AI Strategy for the Federal Public Service 2025-2027: Full-text

Overview

In this section:

• Why an AI Strategy?
• Vision
• Principles
• Scope
• Foreword from the President, Chief Information Officer and Chief Data Officer

Why an AI Strategy?

Artificial intelligence (AI) presents unprecedented and wide-ranging opportunities to enhance the public service and the services it offers Canadians. AI can unlock capabilities beyond human limits, opening doors to new ways of working and operating. With AI, we can create new types of services to better meet the needs of those we serve and improve the quality and efficiency of services already offered.

AI can streamline or automate routine tasks for public servants, freeing them to focus on more complex and critical work. It can increase the public service’s efficiency, effectiveness and productivity, maximizing its value to Canadians. It can improve the speed and scale of data and information analysis far beyond what was once possible, leading to faster, more informed decision making and scientific discovery. It can also create new avenues for public engagement and help us protect Canada’s interests by enhancing our ability to protect our IT and physical infrastructure.

AI is not new to the Government of Canada: departments have been using it for decades. Often developed in-house, early AI applications typically served very specific purposes and were used only by specialist staff. Over the past few years, however, AI capabilities have advanced rapidly, particularly in the field of generative AI. These capabilities are now embedded in a wide range of commercial software, making them more accessible to all public servants.

Learn more about: AI in the Government of Canada

Below are some examples of how AI is being used to improve the work of the Government of Canada.

Case processing: Immigration, Refugee and Citizenship Canada’s Advanced Analytics Solutions Centre

The Advanced Analytics Solutions Centre at Immigration, Refugees and Citizenship Canada has been using AI-based models to triage applications for temporary and permanent residence and find those which can be automatically identified as eligible. These models have been used to accelerate the processing of more than 7 million routine cases, allowing case officers to focus on more complex cases, and to strengthen program integrity by identifying fraud patterns.

Serving clients: Agriculture and Agri-Food Canada’s AgPal

 AgPal helps farmers and agri-businesses find information about over 400 federal, provincial, territorial, and municipal programs and services, along with market intelligence and research. Its generative AI tool, AgPal Chat, helps users find relevant funding and resources faster, supporting the sustainable growth and competitiveness of the sector.

Supporting public servants: The Public Services and Procurement Canada Human Capital Management AI Virtual Assistant

Human Capital Management AI Virtual Assistant is designed to support Pay Centre compensation advisors in processing pay cases from the backlog. The assistant automates routine tasks, allowing advisors to focus on complex cases and expedite resolutions. By shifting from manual to digital processes, it enhances efficiency, reduces workload, and minimizes errors.

Conducting research: Statistics Canada

Statistics Canada works with provinces and territories to collect data for the Canadian Coroner and Medical Examiner Database and organize the collected data into coherent datasets. Analysts can then assess the datasets for patterns of death over time, detecting trends to understand growing hazards to public health.

Transcribing and summarizing: Innovation, Science, Economic Development Canada’s (ISED) AI Accelerator

ISED developed a tool for its Parliamentary Affairs Unit that uses AI and open data to transcribe and summarize parliamentary committee meetings. By reducing manual notetaking, it frees Parliamentary Affairs Officers to dedicate more of their skills to analysis and interpretation, improving efficiency and employee well-being by cutting down on overtime.

Increasing productivity: Shared Services Canada (SSC)

SSC is piloting its multilingual conversational chatbot CANChat as an in-house alternative to commercial generative AI tools. CANChat can support drafting, editing, researching, summarizing, and information and data management and analysis. For greater data security and privacy, CANChat ensures that all data is safeguarded and stored in Canada, and that prompts are not used to train its AI.

Securing networks: The Canadian Centre for Cyber Security’s Assemblyline tool

The Assemblyline tool works to defend federal and critical infrastructure systems from cyber threats involves detecting patterns in vast quantities of data—something AI tools are ideally suited to. Since 2017, its Assemblyline tool has used machine learning to analyze malicious software, scanning over 1 billion files a year for over 300 Government of Canada and critical infrastructure organizations

Securing borders: Transport Canada’s Pre-load Air Cargo Targeting (PACT) program

The PACT uses AI to screen inbound air shipments before takeoff to flag those that could contain concealed explosives or other threats. The use of AI has enabled a tenfold increase in the number of shipments screened per hour and increased coverage from 6 percent to 100 percent of flights, greatly increasing safety on both passenger and cargo flights.

These advances have also greatly increased the risks of AI and the challenges of managing them. They have heightened the potential for AI to overturn traditional ways of working in the public service and have increased public scrutiny of government use of AI. Beyond ethical and security concerns, challenges such as talent shortages, infrastructure gaps, technological sovereignty, and interdepartmental collaboration further complicate AI adoption. Existing and future AI systems must therefore be appropriately governed, with guidance, policy, and training in place to manage risk, address challenges, and uphold human rights, public trust, and national security. At the same time, there are real risks and opportunity costs if we fail to adapt to these new technologies.

The Government of Canada needs an AI strategy to ensure that its AI adoption and use:

• Is aligned with the government’s values and ethics, objectives, and mandate to serve Canadians
• Prioritizes uses that will meet the needs of and deliver the greatest benefits to public servants and those they serve
• Is developed efficiently and collaboratively with internal and external partners
• Is responsible, safe, and secure, mitigating threats, risks, and harms to people and the environment

Vision

By responsibly adopting AI, the Government of Canada ​can deliver world-class services to its clients, protect our people and interests, achieve a more innovative and efficient workplace, and accelerate scientific discovery for the benefit of all.

Principles

Human centred

We focus on the needs of those we serve and the public servants who serve them in deciding where we adopt AI and how we integrate it into our work.

Collaborative

We work together on AI adoption with Indigenous and Canadian partners, other Canadian and international jurisdictions, and our public service colleagues.

Ready

We have the data, infrastructure, tools, culture, talent, skills and policy we need for responsible, safe, secure, and successful AI adoption.

Responsible

We inform clients and public servants when and how we use AI so that they trust that our use of AI respects privacy and is justified, responsible, fair, safe, and secure.

Scope

Many different definitions for AI exist, including the definition in the Government of Canada’s Directive on Automated Decision-Making. One of the most widely accepted definitions comes from the Organisation for Economic Co-operation and Development (OECD), which defines an AI system as:

a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment.

AI includes:

• Both knowledge-based systems that use a combination of domain knowledge, rules, facts, and relationships curated by human experts and machine learning systems that that can learn from data and generalize to perform tasks without explicit instructions.
• Application areas such as computer vision, natural language processing, speech recognition, intelligent decision support systems, and intelligent robotic systems.

This current strategy applies to all types of AI technologies with adaptive capabilities after initial training:

• At any stage of the AI lifecycle, from design, development, deployment, and operation to system decommissioning.
• In use for any purpose in any department or agency covered by the Policy on Service and Digital, including those used by external subcontractors. Organizations that are partially or wholly exempt from the Policy on Service and Digital, including those that fall under the national security exemption, are encouraged to comply with the AI Strategy as far as possible as a matter of good practice.
• Whether they are developed within the Government of Canada, open source, commercial off-the-shelf products, or custom vendor solutions.

The AI Strategy excludes:

• Systems that only use software-based solutions without adaptive capabilities after initial training
• The adoption of AI by organizations outside the Government of Canada.

Learn more about: How we used AI in developing this Strategy

The team responsible for the development of the AI Strategy used an approved generative AI tool (Microsoft Copilot) and some Microsoft Teams AI capabilities to support the work of its members.
AI was used during development to:

• Automatically transcribe some discussions
• Summarize and group comments and feedback
• Generate meeting invitation text
• Scan and summarize research
• Translate small pieces of text
• Draft and edit reports and discussion papers

All uses of AI were consistent with TBS policy and guidance. Any personal identifiers, such as individual or organization names, were removed before AI use. Products generated by AI were reviewed by human analysts and were labelled to indicate that AI had been used in their development.

In total, these uses of AI saved analysts approximately three weeks’ work during the development process, enabling the team to allow more time for engagement and consultation.

For more information, please see Guide on the use of generative artificial intelligence - Canada.ca

Foreword from the President, Chief Information Officer and Chief Data Officer

Message from the President

Artificial intelligence (AI) has the potential to revolutionize the way Canadians interact with the Government of Canada. By using AI responsibly to modernize government operations, we can unlock new ways to increase productivity, efficiency and effectiveness, while reducing response and wait times. We can make it easier for Canadians and Canadian businesses to access all of the services, information, and opportunities the Government of Canada has to offer.

While the adoption of AI for its innovative applications is becoming the emerging norm worldwide, we must ensure its responsible use by assessing and mitigating the risks. This means addressing bias and preventing misinformation, protecting the privacy and security of Canadians, and ensuring that the benefits of AI do not come at the expense of our environment or our workforce. AI is simply a tool, not a replacement for public servants, as we look to modernize government operations to meet the needs of Canadians in the digital 21^st century.

The Government of Canada’s first-ever AI Strategy for the federal public service will allow us to seize the opportunities of innovative technology while establishing guardrails to protect our systems. In developing this Strategy, we engaged the public, partners and stakeholders. Participation from citizens was central to ensuring a Strategy for the public service that reflects the very democratic values we prioritize today.

As we implement the Strategy across the public service, our work will continue to focus on the needs and expectations of those we serve. This means making sure Canadians are involved in the design of services that use AI. This is especially important for those who may face barriers to access, such as persons with disabilities and members of equity-deserving groups. We will also rely on the expertise of Canadian innovators and businesses that are already global leaders in AI.

The AI Strategy for the federal public service establishes a robust AI governance framework to ensure the transparent and responsible use of AI. Ultimately, Canadians need to have confidence in how government uses this technology. Trust is built by being upfront and open about the use of AI, and that is central to the success of the AI Strategy.

To learn more about how the Government of Canada plans to harness the potential of AI responsibly and for the benefit of all Canadians, I invite you to read the full Strategy.

The Honourable Ginette Petitpas Taylor, P.C., M.P.
President of the Treasury Board

Message from the Chief Information Officer and Chief Data Officer

We are pleased to present the AI Strategy for the Federal Public Service 2025–2027, our plan for the responsible, secure, and accelerated adoption of AI in the public service.

AI is a transformative force. It can enhance the capabilities of public servants and change how we work and what we do. Adopting it in the workplace can improve our operational efficiency by automating certain repetitive manual processes and allowing employees to focus on more complex and strategic work, such as supporting decision-making and improving collaboration.

The AI Strategy lays out a plan for how we move forward with AI. It highlights the importance of coordinating approaches across federal organizations, learning from our collective experiences, and supporting organizations of all sizes and maturity as they explore this technology. It sets out the role of public service leaders in adapting AI to their organizations’ mandates, ensuring strong data foundations for future AI projects, and adopting more agile practices for development and procurement.

The responsible adoption of AI will require culture change within our organizations. The Treasury Board of Canada Secretariat will encourage departments to give employees the time, space, support, and tools to explore its use, grow from setbacks, and collaborate with partners, both internal and external to government.

Implemented together with the Government of Canada’s Data Strategy, the AI Strategy will help maximize the effectiveness and value of data and AI investments across government, delivering benefits for service delivery, science and research, security, and corporate processes.

We encourage all federal organizations to embrace AI responsibly to meet the expectations of all Canadians for secure and modern government operations in the digital age.

Dominic Rochon
Chief Information Officer of Canada

Stephen Burt
Chief Data Officer of Canada

Priority areas

Canada’s AI Strategy for the Federal Public Service focuses on four priority areas:

• Priority 1: Central AI capacity
• Priority 2: Policy, legislation and governance
• Priority 3: Talent and training
• Priority 4: Engagement, transparency, and value to Canadians

These priorities were developed in collaboration with a working group of departments that have responsibilities for AI policy or implementation. They were discussed throughout our consultation with partners, stakeholders and the public and in policy consultations across the Government of Canada. They address what we heard as the most pressing needs to advance responsible adoption of AI across the Government of Canada.

Each of these priorities has a set of accompanying actions. These have been chosen because they are concrete, can be achieved or initiated within the AI Strategy’s two-year timeline, and have the greatest potential to advance responsible AI adoption within the public service. These actions include both ongoing and new work. Some will build on work already begun, or scale innovations and emerging best practices. Others are new actions to respond to emerging needs and known barriers that must be addressed if AI adoption is to succeed.

These priorities and the associated actions reflect the time when the AI Strategy was developed. Because the future pace and direction of AI development is highly uncertain, what we and our partners, stakeholders, and clients identify as priorities may be very different at the end of the Strategy’s lifespan.

To remain relevant in this rapidly changing landscape, the AI Strategy and its implementation plan will be reviewed frequently and will be renewed in 2027. Progress on implementation will be reported on a quarterly tracker. In this way we will model the agility needed for AI adoption, adapting our priorities to meet new needs while continuing to collaborate with users and engage those we serve.

Priority 1: Central AI capacity

A common theme heard from government departments during consultations was a need for a central hub to support project implementation and share knowledge. AI accelerators or specialist technical teams able to support project teams with technical development are increasingly being established within departments. However, there is an unmet need for guidance on many other aspects of AI implementation. These include identifying use cases, evaluating data readiness, assessing risk, determining whether to build or buy solutions, and navigating assessment, governance, and procurement processes. Departments also commonly expressed a need for a convenor to share knowledge, code, scalable tools, and lessons learned from departmental experience.

Learn more about: AI Accelerators in the Government of Canada

Over the past decade, more and more Government of Canada departments have established their own AI accelerators or centres of expertise to promote departmental adoption. Some examples of these include:

National Research Council’s (NRC) AI Accelerator and Digital Technologies programs

The NRC has promoted AI adoption across federal departments and agencies through its AI Accelerator and Digital Technologies programs, completing over 100 projects in the past five years. These initiatives span national security, digital privacy, digital health, scientific discovery, logistics, geospatial analytics, and Indigenous languages, improving public services, productivity, and situational awareness. With over 110 AI specialists and access to advanced computation facilities and global partnerships, the NRC supports and enhances AI initiatives across the Government of Canada, driving innovation and adoption for a more secure and technologically advanced nation.

Shared Services Canada’s Artificial Intelligence (AI) Program and AI Centre of Excellence (AICoE)

The AI Program and the AICoE Incubate AI use cases, promote the use of AI, break down silos and foster digital innovation. Established in 2019, the AI Program has incubated more than 15 use cases, including CANChat. The AI CoE supports Government of Canada exploration of AI and intelligent automation, providing a central repository for sharing best practices, training materials, and strategic guidance. It convenes AI and intelligent automation working groups to explore challenges and identify opportunities and solutions to accelerate responsible adoption. The AI CoE also provides guidance to departments embarking on AI adoption and contributes to Algorithmic Impact Assessment peer review and the development of policy.

Natural Resources Canada's Digital Accelerator

NRCan works with scientists, economists and researchers to pilot advanced solutions and tools, including AI, strengthen digital expertise and literacy in the department and sector, and future-proof the department and its partners. Its projects include platforms or tools for accelerated materials discovery, mineral detection, industrial systems performance optimization, and grid optimization for electric vehicles.

Key actions

Establish an AI Centre of Expertise for the Government of Canada

The AI Centre of Expertise (AI CoE) will complement services offered by existing accelerators and centres, focusing on project support, knowledge sharing, and strategic guidance to support AI adoption and experimentation. It will provide project guidance, advise on common processes, and share best practice, experience, knowledge and code. It will also encourage interdepartmental or whole-of-government collaboration on solutions for common needs. The AI CoE will help business teams to:

• Identify high-value use cases for AI integration. This may include helping departments evaluate factors like task and data suitability; infrastructure, model, and data requirements and limitations; cost/benefit analysis; privacy, accessibility, environmental, and equity considerations; risk identification, evaluation, and mitigation; workforce impacts; and how to evaluate project success against objectives.
• Support data readiness: This would include supporting the implementation of the 2023-2026 Data Strategy for the Federal Public Service as a critical enabler for AI adoption. The AI CoE could advise departments on preparing their data for AI use or training and identifying Government of Canada datasets that could be combined to enable AI.
• Support with procurement, governance, assessments, review processes, and other requirements. This would include providing guidance on options for procurement; algorithmic, accessibility, language, privacy, and environmental impact assessments; transparency, reporting, ethics, bias, peer review, GBA Plus analysis, and Indigenous Data Sovereignty requirements; securing AI and understanding risks; and processes for explanation and recourse. It will also include providing input into the development of a governance framework (see Priority 2) and the creation of standard language to inform vendors of their role in responsible AI adoption.

In addition to supporting project teams, the AI CoE will act as:

• A convenor for government-wide knowledge sharing. It will share successful initiatives to prevent duplication of effort, maximize return on investment, and promote awareness and adoption of existing approved solutions. This will include sharing government-developed code and solutions, project documentation, information, policy, and instruments; soliciting feedback, use cases, and lessons learned from departments; and encouraging the scaling of successful projects. It will also work with the Canada School of Public Service (CSPS) to identify and promote training priorities and provide input into new policy or procurement vehicles.
• An accelerator for AI solutions to meet common Government of Canada needs. Working with departments, the AI CoE will identify potential solutions that meet government-wide needs that could be broadly scaled and support their development.
• A monitor of progress on AI adoption. The AI CoE will develop frameworks for progress and impact of Government of Canada AI adoption that can be used to benchmark, monitor, and report on the progress and compliance with policy and standards.

Enable common infrastructure

The Government of Canada and departments will ensure the provision of common infrastructure to enable AI adoption and will promote the adoption of existing approved enterprise solutions. This includes:

• high-performance computing (HPC) and cloud infrastructure that is available, secure, and scalable to meet the demands of AI projects. 
• common data and information management systems and practices to support sharing, scaling, and agentic capabilities across Government of Canada platforms.
• access to approved models, services, and application programming interfaces (APIs) within common Government of Canada cloud platforms to build or deploy systems.
• access to common AI solutions and capabilities in vendor solutions through a standard Government of Canada platform service.

Where possible, they will support Canadian suppliers and vendors in order to promote the growth of the Canadian AI industry and ensure secure sovereign infrastructure and solutions.

Identify and develop a lighthouse project

This project will be either a new initiative or one currently at pilot stage that would meet an enterprise-wide need and could be readily scaled. Its development, testing, and delivery will be undertaken collaboratively by the AI CoE and lead department. It will serve as:

• A test case to identify barriers and project teams’ needs for support during development and obstacles to subsequent customization and scaling.
• A pilot for the development of government-wide governance processes (see Priority 2 ).
• An opportunity to develop templates and examples of project documentation.
• A demonstration of the value of AI use cases.

Learn more about: The lighthouse project

The Strategy proposes the development of a lighthouse project that would both meet an enterprise-wide need and provide an opportunity to develop and test Government of Canada governance and support processes for AI adoption.

As its first lighthouse project, TBS will work with the Translation Bureau at Public Services and Procurement Canada (PSPC) to scale its self-serve language hub pilot across the Government of Canada.

The Translation Bureau has developed a self-serve language hub pilot to provide PSPC employees with access to a variety of secure, real-time AI-driven language tools, trained with Canadian data. These include automated translation tools that can be used to provide instant translations of low-risk and low-value documents. The service operates in a secure cloud up to Protected B, with all data centralized within the Bureau and housed in Canada.

For users, this would provide a secure and approved one-stop shop for linguistic needs. For the Government, availability of an approved automated tool would reduce translation costs without compromising data security or sovereignty or product quality. Use of the Translation Bureau’s repository of 8 billion words (2 TB) to train the model would ensure a high level of consistency, quality, and customization to the specificities of Canadian culture, identity and realities.

Priority 2: Policy, legislation, and governance

Responsible AI adoption needs clear, up-to-date legislation and policy. Together, they mark out not only the necessary guardrails for identifying and mitigating risk, but also the space within which developers are free to experiment and innovate. Clear legislation and policy help to build public trust, overcome institutional resistance to AI innovation and enable governments to move further and faster.

As in many jurisdictions, some Canadian legislation and federal policy has not been revised for the AI era. Some law or policy is silent on areas needed to govern AI, while others may introduce unintended bias in data collection or obstruct AI adoption unnecessarily and unintentionally. Incremental development has created a patchwork of policies that are difficult for AI project teams to understand and navigate, and no common model for AI governance yet exists within the Government of Canada. These challenges must be addressed to build public confidence in the Government of Canada’s ability to deliver AI-enabled services.

Learn more about: AI-ready law and policy

Policy, law, and regulations must support the use of AI and must be kept updated to ensure that they remain relevant and effective as technology evolves. In response, the Government of Canada and leading jurisdictions worldwide have begun to incorporate commitments to scheduled review cycles into key laws and policy instruments, a new best practice that should be more widely adopted.

• The Government of Canada’s Directive on Automated Decision-Making and associated Algorithmic Impact Assessment tool are reviewed every two years. 
• Amendments made in 2019 to the Access to Information Act include a 5-year review cycle.
• The EU AI Act includes provisions for an annual review of both its list of high-risk AI systems and the AI practices it prohibits.

Even without a specified review cycle, other jurisdictions regularly review and amend key legislation and policy:

• Australia has conducted regular reviews of its Privacy Act 1988 to address emerging privacy issues and technological developments, with four major reviews since its enactment.
• The EU regularly reviews its General Data Protection Regulation (GDPR) and other technology-related laws to adapt to new technological advancements and challenges.

Lastly, some jurisdictions have developed guidance to ensure that all new legislation supports new technologies by design.

• Denmark’s digital-ready legislation program has established mandatory assessment against seven principles for digitally-ready legislation to ensure that new laws and regulations are compatible with digital technologies and can be efficiently administered using digital tools.

Key actions

Establish common AI governance and risk management frameworks

Drawing on international and Government of Canada best practice, the Government of Canada will establish common governance and risk management frameworks for the AI lifecycle to provide clear guidance to AI project teams. These frameworks will balance risk with the pace required for innovation; be scaled to system risk, sensitivity, and impact; and will be designed to adapt as technology changes. They will address potential risks associated with AI use, such as data privacy and security, bias detection and mitigation, model interpretability and explainability, environmental impact, and human involvement. The frameworks will incorporate Canadian requirements, such as the need to advance Indigenous Data Sovereignty and provide technologies in both official languages. They will also lay out the security, trust, and reliability controls necessary to ensure the continued maintenance and resilience of these systems, including system shutdown measures to respond to emergencies. This work will support ongoing efforts to harmonize data standards, increase interoperability, and support other enablers.

In addition, it will include a government-wide governance structure responsible for implementing the governance framework. This will include an AI ethics review board responsible for providing guidance on responsible AI and for evaluating higher risk and impact projects at key stages of the project lifecycle. The governance structure will make use of existing Government of Canada governance bodies and organizations such as the Canada AI Safety Institute wherever possible. In addition to providing project governance, these bodies and organizations will help identify high-value AI use cases, regularly reprioritize the AI Strategy's actions, and prioritize and oversee the AI Strategy's implementation.

Address policy and legislative alignment, gaps, and barriers

The Government of Canada will review and propose changes to instruments that create unnecessary obstacles to AI adoption. It will fill identified policy gaps, such as clarifying the responsibilities of chief information, data and privacy officers for AI adoption, and the acceptable use of AI by outside organizations in their interactions with the Government of Canada. It will also address legal and policy ambiguities related to privacy and training data and the application of the national security exemption. The Government of Canada will update procurement policies, instruments and processes to make them more responsive to pace and requirements of AI procurement. It will also consider ways in which the Government of Canada can better align internal AI policy with the Pan Canadian AI Strategy to support the Canadian AI sector, with the United Nations Declaration Act commitments to Indigenous Data Sovereignty, and with international treaties, legislation and norms.

This work will lead to the development of clear and concrete commitments to revise specific instruments within a set timeline, and an agile process to review and update policy, guidance, tools and resources to respond to technological, legislative and social change. The Government of Canada will also review the policy landscape for opportunities to synthesize or interpret existing policy to increase usability.

Adopt a “think AI” approach

The Government of Canada will optimize its AI adoption by embedding a “think AI” approach to its policies, programs and services. The intent is not to adopt AI at all costs or in contexts where its use would not be responsible or useful. Rather, the goal is to challenge departments to identify key business problems that could be transformed using AI, consider AI options before defaulting to traditional IT or HR approaches, and make planned investments in AI and its enablers.

To support this, the Government of Canada will require departments to:

• Identify three areas, programs or services with business problems that have a high potential to be solved using AI.
• Consider solutions and resourcing requirements for AI and its enablers at the outset of initiatives. This will include changes to Treasury Board submissions, Memoranda to Cabinet, and budget and off-cycle funding proposals to incorporate data, AI, compute, and other relevant requirements.
• Prioritize AI infrastructure and secure adoption in departmental integrated IT planning processes.
• Develop their own AI strategies to ensure alignment and effective use of resources.

Priority 3: Talent and training

To adopt AI responsibly, we need people with the right technical and non-technical skills. Although Canada is a global leader in AI research, demand for AI skills significantly outpaces supply. Within the Government of Canada, there is a 30% vacancy rate for digital roles, threatening delivery and leading to a costly dependence on external contractors. As it plans for increased AI adoption, the Government of Canada must consider how it will meet its AI talent needs through training, upskilling, and recruitment so that it can optimize its use of AI to serve Canadians better.

Key actions

Develop a training plan

Building on existing offerings from CSPS, the Government of Canada will develop a training plan for existing public servants. The developed training plan will be evergreen to match the pace of AI development. Through this plan, the Government of Canada will consider ways that AI may reshape the workforce, working with employees and their bargaining agents to prepare public servants for this change through retraining.

The training plan will incorporate both general training and training tailored to specific personas with varying roles, levels and responsibilities. The general training will be directed at increasing understanding of and confidence in using AI, including embedded AI capabilities; developing skills associated with responsible, secure, and effective use, including effective prompt engineering; and establishing leadership programs to achieve a culture that promotes AI adoption. The tailored training will address both more specific and advanced technical skills, and the behavioural skills needed for successful adoption, such risk identification and management, and effective leadership of AI projects and teams.

Benchmark talent needs

The Government of Canada will benchmark both talent requirements for AI and its employees’ existing AI knowledge and skills across the enterprise. These benchmarks will enable the development of learner personas with accompanying training plans and identify employees who could be offered further training.

Develop a talent plan

Since not all talent needs can be met through training, the Government of Canada will need to develop a plan to recruit and retain talent. This plan will explore obstacles to recruitment and retention and ways to establish flexible data science career pathways for AI practitioners. It will also consider ways to expand interchanges, apprenticeships, co-op programs, and partnerships with AI institutes and research centres to create a talent pipeline. It will consider ways to make efficient use of AI talent through flexible assignments, and competitions and challenges to meet some project-based needs.

Learn more about: AI and data talent pathways

To meet the challenge of AI talent needs, both departmental and government-wide initiatives are being developed to improve recruitment, retention, and reskilling:

Digital Talent Strategy and Platform:

The Government of Canada is committed to strengthening AI talent and adoption through the Government of Canada Digital Talent Strategy. Its targeted initiatives include centralized AI-specific recruitment campaigns for data science graduates and the Digital Talent Platform, which simplifies the application process for individuals looking for digital careers in the Government of Canada and helps managers to find pre-qualified digital talent that matches their needs. The Strategy also focuses on developing and retaining AI talent through learning platforms, training opportunities, and partnerships with educational institutions and the Canada School of Public Service.

Training:

CSPS offers a range of courses, events, and resources on AI designed to provide users with a grounding in the knowledge and skills needed for successful and responsible use. These include a data and AI learning pathway, courses, job aids, articles, and videos, and an AI event series.

Co-op programs and internships:

Co-op programs are widely used by the Government of Canada as a source of new talent but have also been reimagined to support specific AI initiatives. Agriculture and Agri-Food Canada established an AI talent pipeline with three post-secondary institutions. Through it, AAFC hired 13 co-op students in 2023-24 and supported in-class projects with the institutions. From this partnership, students received course credit and employment experience, while AAFC received an AI model, with ownership of both IP and data. The Canadian Food Inspection Agency, Employment and Social Development Canada, Natural Resources Canada, and Statistics Canada have become partners with Mila, offering opportunities to recruit Mila students for internships or post-graduation roles.

Priority 4: Engagement, transparency, and value to Canadians

Despite the increasing use of AI in Canada, levels of mistrust in AI and its use are high. In public consultations on the AI Strategy, participants expressed a desire for more engagement in the process of designing and developing government AI systems, especially by those more greatly impacted by algorithmic bias or barriers to access. They asked for greater transparency about the government’s AI use through labelling of AI-generated products and information on systems in use, and for information about ways to seek explanations or recourse for decisions.

Key actions

Strengthen accountability and transparency on AI use

The Government of Canada will continue to strengthen and clarify accountabilities for AI use in policy and in notifications about AI use. These will include new requirements and standard language for the disclosure of AI use, explanations of how an AI system reaches a decision, and information about rights and protections, including how to seek explanations or recourse and how to report problems. Lastly, the Government of Canada will identify those AI capabilities that it will not pursue.

As part of these efforts, the Government of Canada will prioritize the establishment of a public register of its AI systems. The register will include information about all AI systems that fall within a defined scope, drawing wherever possible on information already collected through Algorithmic Impact Assessments and Personal Information Banks. The scope of the register will be defined and publicized on the register itself and will follow best practice for registers in other jurisdictions, which exclude embedded AI systems and any systems covered by specific policy prohibiting publication. The register will include information about what and how data is being used, how it was trained, and what quality assurance and privacy and security measures are in place. Where information about systems cannot be published, the Government of Canada will develop and publish alternative oversight processes.

Demonstrate impact and value to Canadians

To ensure good stewardship of public resources, the Government of Canada will develop metrics and performance indicators to demonstrate the impact and value of AI initiatives to those we serve. This will track both the cost-effectiveness and cost-efficiency of AI projects through a range of financial and non-monetary metrics, including costs of implementation, efficiencies and cost savings achieved, service improvements, increased client satisfaction, or increased program uptake.

The Government of Canada will also develop a framework to track AI adoption. This framework will incorporate metrics for the deployment of AI solutions overall, but also for metrics such as collaboration, sharing, or scaling of solutions to avoid duplication of effort, maximize investment, and reduce costs. The metrics will also track departmental investments in the enablers of AI, including data, infrastructure, and talent.

Commit to engagement on AI

In keeping with its commitments to meaningful public engagement through the Directive on Open Government, and with the duty to consult, the Government of Canada commits to early and meaningful public and stakeholder engagement on AI initiatives of significant public interest or concern. This will include targeted engagement of communities that face greater impacts, risks or barriers from AI systems and union and employee engagement on workforce impacts. It will also include client participation in system design to ensure that AI systems do not create or perpetuate barriers to access for clients. The Government of Canada will also provide mechanisms for ongoing public feedback and questions on AI used by the federal government.

Learn more about: Public AI registers

Public AI registers are standardized, searchable databases that document the decisions, assumptions, and processes involved in the lifecycle of AI algorithms used by government organizations. AI registers usually include:

• A non-technical overview of the AI application’s goals, use cases, and impacts.
• The organizations responsible for the system.
• Stage and date of system development.

Some registers also include information on

• Data origins, management, processing, and quality issues.
• Model architecture, key features, parameters, performance, and source code.
• Bias, accessibility, and how those impacted were involved in system development.
• Risk levels and mitigation, risk-benefit trade-offs, and impact assessments.
• Human oversight in development, decision cycles, and monitoring.
• How those impacted can seek an explanation for decisions.
• Relevant privacy policies, information and system governance models, supplier contracts, and audit reports.

Most registers exclude AI that is embedded within commercial products, such as virtual assistants or spell checkers, but encourage organizations to default to reporting systems if unsure whether they qualify. They also exclude systems that fall under law or policy prohibiting public disclosure, which may be reported to oversight bodies instead.

From 2020 to 2024, under Executive Order 14110, the US government required all federal agencies to publish an annual inventory of their planned, new, and existing AI use cases, with exclusions only for very simple rule-based systems, robotic process automation, and defence systems. Other jurisdictions with AI registers include the Netherlands and Scotland, state governments of Texas, Vermont, Washington, and Catalonia, and municipalities of Amsterdam, Helsinki and San Jose.

Expectations for federal organizations

Approach

The AI Strategy lays out an approach for the Government of Canada to follow in advancing its AI adoption, but there is clearly much work still to be done in pursuing its implementation. During the months following publication, TBS will be engaging departments on the actions laid out in the AI Strategy to confirm action leads and develop a detailed implementation plan including resources, responsibilities, timelines, and milestones. It will also continue to engage all departments on action implementation to ensure horizontal alignment.

Expectations of all federal organizations

All federal organizations have a part to play in the implementation of the AI Strategy, regardless of whether they are leading actions within it. To prepare for this, all organizations should:

• Identify and prepare to report on their existing AI use cases and those in development, including actualized and estimated impacts of AI adoption.
• Identify key business problems where AI could be applied.
• Ensure employees have access to approved AI tools and the training required for safe, secure, and responsible use.
• Ensure that AI project teams have access to the necessary infrastructure and compute resources to support AI research and development.
• Review the alignment between their departmental policies and strategies on AI and its enablers and the AI Strategy.
• Review their compliance with existing policy requirements or expectations related to AI and its enablers, as set out in the 2023–2026 Data Strategy for the Federal Public Service, the Directive on Automated Decision Making, the Directive on Digital Talent, and the Policy on Service and Digital.
• Review expectations on inclusive consultation within the Trust and Transparency Strategy, the Digital Standards, and the duty to consult and Principles respecting the Government of Canada’s relationship with Indigenous peoples.
• Identify departmental policy, process, and technical barriers to AI adoption.
• Review their own technical and non-technical talent needs for AI adoption.
• Familiarize themselves with resources such as the list of interested AI suppliers and open-source software.

Relevant strategies and policy

The Strategy builds on existing commitments in other strategies to the responsible adoption of AI and its enablers such as infrastructure, data, cybersecurity, and talent.

Strategies

2023-2026 Data Strategy
Developing and implementing common data stewardship practices, using the Government’s data holdings to derive insights for decision making, and building both specialist capacity and data literacy within the public service through access to tools and training. Given the dependence of AI on quality data, the implementation of the Data Strategy will be a critical enabler for the success of the AI Strategy.

Digital Ambition
Foresees the use of AI as part of the goal of delivering modern services with a digital mindset. It identifies the need for responsible AI, fairness and transparency to allow Canada to benefit from efficiency gains while countering potential harms from ungoverned AI. It also identifies the importance of transparency and preserving privacy in the handling of personal data to maintain the trust of Canadians.

Application Hosting Strategy
Explains how the Government of Canada will optimize its use of cloud to maximize business value, reduce technical debt, and continue to evolve its service-focused culture.

Canadian Sovereign AI Compute Strategy
Invests in public and commercial computing infrastructure to support the Canadian AI ecosystem and safeguard Canadian data and intellectual property.

Enterprise Cyber Security Strategy
Sets out a risk-based, whole-of-government approach to ensure that the Government can quickly and effectively combat cyber threats and address vulnerabilities. It aims to help safeguard government systems, protect Canadians’ information and strengthen the resilience of digital government to ensure the continued delivery of secure and reliable digital services. foster the right skills, knowledge, and culture to support cyber security.

Policies

The AI Strategy should also be read in the context of relevant laws and policies:

• Policy on Service and Digital
• Directive on Automated Decision Making
• Values and Ethics Code for the Public Sector
• Guide on the use of generative artificial intelligence
• Government of Canada Enterprise Architecture Framework
• Directive on Digital Talent
• Digital Standards Playbook 
• Policy on Government Security
• Policy on Privacy Protection
• Directive on Open Government
• Accessible Canada Act
• United Nations Declaration on the Rights of Indigenous Peoples Act Action Plan 2023-2028

Together, these policies create a framework for responsible, secure and successful AI adoption.

Engagement and consultation

Between May and October 2024, TBS engaged stakeholders, Indigenous partners, public servants, and the public on the development of the Strategy. TBS held roundtables to seek the input of academics, civil society, Indigenous organizations, industry, and labour, engaged provincial and territorial governments and other federal departments, and held a public consultation through Consulting with Canadians.

Key findings

The findings of these engagements can be found in the What We Heard report. Key themes heard from participants included:

Engagement and inclusive design

Participants highlighted the importance of engagement and partnerships with academia, civil society, Indigenous partners, industry, and other jurisdictions on AI adoption. They also suggested holding regular public consultations to gather feedback and ensure that AI initiatives are aligned with public expectations and collaborating with international and multilateral partners to align approaches. AI systems must be designed to meet the needs of all users, especially marginalized communities, requiring engagement with groups which have specific access or accessibility needs.

Ethical use

Respondents said comprehensive ethical guidelines for AI use in the federal public service were essential. These guidelines should cover fairness, transparency, accountability, and bias prevention. Respondents suggested regular ethical audits to ensure compliance with the guidelines and prevent harmful biases.

Preparing the workforce

Participants saw a need for comprehensive retraining programs to equip public servants with the skills to work with AI technologies, and to consult bargaining agents on retraining and impacts on public service workforce.

Infrastructure and data readiness

High-performance computing and cloud infrastructure should be available, secure and scalable to meet the demands of AI projects. The Government of Canada also needs continued investment in data governance frameworks to ensure that data is clean, accurate, and available for AI applications.

Environmental impact

The Government of Canada should minimize the environmental impact of its AI use by deploying AI appropriately and choosing solutions that demonstrate responsible environmental practices.

Transparency and accountability

Participants wanted clear communication about how and when AI is used, with labels for AI-generated content and published information about AI systems. They also wanted ways to seek explanations and recourse for system decisions.

Potential uses for AI

Participants identified many administrative uses for AI, such as drafting and translating text, managing documents and inboxes, and scheduling personnel processes. They saw potential to use AI to generate insights from large public health, environmental, and economic data sets, and to extract information from legal and policy documents and public consultations to inform decisions. They also proposed using AI to make service and legal case processing more efficient.

No-go areas

Areas cited by participants where AI should not be used included decisions on criminal justice cases, hiring, and social service eligibility, because of the risk of bias and the need for explainability and individual discretion. Participants also felt AI should not be used for mass data collection or surveillance, or to make policy decisions without human input.

An Update on our Progress

Context

The first year of the AI Strategy for the Federal Public Service 2025–2027 (the AI Strategy) made significant inroads. This report highlights what was achieved, what was learned, and how momentum is building. It explains how the Government of Canada improved responsible AI practices, strengthened governance, and helped departments use AI tools in alignment with the AI Strategy.

Looking ahead, the AI Strategy positions the federal public service to move beyond early adoption to sustained, enterprise-wide impact. The goal is to scale trusted AI that improves public services, supports employees and delivers lasting value for Canadians.

Executive Summary

In its first year, the AI Strategy for the Federal Public Service 2025–2027 made significant progress in establishing the foundations for responsible, enterprise-wide AI adoption. The Government of Canada strengthened governance, built core infrastructure, and expanded workforce capacity while demonstrating early, measurable value through practical AI solutions.

Key achievements include:

• Established central AI leadership and coordination to guide departments, support implementation, and promote consistent application of responsible AI practices
• Delivered a flagship lighthouse project (GCtranslate), demonstrating how centrally supported, well-governed AI solutions can scale rapidly
• Strengthened governance, risk management, and transparency, including updates to the Directive on Automated Decision-Making and the launch of the Government of Canada AI Register
• Expanded AI skills and talent capacity, with new learning pathways introduced, and targeted initiatives to build a diverse and future-ready workforce
• Aligned with international leadership and partnerships, including signing the Council of Europe’s Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law and advancing G7 initiatives such as the GovAI Grand Challenge and G7 AI Network
• Advanced shared infrastructure and enterprise capacity, including planning high-performance computing resources, supporting services, and developing options for secure, sovereign AI platforms
• Demonstrated tangible operational and service improvements, with departments deploying AI tools to enhance productivity, improve access to information, and deliver better services to Canadians

Overall, the first year demonstrated clear momentum and growing maturity in the government’s approach to AI. It highlighted the importance of sustained investment, strong governance, and coordinated enterprise approaches to fully realize the transformative potential of AI while maintaining public trust.

Building on this foundation, the next year will focus on scaling responsible AI across the enterprise by strengthening data foundations, advancing shared infrastructure, and prioritizing the deployment of high-impact, scalable solutions. Efforts will shift from pilots to sustained, government-wide implementation that delivers measurable value to Canadians while maintaining strong governance and trust. These efforts will complement and reinforce Canada’s National Artificial Intelligence Strategy: AI for All, which sets Canada’s overall direction for AI leadership and adoption and the development of a strong, sovereign, and innovative AI ecosystem across Canada.

Key forward-looking priorities:

• Accelerate deployment of AI solutions, shifting from pilots to operational, enterprise-wide use
• Prioritize and scale lighthouse projects and other high-impact, reusable solutions
• Expand shared infrastructure and enterprise capacity to support adoption at scale
• Strengthen governance, talent and organizational readiness for responsible AI use
• Integrate Canada’s Data and AI strategies to enable interoperable, high-quality data foundations

Key deliverables under the AI Strategy

In this section

• Central AI capacity
• Policy, legislation and governance
• Talent and training
• Benchmark talent needs
• Engagement, transparency and value to Canadians

Central AI capacity

Establish an AI centre of expertise for the Government of Canada

Over the past year, the Government of Canada increased centralized AI leadership and expertise to encourage responsible AI adoption across the public service. The Treasury Board of Canada Secretariat (TBS) acted as an AI hub by providing guidance, coordinating AI activity and advancing lighthouse initiatives.

Through guidance, tools and hands‑on support, the hub helped teams navigate policy, risk and implementation considerations to translate AI governance requirements into practical, consistent application as new AI capabilities were adopted. These efforts laid the groundwork for a more formalized, sustained centre of expertise to support coordination, guidance and scaling in future years.

Enable common infrastructure

The first year of implementation focused on building the shared technical and service foundations required to support AI at scale. Shared Services Canada (SSC) led key initiatives to ensure that AI was secure and scalable across the federal government. This included:

• planning and seeking funding for high‑performance compute capacity across cloud and on‑premise environments
• ensuring adequate resources and systems to support enterprise services such as CANChat
• developing sovereign and agentic AI platform options for long‑term, secure compute availability

SSC also continued work on an enterprise AI Marketplace. This new tool will provide departments with secure access to approved AI models, tools and application programming interfaces. The tool will reduce duplication and improve compliance, although sustained investment will be required to build and maintain the platform.

To support AI procurement, coordination and adoption, SSC also:

• established a Generative AI Framework Agreement to support consistent and secure access to AI‑enabled services
• published an AI governance framework
• assessed Canadian-made governance tools
• established the Government of Canada AI Forum to promote coordination, knowledge sharing and community building

These efforts improved the shared infrastructure required to move from isolated experimentation toward reusable, enterprise‑level AI services.

Identify and develop a lighthouse project

Lighthouse projects are either a new initiative or one currently at pilot stage that would meet an enterprise-wide need and could be readily scaled. One of the strengths of the AI Strategy for the Federal Public Service is that it identifies a tangible lighthouse project to focus efforts on while, at the same time, leveraging the project to demonstrate how centrally supported, well‑governed AI solutions can deliver real results and value at scale.

GCtranslate was launched by Public Services and Procurement Canada (PSPC) and the Translation Bureau as the first official lighthouse project under the AI Strategy. Following an internal launch in June 2025 and a pilot expansion to seven institutions in September 2025, Phase 1 rollout started on April 29, 2026, and will reach 43 federal institutions and approximately 270,000 users.

GCtranslate embedded official languages requirements, strong governance, central policy support, and user‑centred design from the outset, while addressing longstanding operational needs - high‑quality, simultaneous translation in both official languages. Its rapid growth demonstrates how responsible AI solutions can scale effectively across the public service.

This pathfinder lighthouse project established a clear model for future projects: centrally supported, reusable solutions that meet common needs while maintaining strong governance and trust.

Policy, legislation and governance

Establish common AI governance and risk management frameworks

In year one, the Government of Canada improved common governance mechanisms to support consistent, responsible AI adoption across the federal public service. Departments benefited from guidance, tools and hands-on support to help them navigate risks and implement responsible AI practices more consistently.

The past year saw the completion of the fourth review of the Directive on Automated Decision-Making and the supporting Algorithmic Impact Assessment tool. The updates resulting from the review included:

• increased transparency of systems and their impacts
• improved federal and international policy alignment
• enhanced testing and monitoring requirements
• strengthened senior level accountability

Together, these measures created a more coherent, enterprise-wide approach to AI governance and risk management.

Address policy and legislative alignment, gaps and barriers

The past year, the government focused to make sure that AI was adopted according to existing laws and policies, while also identifying areas that needed modernization or better coordination. As AI technology evolved, the Government of Canada reviewed and refined AI‑related policies to address gaps related to accountability, transparency and oversight.

The Government of Canada also increased alignment with international AI governance frameworks, including signing the Council of Europe’s Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law in February 2025—the world’s first international treaty dedicated to AI.

The National Research Council, launched 14 research projects under its Canadian AI Safety Institute mandate, addressing risks from emerging AI models and agentic systems. These projects cover areas such as multilingual AI safety, cyber security, explainability, deepfake detection, content provenance, and autonomous behaviour and provide evidence and tools to support government-wide responsible AI governance. These projects contributed to a foundation of adaptable AI safety best practices and responsible AI use.

The Government of Canada also took significant steps to modernize digital governance. In Budget 2025, the government announced plans for the Office of Digital Transformation, signalling a renewed commitment to building a modern digital ecosystem with a strong focus on using AI to make federal services faster, simpler and more efficient.

In parallel, new federal bodies—such as the updated Advisory Council on AI and the Safe and Secure AI Advisory Group—were launched to improve oversight and ensure that expert advice informs decision-making.

Momentum grew beyond government, with increased interest in Canada’s Voluntary Code of Conduct for advanced generative AI and more industry partners committing to responsible AI practices.

Adopt a “Think AI” approach

Departments increasingly integrated AI considerations into planning, design and decision‑making. Employment and Social Development Canada (ESDC) implemented mandatory AI intake, review and registration processes for AI projects to increase responsible AI adoption.

This life cycle–based model encourages teams to assess opportunities, risks and governance requirements early and embed ethical, privacy, security and equity considerations from the start. The approach ensures consistent oversight and is being shared with other departments as a potential government‑wide foundation.

TBS provided guidance and hands‑on support to help teams incorporate AI responsibly into program design, service transformation and internal operations.

Talent and training

Develop a training plan

In year one, the Government of Canada took a coordinated approach to building AI literacy and skills across the public service. The Canada School of Public Service (CSPS) expanded AI training, guidance and learning pathways. The Digital Academy launched more than 15 new or updated AI-focused products. Over 31,000 employees registered for foundational AI courses, and an updated Data and AI learning path helped employees at all levels build essential skills.

TBS promoted governance, workforce readiness, and AI skills development across the public service for responsible AI adoption. The CSPS Digital Academy Plan, the Public Service Skills Strategy, and the Office of the Chief Information Officer Digital Talent Strategy delivered coordinated, role-based AI training to support AI literacy and develop capabilities across departments. Together, these efforts established a strong foundation for a government‑wide AI training plan that supports both safe adoption and long-term capability building.

Benchmark talent needs

This past year, TBS also focused on clarifying and benchmarking the AI‑related skills and roles required to support responsible adoption across the government’s diverse mandates.

Standardized data science and analytics job descriptions were created to clarify roles, responsibilities and accountabilities across departments for more effective recruitment and deployment of specialized skills. Clear digital accountabilities for executives further supported alignment between AI‑enabled service improvements and strong cyber risk management.

At the same time, CSPS, through the Government of Canada Data Community, created a common data maturity assessment framework and learning events that strengthened data governance and AI readiness across the public service. Insights from the lighthouse project and departmental implementations informed an emerging understanding of the skills required to move from pilots to enterprise scale delivery.

These activities strengthened the government’s ability to benchmark current and future AI talent needs in a consistent and evidence‑based manner.

Develop a talent plan

Steps were taken to translate training and benchmarking insights into more intentional talent development approaches. To build sustainable and inclusive AI talent pipelines, TBS established coordinated workforce and talent development initiatives across the public service.

TBS’s Office of the Chief Information Officer partnered with chief information officers to deliver the Data & AI Accelerator for Black Public Servants, which combines training, mentorship and experiential learning to build a diverse and skilled workforce for AI‑enabled digital and cyber roles. System‑wide upskilling was expanded through the IT Community Training and Development Fund to align learning investments with evolving AI and digital role requirements.

TBS also launched the Human-centred AI in People Management working group and convened a special session of the Human Resources Council with heads of HR from more than 50 organizations to reinforce an enterprise approach to integrating AI into core HR functions.

Collectively, these efforts laid the groundwork for a more cohesive AI talent plan that balances broad literacy, specialized expertise, diversity and inclusion, and long‑term workforce sustainability.

Engagement, transparency and value to Canadians

Strengthen accountability and transparency on AI use

A major focus for year one was making AI use across the federal government more visible, understandable and accountable. As part of these efforts to support responsible AI adoption and accountability, TBS launched the Government of Canada AI Register in November 2025.

The AI Register gives Canadians information about where and how AI is being used in the federal government. For departments, it supports planning, reduces duplication and helps identify opportunities to work more efficiently.

Between January and March 2026, TBS held public consultations with stakeholders to further refine the register’s design and usability. These consultations strengthened accountability and supported improvement based on user and stakeholder feedback.

Updates to the Directive on Automated Decision-Making further reinforced transparency requirements and senior‑level accountability for AI‑enabled systems. Together, these measures strengthened public trust and reinforced clear lines of accountability for AI use in government.

Demonstrate impact and value to Canadians

Throughout the year, departments used AI to deliver measurable improvements to services, programs and internal operations, with clear benefits for Canadians.

Innovation, Science and Economic Development Canada (ISED) expanded its AI use across programs and internal services by focusing on reusable, scalable systems and reducing duplication. Its growing portfolio includes tools in testing, development or active use, such as ParlBrief for committee meeting transcription, and internal tools like Atlas HR and Ombot that help employees access guidance.

GAC advanced practical AI initiatives that improved services and increased internal readiness. The department launched its first public‑facing chatbot, Eva, through the Trade Commissioner Service to help users quickly access export and investment information. GAC also created a Copilot Studio citizen development hub to build AI literacy and support safe experimentation across the organization.

Internally, departments demonstrated the productivity benefits of secure, well-governed AI. Employment and Social Development Canada (ESDC) piloted EVA Chat, with more than 13,000 employees submitting over 2 million prompts in its first year, showing how generative AI can improve access to information and enable employees to focus on higher‑value work.

To support safe and effective use, ESDC complemented the pilot with targeted upskilling, including the EVA and Microsoft Copilot Course and a dedicated Digital Data and Artificial Intelligence Learning hub to strengthen workforce readiness in an increasingly AI‑enabled workplace. These examples show how responsible AI adoption can translate into tangible service improvements and better outcomes for the public.

Commit to engagement on AI

Ongoing engagement, both domestically and internationally, was a core element of building trust and shared understanding around AI. As part of Canada’s 2025 G7 presidency, the G7 Leaders’ Statement on AI for Prosperity including commitments to accelerate the responsible use of AI in the public sector.

In support of these commitments, Canada launched the G7 GovAI Grand Challenge to develop scalable, impactful and responsible AI solutions to common public sector problems. The challenge focused on four Rapid Solution Labs, where participants from G7 and European Union (EU) countries proposed AI solutions to real government problems. An international panel of AI experts selected seven solutions to receive $10,000 CAD each, along with several honourable mentions and finalists.

Canada also created the G7 AI Network (GAIN), connecting AI adoption leads from G7 countries and the EU. The GAIN supported the Grand Challenge and other G7 commitments by:

• developing a roadmap for scaling AI projects in the public sector, proposing key actions to reuse or expand AI solutions across organizations
• establishing the G7 AI solution directory, a central location for open-source and shareable AI solutions hosted by governments of G7 countries and the EU
• sharing experiences on AI measurement to ensure that government AI solutions have measurable and meaningful impacts

Collectively, these efforts reinforced the Government of Canada’s commitment to ongoing engagement as AI capabilities and public expectations continue to evolve.

Challenges and lessons learned

The first year of implementing the AI Strategy underscored that human-centred, ready AI adoption depends on more than technology. Departments made progress at different speeds based on their digital maturity, organizational culture, workforce capacity and access to high-quality data.

While some departments scaled AI solutions quickly, others focused on foundational work. This highlighted the need for shared enterprise services, common tools and coordinated support for more consistent adoption across government.

Experience also showed that scaling AI requires strong collaboration and alignment across policy, procurement, infrastructure, data and funding. Rigid procurement processes and limited computing capacity slowed broader deployment in some cases. Successful pilots highlighted both the potential of AI and the importance of sustained, multi‑year investments and cross-functional coordination to move from experimentation to enterprise delivery.

Finally, lessons learned emphasized that responsible AI requires practical governance and effective change management. Mandatory intake, registration and life cycle assessment models improved oversight but added work for teams. This made hands-on guidance, clear accountability, role-based training and transparent communication even more important. Together, these elements helped build trust, scale AI safely, and deliver measurable value for Canadians.

Looking ahead

Artificial intelligence is rapidly becoming one of the defining technologies of our time, shaping how economies grow, governments serve citizens, and societies respond to complex challenges.

For Canada, AI presents an opportunity to strengthen prosperity; enhance productivity; improve public services; and ensure that technological innovation reflects Canadian values of fairness, inclusion, safety and trust.

As Canada enters a new phase of AI adoption, Canada’s National Artificial Intelligence Strategy: AI for All sets out a vision for ensuring that AI drives economic growth, strengthens Canadian sovereignty, and benefits Canadians across all regions and sectors. The strategy reinforces a commitment to trusted and widespread AI adoption by emphasizing public trust; AI literacy and skills development; sovereign foundations in data, talent, compute and infrastructure; and the responsible development, adoption and governance of AI.

Within this broader national context, the AI Strategy for the Federal Public Service 2025–2027 provides the roadmap for how the Government of Canada will lead by example and responsibly adopt and scale AI within its own operations.

The strategy complements Canada’s National Artificial Intelligence Strategy: AI for All. Together the two are mutually reinforcing: the national strategy sets Canada’s overall direction for AI leadership; adoption; and the development of a strong, sovereign, and innovative AI ecosystem across Canada, while the federal public service strategy equips government institutions with the governance, talent, data, infrastructure, and implementation mechanisms needed to realize that vision and deliver better outcomes for Canadians.

Moving forward, the government remains committed to supporting departments in responsibly adopting AI, strengthening the data foundations required for effective digital services, and preparing the public service for the next decade of digital government. This effort will ensure that Canada continues to build the capacity, governance, and infrastructure needed to use AI in ways that deliver real value to Canadians.

Work is already underway to bring together Canada’s Data and AI strategies for the Federal Public Service, recognizing that strong, interoperable data systems are essential for scaling trustworthy AI. Future investments will continue to modernize digital infrastructure and support wider adoption across departments.

Federal departments are also identifying needs and gaps that will guide collective action. Departments can expect increased attention on data infrastructure, governance, talent pathways and organizational readiness. These efforts will help the public service adopt AI safely and deliver better services for Canadians.

Alongside these priorities, several initiatives will continue:

• GAC will expand external-facing AI services and citizen development training
• ESDC will explore additional GenAI capabilities in EVA Chat
• GCtranslate will move toward full enterprise rollout by April 2027

Also, new potential lighthouse projects will be highlighted across the enterprise.

Canadian Digital Service’s AI Answers is an enterprise service that helps users navigate Canada.ca by providing faster, accurate, plain language answers in both official languages. Public trials showed strong satisfaction and signalled potential to reduce call centre demand, with built-in safety, privacy and review features supporting continuous improvement. With broader testing planned for 2026, it is emerging as a scalable, cross government self-service tool.

Early conceptual work has begun to explore the feasibility of a government‑wide job library as a potential lighthouse initiative. This concept could bring together modern job architecture and AI‑enabled tools to eventually support more consistent definitions of work across the federal public service. While still at the exploratory stage, this ideation is intended to inform how structured, enterprise‑quality data could, over time, support responsible AI adoption, workforce planning, classification modernization, and future generative or agentic AI use cases. If pursued, such an approach could position the public service to more safely scale AI capabilities, improve mobility and pay equity, and strengthen organizational readiness.

In parallel, exploratory work is underway to consider opportunities to modernize grants and contributions through the exploration of emerging technologies. This early ideation focuses on understanding whether and under what conditions AI can support more intelligent, transparent and efficient allocation of funding while improving fraud detection and reducing administrative burden.

The government has made meaningful progress this year in advancing responsible AI. It demonstrated clear momentum and global leadership through initiatives such as its G7 presidency and major federal investments in digital and AI capabilities. Taken together, the departmental success and enterprise-wide efforts show how the Government of Canada is building a more capable, consistent and responsible AI ecosystem, while also underscoring that continued work is needed to keep pace with rapid technological change and growing expectations for safe, trustworthy and scalable AI adoption.