Edition 01 | Where AI strategy becomes leadership advantage

AIDA is dead. The governance vacuum is real. And most leaders don’t yet understand what that means.

In an era of constant AI noise, leaders don’t need more information—they need clarity.

The Situation

On January 6, 2025, Canada’s most ambitious attempt at AI regulation ended. The prorogation of Parliament terminated Bill C-27 and the Artificial Intelligence and Data Act (AIDA) before they became law, ending three years of legislative effort.

Currently, Canada has no federal AI law in force, not even a draft or interim measure.

Organizations are deploying AI in customer service, credit adjudication, hiring, and operations. AI is writing code, summarizing legal documents, and informing clinical decisions, yet there is no binding federal framework governing these activities.

The absence of law does not eliminate risk; it removes clarity. In this environment, each leader is responsible for making governance decisions independently.

Why This Matters

Many leaders interpret regulatory silence as permission, but it actually increases risk exposure.

In the absence of AIDA, existing privacy legislation under PIPEDA, human rights law, employment standards, and consumer protection frameworks still apply. While none were designed for AI, all will be enforced when issues arise.

Ontario’s Bill 194 now regulates the use of AI in the public sector, including hospitals, schools, and law enforcement. It passed in six months, demonstrating that provincial regulation is advancing more quickly than federal efforts. This patchwork now defines your compliance landscape.

The EU AI Act is now in force, and global partners are establishing interoperability requirements. If your organization operates internationally or collaborates with such partners, the lack of a Canadian framework does not exempt you from global obligations.

The Leadership Implication

The core issue is that most organizations are waiting for regulation to define effective AI governance. This approach is risky, especially in the current regulatory vacuum.

Organizations that develop internal governance frameworks proactively will gain a genuine advantage. They do so not only for regulatory compliance, but to meet the expectations of customers, employees, and boards.

Voluntary codes of conduct and Treasury Board guidelines for the federal public sector are available. Sector-specific guidance from OSFI and others is evolving. Leaders who integrate these resources into organizational practice are not waiting for future legislation.

They are now establishing strong governance practices.

What Leaders Should Do Now

1. Audit your current AI use cases against existing laws, rather than anticipated regulations. PIPEDA, human rights legislation, and sector-specific rules apply today. Assess your exposure proactively, rather than waiting for regulatory or legal action.
2. Assign ownership of AI governance internally. Assign this responsibility to a cross-functional group with a clear mandate, designated chair, and direct reporting line to leadership. Governance requires accountability, not just documentation.
3. Watch for the next federal bill—it is coming. A future government will likely reintroduce AI legislation, separate from privacy reform. Organizations with established frameworks will adapt quickly, while those without will face significant delays.

Does your organization have a designated owner for AI governance decisions, or is accountability still dispersed across teams without clear responsibility?

One Resource Worth Your Time

The Schwartz Reisman Institute’s analysis, “What’s Next After AIDA?”, provides a clear summary of Canada’s AI governance landscape following the bill’s collapse, including provincial regulation, federal alternatives, and future directions.

It is a valuable resource to review before your next AI strategy discussion.

Closing

AI is not a technology race. It is a decision-making advantage.

The winners in AI won’t have better models. They’ll have better discipline.

Execution—not experimentation—will define the next phase of AI.

Dwayne D. Taylor, Senior Manager, Data Product Excellence & Innovation — Scotiabank MBA (AI Leadership), completing 2026 Publisher, Taylect: AI Leadership Brief

The views expressed are my own and do not reflect those of my employer.