CMC Quarterly: AI at Work: The Leadership Imperative for 2026

By Canadian Management Centre and AMA Global

Overview

AI is now part of everyday work in most organizations, but policies, expectations, and leadership practices have not kept pace. This first edition of CMC Quarterly explores what leaders, managers, and individual contributors need to understand now, from governance and strategy to human capability and effective management in a changing workplace.

AI adoption has moved faster than most organizations expected.

Nearly 95% of organizations are now using AI in some form, and 58% are using it daily. But governance has not kept up. Managers are navigating expectations without clear direction, and employees are using tools their organizations have not been fully prepared to use well.

This first edition of CMC Quarterly looks at what that gap means in practice, and what leaders, managers, and individual contributors can do about it.

Drawing on research from Canadian Management Centre and AMA Global, with insights from 1,365 respondents across 29 countries, this issue explores three key questions:

  • How do organizations move from AI experimentation to real results?
  • What human capabilities matter most as AI becomes part of everyday work?
  • What does effective management look like when complexity is constant?

What’s Inside

The New AI Reality

AI adoption is accelerating, but many organizations are still working out how to govern it, scale it, and connect it to business outcomes. This section focuses on what leaders need to understand about strategy, alignment, and organizational readiness.

Human Capability in an AI World

As AI becomes more embedded in daily work, the skills that matter most are shifting. Critical thinking, judgment, emotional intelligence, and trust are becoming more important, not less. This section looks at how organizations can strengthen these capabilities alongside AI adoption.

Managing at the Edge of Change

Managers are dealing with more ambiguity, more pressure, and faster change. This section offers practical guidance on leading AI-supported teams, maintaining focus, and managing effectively when conditions keep shifting.

From the Research

  • 95% of organizations report using AI in some form
  • 58% use AI daily across the enterprise
  • 75% have AI implementation strategies, but only 53% have governance policies in place
  • 57% of employees still feel behind on AI, even as training expands

Want to Go Deeper?

Download the whitepaper for a closer look at the research, what it means for your organization, and where leaders should focus next.

Download the Whitepaper: AI at Work: The Leadership Imperative for 2026

© Canadian Management Centre and AMA Global

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Frequently Asked Questions

 How do you lead a team when everyone is using AI differently?

People will adopt tools at different speeds, often without clear direction. Start by setting shared expectations around how AI should be used, where human judgment is required, and what good outcomes look like. Even simple guidance helps reduce confusion and inconsistency.

 What should you do if your team is already using AI without guidelines?

Start by understanding how tools are being used today. Look for risks around quality, privacy, and inconsistency. Then introduce basic guardrails so people know what’s acceptable and where they need to be more careful. Waiting for perfect policies usually slows things down.

 What skills matter most when AI becomes part of daily work?

Technical skills help, but they are not enough. People need strong judgment, critical thinking, and communication skills to interpret AI outputs and make decisions. Trust and emotional intelligence also matter more as teams adapt to change.

 How do organizations move from testing AI to actually using it well?

Access to tools is only the starting point. Organizations need clearer strategy, stronger governance, and support for managers who are leading through change. They also need to invest in human capability so people can apply AI effectively in real work.

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