increase AI adoption is a business and workforce issue before it is a technology metric. This article gives leaders a direct answer, shows what to examine in daily work, and turns the issue into practical decisions.
The recommendations apply to Canadian organizations of different sizes. The right controls and pace will still depend on the use case, affected people, sector, data, and possible harm.
Table of contents
- Begin with work that matters
- Design with users
- Make approved use easy
- Build role-specific confidence
- Equip managers
- Remove workflow friction
- Measure sustained value
- Practical checklist
- Frequently asked questions
- References
“People adopt AI when it makes important work better and the organization makes responsible use easier than unsafe improvisation.”
Mehrzad Verdizadegan,
CEO, Praevion Consulting Inc.
Begin with work that matters
To increase AI adoption, start with a repeated problem users already want solved. Establish the current cycle time, quality, rework, cost, or service result.
A clever tool attached to an unimportant task creates curiosity, not sustained use.
Design with users
Observe the current workflow and involve employees in the future design. Test handoffs, exceptions, approvals, and the effort needed to verify output.
Users often see problems that a project team misses. Their involvement also makes the reason for change more credible.
Make approved use easy
Provide secure access, usable guidance, good integration, and prompt support. When responsible use is slow or confusing, shadow tools become attractive.
Canada’s AI Strategy for the Federal Public Service 2025-2027 connects responsible adoption with secure access and capability.
Build role-specific confidence
Teach people how to use the approved system, check important outputs, protect information, document material use, and escalate faults.
Practice with real cases. Completion data shows attendance; observed work shows whether a person can act safely.
Equip managers
Local managers translate enterprise policy into workload, priorities, coaching, and performance expectations. They need early involvement and direct support.
Ask managers to review quality and behaviour, not simply encourage more usage.
Remove workflow friction
Measure duplicate entry, extra checking, unclear approval, slow access, and failed integrations. Fix the process around the tool.
A technically strong model will still be rejected if the total job becomes harder.
Measure sustained value
Track eligible users, appropriate frequency, workflow coverage, proficiency, quality, rework, incidents, and business results.
Segment the data. High login counts may hide shallow use, while rare use can be valuable in a specialist workflow.
increase AI adoption checklist
- Name the business outcome, current baseline, target, and accountable owner.
- Map the affected workflow, roles, users, decisions, and possible harm.
- Use real user evidence to separate value, skill, trust, access, and process barriers.
- Provide approved tools, role-based learning, manager support, and clear safeguards.
- Measure suitable use together with workflow results, total cost, and risk.
- Advance, revise, pause, or stop based on evidence rather than enthusiasm.
Related Praevion guidance
- Read the related Praevion knowledge-hub guide
- Explore the next related article
- Explore Praevion Consulting Inc. digital transformation services
Frequently asked questions
What is the fastest way to improve adoption?
Fix one valuable workflow with a willing user group, visible manager support, and rapid feedback.
Does training guarantee adoption?
No. Training cannot overcome poor value, weak access, bad workflow design, or unclear accountability.
Should leaders reward AI use?
Reward better outcomes and responsible practice, not tool use by itself.
Executive takeaway
How Do You Increase AI Adoption? The practical answer is to connect adoption to useful work, prepare people honestly, make responsible use easy, and review value with risk. A launch is only the beginning. Sustained adoption appears when the new workflow works better and people know how to use it well.
To discuss your needs, contact Praevion Consulting Inc..
References
- Statistics Canada, Analysis on artificial intelligence use by businesses in Canada, second quarter of 2026
- OECD, Skills in the AI Age, 2026
- Government of Canada, AI Strategy for the Federal Public Service 2025-2027
- NIST, Artificial Intelligence Risk Management Framework
- ISO/IEC 42001:2023, AI management systems
