Change Management: GenAI and CDS Are Already Accepted by Clinicians

Why It Matters

Rapid clinician uptake forces health systems to rethink procurement, governance and staffing while unlocking up to 15 hours of weekly clinician time for higher‑value care.

Key Takeaways

• 28% of Canadian doctors use ambient AI scribes (2025).
• 34% adopt second‑screen CDS tools like OpenEvidence (Feb 2026).
• Clinicians download AI apps without IT approval, bypassing traditional governance.
• EMR likely shifts to record‑keeping as AI copilots become primary interface.
• Health leaders must adopt agile, bottom‑up change management for AI tools.

Pulse Analysis

Generative AI’s surge in Canadian clinics has been nothing short of meteoric. Launched commercially in late 2022, ambient scribe solutions quickly crossed the novelty threshold, with a CMA‑CFIB survey indicating 28 % physician adoption by the end of 2025. Second‑screen clinical decision‑support platforms such as OpenEvidence have followed a similar trajectory, reaching 34 % usage in February 2026. Unlike earlier digital‑health rollouts that required lengthy steering committees and enterprise‑wide pilots, clinicians are now downloading AI apps directly to their devices, often before IT departments are aware. This grassroots diffusion mirrors the spread of journal subscriptions rather than the controlled EMR module deployments of the past.

The speed of adoption reshapes the change‑management playbook. Traditional health‑IT projects spent months—sometimes years—building consensus, training super‑users, and polishing perfect workflows before go‑live. With AI tools already embedded in daily practice, the primary challenge is no longer resistance but governance at scale. Leaders must transition to an agile, bottom‑up model that monitors usage, ensures data privacy, and iterates on functionality in near real‑time. By reclaiming five to fifteen hours of clinician time each week, AI creates a new quality‑improvement frontier where the focus shifts from enforcing compliance to optimizing how that reclaimed time adds value to patient care.

Strategically, the rise of AI copilots threatens to relegate electronic medical records from the central hub of clinical work to a passive system‑of‑record. Major EMR vendors have already announced AI‑enhanced scribes, decision‑support agents, and autonomous coding assistants, acknowledging that the intelligence layer will soon dictate workflow rather than the other way around. For health systems, this means revisiting procurement contracts, investing in rapid‑prototype AI development (such as Vibe coding), and building internal expertise to compete with the eight-plus tech giants entering the space. Organizations that treat AI as a knowledge strategy—embracing iteration, user‑driven innovation, and continuous improvement—will capture the efficiency gains and maintain relevance in a landscape where the EMR is no longer the organizing principle.