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.

Legacy systems underpin critical services, but they are expensive to maintain and difficult to integrate with modern tools. This session will teach you how to migrate safely using staged, risk-managed pathways so your agency can modernize infrastructure while protecting continuity and trust.

- Advance your platform strategy by mapping dependencies, defining clear migration milestones, and shipping incremental value instead of big-bang replacements.

- Reduce downtime and risk by running parallel systems, automated testing, and rollback plans that protect service delivery during transitions.

- Optimize interoperability by adopting open standards and API-first architecture that let new and legacy systems exchange data seamlessly.

- Transform your workforce by upskilling teams on cloud-native tools, DevSecOps practices, and modern data platforms through hands-on delivery.

- Assess your legacy estate using a modernization maturity model and prioritize the highest-risk, highest-value systems for action in the next 90 days.

As organizations move beyond the hype of generative AI, the focus has shifted to a practical goal: building a digital assistant that actually lightens the load. This session moves past generic prompts to explore what it truly takes to make AI a genuinely useful executive partner, recognizing that "utility" looks different depending on your seat at the table. By examining the unique needs of different organizational functions, you will learn how to deploy smart guardrails and customize the same underlying tools to deliver specific, high-impact value across your agency.

• Define the core architecture required to transform standard AI tools into specialized, high-functioning executive assistants.
• Analyze how AI value scales across different roles, comparing how varied functions within an organization derive unique benefits from the same technology.
• Establish robust guardrails to ensure AI implementation remains secure, ethical, and aligned with organizational policy.
• Bridge the gap between raw data and actionable support by identifying which workflows are ripe for AI-driven optimization.
• Navigate the cultural shift necessary to integrate AI assistants into daily executive operations while maintaining trust and human oversight.

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 depends on high-quality, connected data, but siloed systems and inconsistent standards block progress. This session will show you how to design data foundations with interoperability, privacy, and reuse by default so your AI initiatives can scale responsibly across programs and agencies.

- Transform fragmented data into shared assets by adopting open data standards, common identifiers, and federated data architectures that break silos.

- Advance data governance using automated lineage tracking, privacy-enhancing technologies, and consent management that protect individuals while enabling AI.

- Reduce preparation time by building reusable data pipelines, quality checks, and metadata catalogs that make clean data available on demand.

- Optimize AI readiness by creating labeled training sets, synthetic data for testing, and explainable feature stores that accelerate responsible model development.

- Improve cross-agency collaboration using data-sharing agreements, secure APIs, and shared analytics platforms that enable joined-up insights.

Complex decisions require judgment, but AI can surface insights, flag risks, and recommend options faster than manual analysis. This session will teach you how to design AI-assisted decision support that augments expertise without replacing accountability so your teams can make better choices under pressure.

- Amplify decision quality by using AI to analyze case history, identify patterns, and surface relevant precedents that inform judgment.

- Advance risk management with AI-powered alerts that flag compliance issues, contradictions, or missing information before decisions are finalized.

- Reduce cognitive load by presenting AI recommendations with explainable reasoning, confidence scores, and links to supporting evidence.

- Optimize human oversight by designing one-click escalation paths, audit trails, and feedback loops that let staff correct AI errors and improve models over time.

- Improve outcomes by measuring decision speed, consistency, and satisfaction before and after AI adoption to prove value and guide iteration.

Proactive, personalized services can meet citizens where they are, but privacy concerns and compliance risks hold many agencies back. This session will teach you how to use AI-driven personalization responsibly with consent-based triggers and data minimization so your services feel human and earn trust.

- Enable proactive notifications using life-event and case-event triggers that reach citizens at the right moment without intrusive surveillance.

- Advance consent-based personalization through transparent opt-in flows that give citizens control over what data is shared and reused.

- Reduce privacy risk by applying data minimization and purpose limitation by default in every AI-powered workflow.

- Amplify accessibility using AI to generate adaptive formats, plain language summaries, and multi-language support tailored to individual needs.

- Assess your readiness with a personalization maturity model and start with one low-risk, high-value journey in the next 30 days.

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.

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.

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.

Pilot AI projects are proliferating, but scaling responsibly requires governance, safeguards, and shared infrastructure that most agencies lack. This panel will showcase how Alberta is building repeatable AI platforms and oversight models using its Data Ethics Framework so you can move from experimentation to enterprise-wide deployment without compromising trust.

- Explore Alberta's Data Ethics Framework as a formal governance model that establishes strict standards for privacy, transparency, and ethical use of citizen data across all AI initiatives.

- Advance governance using mandatory privacy impact assessments, bias audits, and independent review processes that catch risks before AI systems are deployed at scale.

- Reduce duplication by creating centralized AI platforms with pre-approved models, explainability tools, and compliance guardrails that teams across ministries can reuse.

- Optimize transparency by publishing an AI register that lists every system in use, its purpose, the data it processes, safeguards applied, and performance outcomes.

- Improve accountability by designing clear redress paths, human oversight requirements, and continuous monitoring that let you pause or adapt AI systems when safeguards fail.

Leaders need evidence that AI and automation deliver value, but productivity gains are hard to measure and easy to overstate. This panel will explore documented case studies of intelligent automation program and enterprise modernization so you can learn from initiatives that saved hundreds of work-years and apply proven measurement methods.

- Explore deployed Robotic Process Automation (RPA) to automate IT service requests and HR onboarding, saving over 200 work-years of manual labor with measurable time and cost reductions.

- Advance back-office productivity by consolidating HR, finance, and procurement systems into the cloud platform, streamlining workflows and reducing duplication across the Public Service.

- Optimize measurement by tracking baseline performance before automation, comparing outcomes at 30, 60, and 90 days, and publishing dashboards that show hours saved, error reduction, and staff satisfaction.

- Transform investment decisions by using productivity evidence to prioritize high-impact automation projects and retire tools that do not deliver measurable public or operational value.

- Improve transparency by documenting what worked, what failed, and the lessons learned so other jurisdictions can accelerate their own automation journeys with confidence.