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AI Adoption

Where Canadian organizations actually are on AI readiness in 2026

By CSBAA Editorial Team6 min read

Observations from CSBAA training cohorts and member conversations: foundational AI literacy is spreading quickly, but governance and advanced capability remain the weak layers in most organizations.

What We See in Training Rooms

This piece reflects what we observe across CSBAA training cohorts and member conversations — it is a practitioner's view, not a formal study. The clearest pattern of the past eighteen months is that basic AI literacy is no longer rare. Most cohorts now start with participants who already use AI tools in some part of their work, particularly in administrative, communications, and customer-facing roles. The question organizations bring to us has shifted from "should we use these tools?" to "how do we use them consistently, safely, and well?"

Governance Is Still the Weak Layer

Tool adoption is running well ahead of policy. In our experience, most organizations arriving at training have no written AI use policy, no assigned accountability for AI oversight, and no shared answer to basic questions like what data may be pasted into which tools. This gap creates real risk exposure, and it also quietly limits adoption: employees who are unsure what is allowed tend to either avoid the tools or use them without telling anyone. Both outcomes are bad.

Advanced Capability Is Concentrated

Workflow automation, agent-style tooling, and transformation planning remain concentrated in a small subset of organizations — usually those that have invested in structured, progressive training rather than one-off sessions. Teams that complete multiple levels of a certification pathway tend to keep building afterward; teams that attend a single demo session tend to plateau. Structure and progression appear to matter more than any particular tool choice.

Where to Invest Next

Our standing recommendation to members has three parts: put a baseline AI use policy in place before expanding tool access; fund cohort-based training for team leads and operational staff rather than relying on self-directed learning; and name an internal AI champion with real accountability for capability development. Organizations that do these three things consistently outpace those that treat AI adoption as a procurement decision.

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