Securing agentic AI is key for Canada to build trust, ensure sustainable innovation
Canada stands at a pivotal moment to harness the transformative power of agentic artificial intelligence while safeguarding the rights and wellbeing of its citizens.
Profound contributions in AI and computer science by Canadians continue to garner acclaim, while sustained government efforts and private-sector commitments to studios like AXL bolster the country’s unique position as a global research and innovation leader.
These developments expand on the vibrant ecosystem established by Canadian institutions like MILA, AMII and the Vector Institute, whose groundbreaking research attracts global talent and investment.
Sustaining momentum amid rapid transformation is essential for long-term growth. This is particularly important for agentic AI systems that are capable of autonomous decision making and managing complex end-to-end workflows.
Their ability to perform actions that involve both reading and writing data and processes goes beyond traditional large language models (LLMs) that focus primarily on generating information. This heightens risks around data confidentiality, integrity and regulatory compliance—especially when handling sensitive personal, transactional or health data.
As agentic AI systems emerge, it is critical to embed security, privacy and trust guardrails early in their design and deployment to ensure sustainable innovation.
Challenges and opportunities
By its very nature, agentic AI has unique security and governance challenges compared to other systems like generative AI.
Agentic AI systems’ ability to evolve behaviours autonomously necessitates advanced security strategies, including continuous monitoring and fail-safes. Their broad reliance on diverse datasets requires appropriate data governance and security to ensure integrity, privacy and resistance to adversarial attacks.
Agentic AI also comes with inherent ethical risks: without rigorous policy frameworks, autonomous agents may inadvertently propagate biases or cause harm.
To address these challenges, security and ethical controls must be embedded throughout the AI lifecycle—from design to deployment and continuous operation. Making AI systems transparent and auditable goes a long way toward building trust among users and stakeholders.
Robust access controls, ongoing security evaluations and proactive vulnerability management are essential security-by-design measures that businesses should consider implementing. Incorporating human-in-the-loop controls is also critical to maintain human oversight for critical decisions where agentic actions could affect safety or fundamental rights.
Preparing for responsible innovation
Canada is actively shaping a comprehensive regulatory framework to govern AI through the Artificial Intelligence and Data Act (AIDA) proposed under Bill C-27.
While final legislative approval is pending, AIDA lays the foundation for regulating AI systems based on risk profiles—starting with high-impact applications in health care, biometric identification, workforce management, critical infrastructure, education, law enforcement and online content moderation.
Some of AIDA’s key provisions related to agentic AI include:
- Risk mitigation: Obligations on developers and deployers to identify and reduce biases, discrimination and systemic harms
- Transparency: Mandates for explainable AI that would allow affected individuals and regulators to understand AI decision making
- Accountability and oversight: Documentation and co-operation with regulatory audits to maintain trust
- Incident reporting: Prompt notification of significant AI-related malfunctions or harms
There is also complementary legislation, such as the Consumer Privacy Protection Act (CPPA), and sector-specific regulations that reinforce principles around privacy, consent and ethical AI deployment.
For Canadian organizations—both public and private—success in agentic AI hinges on integrating security and governance into innovation strategies.
Essential strategies to consider include:
- Early adoption of compliance frameworks: Aligning with AIDA, CPPA and other sector-specific laws to minimize disruption and legal risks
- Leveraging cybersecurity frameworks: Utilizing standards such as OWASP, NIST and ISO tailored specifically for AI risk management
- Engaging in regulatory sandboxes and pilot programs: Collaborating across sectors to innovate while maintaining oversight and shaping best practices
- Workforce education: Cultivating skills and awareness to address AI risks, ethical principles and emerging technological complexities
The takeaway
Canadian stakeholders can be global leaders in ethical, transparent and resilient AI deployment by embedding trust, security and responsible design into agentic AI from its inception.
Consulting with the appropriate advisors to support proactive engagement with evolving legislation, implementing cybersecurity best security practices and establishing meaningful collaboration with stakeholders can mitigate risks and unlock sustainable innovation.
These strategies can transcend their value as a competitive advantage and ensure that agentic AI systems serve the public good and foster economic prosperity for a future-ready Canada.
Related insights
- /insights/services/risk-fraud-cybersecurity/as-generative-ai-grows-data-security-controls-are-critical
- /insights/services/digital-transformation/ai-for-the-coo
- /insights/services/digital-transformation/ai-for-the-cio-and-cto