Canada's Agentic AI Guidance for Responsible Scaling

Something has shifted in conversations with Canadian CIOs this year. Six months ago, the question was "should we invest in agentic AI?" Today, the question is "why are we moving so slow?" The intent is there, and the board pressure is present. What's missing is the foundation. Here are the key points being discussed: - Agents are being piloted on top of fragmented, inconsistent data. - Teams are moving quickly on AI tooling but not on the integration layer underneath it. - Governance and compliance (OSFI, Law 25) are being treated as a phase 2 problem, creating real risk. Enterprises making significant progress share one commonality: they addressed the data foundation first, not after the pilot, but before it. Agentic AI isn't waiting for anyone to be ready. The time to build that foundation is now. Are you observing similar trends? Happy to connect and exchange insights. #AgenticAI #CanadianEnterprises #AIReadiness

𝗧𝗵𝗲 𝗔𝗜 𝗿𝗲𝗴𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗱𝗲𝗯𝗮𝘁𝗲 𝗶𝘀 𝗻𝗼𝘁 𝗮 𝗽𝗼𝗹𝗶𝗰𝘆 𝗱𝗶𝘀𝗰𝘂𝘀𝘀𝗶𝗼𝗻. 𝗜𝘁 𝗶𝘀 𝗮 𝗸𝗻𝗶𝗳𝗲 𝗳𝗶𝗴𝗵𝘁. Seriously Risky Business just published a breakdown of the real positions behind the rhetoric. The divide is about who gets to decide what AI systems are allowed to exist. One camp wants pre-deployment testing and red lines enforced before models ship. The other camp wants ex-post liability and market accountability after harm occurs. Both sides claim they are protecting the public. Both sides frame their position as the only way to balance safety and innovation. The infrastructure layer does not wait for this fight to resolve. Data centers are being built. Chips are being deployed. Sovereign AI programs are launching in countries that will not adopt California's rulebook. Over 60 nations have published formal AI strategies. Approximately 30 have committed specific funding to build domestic AI capabilities. France announced €109 billion in AI investments. UAE and Japan are leading sovereign compute buildouts. The regulatory debate assumes AI development happens in a jurisdiction that can enforce rules. That assumption is outdated. The supply chain is global, the compute is distributed, and the models are trained wherever power and capital intersect. Ex-post liability creates compliance overhead that only the largest incumbents can absorb. Both frameworks advantage entrenched players. That much is documented. The real question is not which regulatory model wins. It is whether the U.S. can field a framework fast enough to matter before the infrastructure decisions are already locked in. Click here to subscribe to The Hirsch Report: https://lnkd.in/gyzanhxn Source Article: https://lnkd.in/gQ5fK5gV #AI #Regulation #Policy #AIInfrastructure #Semiconductors #DataCenter #HirschReport #DeepFactChecked

Carney announces refreshed national AI strategy will be released next week | CBC News Canada's much-anticipated refreshed national AI strategy is set to be unveiled next week by Prime Minister Mark Carney. This strategy, built on six pivotal pillars, will outline the federal government's vision for AI, focusing on safeguarding democracy, empowering Canadians, scaling champions, and fostering international partnerships. It also emphasizes equipping all Canadians with access to AI education, modernizing privacy laws, and bolstering AI safety capabilities. Provinces are also making independent moves on AI, such as bans on AI chatbots for minors, while the federal government partners with companies like Telus to advance sovereign AI infrastructure. With ambitions of making Canada a global leader in AI, this strategy seeks to elevate both the technology and its talent pool. Learn more at: https://lnkd.in/dih9fVt6 What are your thoughts on this? Don't hesitate to share your thoughts and ideas in the comments below. devtech.pro is always eager to hear from our community and learn about your experiences and perspectives. Looking forward to connecting with you! #devtech.pro #AI #technology #trending #news #innovation #technology This article is written and published by Doki. Doki is our documentation's and social media's AI Agent.

This morning I had the opportunity to meet and express my thoughts to UK Parliamentary Under-Secretary of State and minister for AI and Online Safety, Kanishka Narayan MP, a former banker, a brilliant man and an expert in AI. He is the UK counterpart to our own federal minister, Andrew Charlton. He is currently visiting Australia to meet with the Australian Federal Government to sign a new Memorandum of Understanding (MoU) which focused on the responsible development, deployment, governance and use of safe and trustworthy AI. Hearing firsthand how the UK Government and leading UK organisations are approaching AI strategy and implementation was something worth listening to. He was also very open to our views and opinions on the same topic. Our roundtable covered not only the opportunities AI presents for productivity, innovation and service transformation, but also the importance of governance frameworks, ethical deployment, sovereignty, cybersecurity considerations and the all important maintaining public trust. Thank you Paul Nicolaou and business Sydney for making Liberty IT Consulting Group a participant to such important discussion. For Liberty, this reinforces several important themes we have been discussing for some time. - We have earned our seat at the AI table. - AI is no longer an experimental side topic. It is becoming a horizontal capability that will impact every industry, every government, every business function and every technology transformation initiative. - The conversation has clearly shifted from “if” organisations adopt AI, to “how” they adopt it safely, responsibly and effectively. Bear in mind in Australia we’re lagging in AI adoption by a long mile, whilst momentum globally is accelerating at never before seen pace. As a technology business, we continue investing in our understanding of AI trends, governance models, enterprise use cases, data readiness and practical implementation approaches for the benefit of our clients and our people. #AI #UKAUS Anne-Marie Paterson Tanya Kunze Craig Saphin Nur Oyman GAICD James Bouzios

The UK government just announced an £11M AI Assurance Innovation Fund. Here's why that matters more than the headline suggests. This isn't just funding. It's a signal. The UK is building an entire AI assurance profession — backed by a government consortium, industry standards, and real money. What this tells us: AI assurance is becoming a distinct discipline, not just a subset of data governance The UK wants to lead on assurance as its competitive advantage vs. the EU's regulation-first approach Organisations that invest in AI assurance now are positioning themselves ahead of the curve The demand for qualified AI assurance professionals is about to accelerate — fast. If you're in risk, compliance, security, or governance, pay attention. This is your field expanding. And if you're a business leader, understand this: the government is investing because they know the market needs it. Your organisation probably does too. #AIAssurance #UKGov #AIPolicy #ArtificialIntelligence #AIGovernance

Integrity AI 2.0™ — EU AI Act Alignment Governance makes it safe. RHITL™ makes it human. EU Requirement → Integrity AI 2.0 Solution High‑Risk AI Governance Strict rules for AI in healthcare and infrastructure. → Chain‑as‑Enforcer: Every decision is logged on an immutable ledger. Governance is the core, not a plugin. Data Sovereignty & Privacy Protecting citizens’ sensitive data from unauthorized access. → Air gapped Fingerprint Nodes: Data never leaves the local jurisdiction. →Proprietary dynamic API = “Zero‑Leak/ Zero-Trust” integrity. Human Oversight (Art. 14) AI must be designed to be overseen by natural persons. → RHITL™ Framework: The “No Pass Zone” ensures the human expert is the final authority before any data is committed. Transparency & Bias Models must be explainable and free from systemic bias. → Local‑Data Training: Using local data eliminates the “imported bias” of global models. → Hybrid‑Capable: Sovereign Core first — external LLM outreach only under governed conditions, with your fingerprinted rules sealed against GIGO contamination. Your system, your rules. @European Commission Sovereign & Safe. Veracity, Fidelity, Governance, Humanity **DM COMPLIANT for consult to pilot. Limited to 3 new consults positions** #IntergrityAI #Compliantbydesign #EUAIACT

Canada has outlined six pillars for its national AI strategy: protecting Canadians and safeguarding democracy, empowering Canadians, powering AI adoption for shared prosperity, building a sovereign AI foundation, scaling Canadian champions, and forging trusted global partnerships. CBC coverage: https://lnkd.in/eui8T_HJ Across all six, one word is implicit: trust. But trust in AI is not a value statement. It is an infrastructure requirement. It means knowing what your AI is doing, how it is doing it, what it is allowed to access, whether it is operating within policy, and whether its outputs can withstand scrutiny. At CharliAI, we have been building that infrastructure since 2020: a Governance Control Plane for accountable, traceable, and auditable AI deployment in regulated financial services. For financial institutions, regulators, government, and institutional investors, trust means more than confidence. It means evidence. Evidence that AI systems are operating within defined controls, aligned to regulation, and producing outcomes that can be reviewed, challenged, and defended. As Canada moves from AI strategy to implementation, advantage will go to those who operationalize AI governance now. For financial institutions, that means treating AI governance as foundational infrastructure, not downstream compliance. For regulators, it means translating principles into enforceable standards for control, transparency, and auditability. For investors, it means evaluating AI governance as a core driver of enterprise value and risk. Canada is ready to lead in AI. But sovereignty will depend on trust that can be built, measured, and proven. The six pillars define the “what.” Charli delivers the “how.” Richard A. Moran, Sharon Castelino, Alyssa Barry, CPIR, Carine Schneider, FGE, Joel Emery, Kevin Collins #AIGovernance #NationalAIStrategy #CanadianAI #ResponsibleAI #AIInfrastructure #FinancialServices #RegTech #CharliAI

Canada has released its new Guide on the Use of Agentic Artificial Intelligence. As these systems become more capable, the new guidance outlines how to use them safely and responsibly. https://lnkd.in/enJQTzyi

Every Australian business is about to face the same question. How are you governing your AI? Not "are you using AI." That ship has sailed. Most organisations already are. The question now is whether you can evidence it. Document it. Defend it. And here is the exciting part 👉 the businesses that get this right first will have the biggest advantage. Australia's mandatory AI guardrails for high risk applications are coming into effect by Q4 2026. The EU AI Act is already enforcing. The AI Safety Commissioner's office is being stood up as we speak. This is not something to fear. This is an opportunity. Think about it this way: ✅ Companies with strong governance will win enterprise contracts ✅ They will attract better talent who want to work ethically ✅ They will build customer trust that competitors cannot replicate ✅ They will be ready when regulators come knocking, not scrambling The organisations treating governance as a competitive advantage, not a compliance burden, are the ones that will lead the next decade. At 1NDYGO AI we have been building for this exact moment. Our platform 1NTEGRAGUARD helps organisations assess, monitor and manage their AI risks, aligned to ISO/IEC 42001 and built specifically for the Australian regulatory landscape. Because governance should be baked in, not bolted on. If your organisation is using AI in hiring, lending, healthcare, education or critical infrastructure, the clock is ticking. But that is a good thing. It means the bar is being raised for everyone. The businesses that move now will set the standard. Will yours be one of them? 🇦🇺🚀 #AIGovernance #ResponsibleAI #AustralianBusiness #1NTEGRAGUARD #ISO42001

Responsible AI in government is not achieved through technology alone. It is achieved through principles, governance, and accountability embedded into every stage of delivery. Designing and implementing AI solutions in government settings requires careful consideration across eight critical areas: 1. Human, societal and environmental wellbeing 2. Human centered values 3. Fairness 4. Privacy protection and security 5. Reliability and safety 6. Transparency and explainability 7. Contestability 8. Accountability These principles are not theoretical. They directly influence how AI systems are designed, governed, deployed, monitored, and trusted. For AI to operate responsibly in government environments, the entire chain must be visible and auditable: * Data sources and quality * Data transformation processes * Model inference and decision pathways * Human oversight and intervention * Predictable and explainable outputs * Accountability for outcomes #ResponsibleAI #Government #ArtificialIntelligence #Governance #PublicSector #EnterpriseAI #DigitalTransformation