel, pushing the boundaries of cross-government collaboration, agile decision-making, and privacy-first service design.

In this session, you’ll discover how the team is modernizing systems to make human-centered delivery a reality — and what that means for the future of public sector innovation.

• Learn how to co-design programs and digital services simultaneously to accelerate delivery and alignment.
• See strategies for embedding privacy, security, and legal compliance within innovation-driven projects.
• Gain insights into managing complex governance structures across ministries and commissioners without losing agility.
• Explore ways to build trust and responsiveness through user-centered digital systems.
• Take away a model for digital transformation that balances compassion, compliance, and modernization.

AI is only as effective as the information it can access, yet in most large organizations, that information remains locked in disconnected silos, constrained by legacy architecture and outdated policy. For Alberta, the path to a high-functioning, AI-enabled government doesn't start with a more powerful model; it starts with a more fluid data ecosystem. Building Data-Enabled Pathways means moving away from "data as an asset to be stored" toward "data as a utility to be consumed." This keynote unpacks the architectural and strategic shifts required to turn fragmented provincial data into the fuel for meaningful, automated, and predictive public service.

• Learn how to transition from static data repositories to interoperable "data highways" that allow AI models to access high-quality, real-time information across ministry lines.
• Explore how to embed privacy, security, and indigenous data sovereignty into the technical architecture itself, ensuring trust is a feature of the system rather than an afterthought.
• Shift the focus from "buying AI" to "cleaning and structuring data," understanding why 80% of AI success is determined by the quality of the underlying data-enabled pathways.
• Identify how data pathways must be designed to empower public servants with better insights, rather than obscuring the decision-making process behind a "black box."
• Understand the specific governance and technical enablers—from API-first strategies to cloud integration—that allow a province to move from isolated AI experiments to a unified, data-driven ecosystem.

Engagement between Ministry partners and Technology and Innovation has historically been a manual journey of forms, emails, and opaque timelines. With the launch of 2 new platforms, that dynamic is fundamentally changing. This fireside chat introduces the new, unified intake tool and demonstrates how it feeds directly into the ecosystem. By standardizing how projects are captured and tracked, T.I. is providing partners with real-time visibility into service delivery, moving from a "black box" model to a transparent, data-driven partnership.

• Get a first look at the streamlined intake tool designed to simplify how Ministry partners initiate projects, ensuring all necessary data is captured correctly the first time.
• Understand the role of the program in standardizing T.I.’s internal processes to ensure consistent service quality across every Ministry engagement.
• See how the data from your initial requests flows, creating a single source of truth for resource allocation, project health, and delivery timelines.
• Explore the new partner dashboards that allow Ministries to track T.I. services in real-time, providing the transparency needed for better departmental planning and reporting.
• Learn how this integrated data ecosystem allows T.I. to identify bottlenecks and optimize service delivery based on actual Ministry needs and performance metrics.

Public sector transformation efforts often stall when policy intent, operating models, and delivery realities drift apart—creating “modernization” programs that can’t be implemented, funded, or governed effectively.

This session will show you how to connect policy reform to service modernization work so you can design feasible reforms, prioritize the right delivery moves, and prove outcomes in real services.

• Assess where policy objectives, legislative constraints, and service delivery realities currently misalign—and what that misalignment is costing your users and teams.
• Translate policy intent into a delivery-ready modernization roadmap that links rules, funding, processes, data, and platforms to measurable outcomes.
• Design governance and decision rights that connect policy owners and delivery teams so modernization can move quickly without breaking compliance or accountability.
• Reduce implementation risk by embedding policy considerations early (privacy, inclusion, procurement, interoperability) rather than retrofitting them after build.
• Transform how you define “modernization” by using service journeys and operational metrics to validate which policy changes will actually shift outcomes.

Expectations for accountable data use and joined-up outcomes are rising, but many teams are still unclear on what “data sovereignty” means in practice and how to align it with existing privacy and service delivery obligations.

This session will clarify actionable models for First Nations-led data governance so you can design data sharing, custodianship, and infrastructure decisions that respect community rights while enabling better outcomes for your programs.

• Assess where your current data governance and privacy practices align or clash with First Nations sovereignty expectations.
• Clarify the difference between sovereignty and custodianship so your team can support use of data on community terms.
• Explore practical options for data hosting and stewardship, including what “in community”, “in province”, and “in Canada” can mean in real delivery contexts.
• Identify repeatable collaboration patterns between First Nations, provinces, and partners to move from intent to implementation without losing trust.
• Prioritize next steps you can take in the next 30 days to start building shared standards, capacity, and outcomes measurement.

The most costly decisions in complex government projects are rarely the technical ones — they are the governance conversations that should have happened in month one and didn’t happen until month eighteen. Getting ahead of those conversations requires a planning discipline that most teams skip: mapping the decisions that will be required, who needs to be in the room for each of them, and whether the capacity exists to act when the moment arrives. This session will show how to front-load your planning on complex projects so you can protect delivery timelines, reduce decision bottlenecks, and build the team capability needed to move with confidence.

• Identify the decisions that will make or break your project before the pressure is on
• Design your governance structure around real decision-making rather than reporting rhythms
• Build team capacity early and deliberately by identifying the skills, knowledge, and relationships your project will demand at each stage
• Map the stakeholder landscape before it maps you
• Distinguish between decisions that need consensus and decisions that need a decision-maker
• Leave with a practical planning framework you can apply to your next complex initiative

AI can transform how citizens interact with government, but poorly designed automation can frustrate users and damage trust. This panel will showcase real examples of AI in citizen-facing services and the safeguards that make them work so you can apply responsible innovation patterns in your own agency.

- Explore AI use cases such as intelligent chatbots, form pre-fill, document verification, and eligibility screening that reduce friction without removing human support.

- Advance trust-by-design by publishing model cards, explainability summaries, and clear redress paths for every AI-powered touchpoint.

- Reduce bias by testing AI systems with diverse user groups and running continuous audits for unintended impacts across demographics.

- Improve outcomes by pairing AI automation with human escalation paths that keep people in control of high-stakes decisions.

Technical debt is often viewed as a "tomorrow problem," but in the context of AI integration, it is an immediate barrier to entry. Legacy systems, unorganized data sets, and fragmented architectures act as a tax on innovation, slowing down the deployment of AI tools and increasing the cost of every new integration. Mitigating this debt isn't just about cleaning up old code; it’s about ensuring the provincial foundation is stable enough to support the weight of generative AI and automated systems. This session explores the practical strategies for identifying "high-interest" debt and modernizing infrastructure to create a sustainable environment for future technology.

• Understand why existing technical debt compounds when AI is introduced, and how to identify which legacy roadblocks will stall your integration efforts first.
• Learn a framework for triaging technical debt, focusing on the data silos and architectural bottlenecks that offer the highest ROI when modernized.
• Explore how to move from "patchwork" fixes to modular, scalable architecture that allows for the rapid swapping of AI models and tools as the technology evolves.
• Discuss the leadership challenge of maintaining service delivery while simultaneously decommissioning outdated systems to make room for modern, AI-enabled workflows.
• Define the governance and coding standards required today to ensure the AI solutions we build now don't become the unmanageable technical debt of 2030.

Pilot results are easy to celebrate. Sustained productivity gains are harder to earn — and harder still to spread across a team. This panel brings together practitioners who have moved past the proof-of-concept stage and are seeing measurable, real-world returns from integrating AI tools into their day-to-day work. This is not a conversation about potential — it is a conversation about what is already working inside government, and what it actually took to make it stick.

• Learn how to identify and eliminate the low-value work that quietly drains capacity
• Understand what GitHub Copilot and similar tools have changed for TI teams
• Get honest about the adoption curve: the panelists will share what they expected versus what they found
• The panel will address the team culture, management support, and skill-building that kept pilots progressing
• Leave with a framework for identifying where AI tools will produce real returns in your own team