Winter 2027 Facilitation Certification Deadline January 1st
Winter 2027 Facilitation Certification Deadline January 1st
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AI | September 25, 2026

Why do so many AI retraining programs fail to create lasting workforce change? This article explores why individual skills and credentials are not the real bottleneck in AI adoption, and why team operating models matter more. Learn how organizations can move beyond classroom-based AI training by embedding AI into real work, redesigning roles and decision-making, and building judgment through practice, feedback, and reflection. Discover why successful AI workforce transformation requires team-level capability building, new working agreements, and organizational change that helps people work differently with AI, not simply learn new tools.

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AI | September 18, 2026

Cutting headcount may create short-term budget room, but it does not guarantee stronger returns from AI. Research on autonomous business shows that organizations seeing the greatest ROI are investing not just in technology, but in the people, skills, roles, and operating models needed to guide and govern it. This article explores why cost cutting alone fails as an AI investment strategy, how automation can quietly erode the development of human judgment, and what organizations can do differently. Learn why redesigning roles, preserving developmental work, and treating human capability as infrastructure are essential to building an autonomous business that can scale and succeed.

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AI | September 11, 2026

AI can now create strategy decks, journey maps, and other polished deliverables in minutes, but faster execution does not automatically create alignment. As AI makes artifacts cheaper and more abundant, the real value shifts to the shared understanding behind the work. Explore why AI-generated deliverables often fail to drive meaningful action, how collaborative processes build the context and commitment teams need, and why facilitation, conversation, and human alignment are becoming even more critical as AI accelerates organizational workflows.

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AI | August 21, 2026

AI transformation is often measured by how much friction it removes, but not every obstacle in the workplace is waste. Some friction creates opportunities for judgment, mentorship, collaboration, and the development of critical leadership skills. Explore why leaders need to look beyond speed and efficiency when redesigning work with AI, how removing too much productive friction can weaken teams over time, and what organizations can do to preserve the human interactions that build expertise, strengthen decision-making, and prepare the next generation of leaders in an AI-enabled workplace.

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AI | August 3, 2026

As AI rapidly transforms how work gets done, one leadership skill is becoming more valuable than ever: facilitation. While AI can accelerate execution, it cannot replace the human ability to align teams, navigate complexity, build trust, and guide better decisions. Organizations that invest in facilitation create leaders who can turn diverse perspectives into meaningful action, foster collaboration, and unlock the full value of AI. Discover why facilitation is emerging as the defining leadership competency for the AI era and how it empowers teams to thrive through constant change, innovation, and increasingly complex challenges.

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AI | June 19, 2026

AI governance is no longer theoretical. Recent cases involving Air Canada's chatbot and iTutorGroup's AI recruiting system show that organizations, not AI tools, are legally accountable for AI-generated outcomes. This article explores what these landmark cases reveal about AI liability, governance failures, and the risks of deploying AI without human oversight. Learn why monitoring, data quality, human review, and cross-functional decision-making are essential for responsible AI implementation. Discover four practical governance patterns that help organizations reduce risk, improve accountability, and build AI systems that are both innovative and defensible.

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AI | June 12, 2026

AI is quietly reshaping the workforce in ways most leaders aren’t measuring. While concerns often focus on entry-level job loss, the bigger risk is the erosion of apprenticeship and skill development. Drawing on research from Cornell, MIT, Yale, Microsoft, and real-world examples from organizations adopting generative AI, this article explores how “AI chains” remove the learning experiences that turn juniors into future experts. Learn why experience starvation threatens leadership pipelines, how hidden AI adoption creates governance blind spots, and what organizations can do to preserve mentorship, judgment, and long-term capability while still capturing AI-driven productivity gains.

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AI | May 15, 2026

Organizations are no longer debating whether AI matters. They are being pulled into two very different futures. This post explores the growing divide between companies investing heavily in AI infrastructure and automation, and those focusing on the human capabilities required to make AI actually work inside organizations. Drawing from nearly a decade of experience in facilitation and AI transformation, it examines why trust, decision-making, collaboration, and organizational adaptability are becoming the real differentiators in the age of AI. A thought-provoking look at the widening gap between technological acceleration and human readiness, and why the middle ground is quickly disappearing.

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AI | May 8, 2026

Most organizations are investing heavily in AI adoption but seeing little return because traditional training models fail to create lasting behavior change. Research from organizations like Gartner and Anthropic reveals that employees quickly forget one-time AI training and struggle to integrate AI into daily workflows. While licenses and training programs increase, real usage and collaboration remain low. This article explores why AI adoption is a design problem rather than a training problem, highlighting emerging research, behavioral insights, and a new three-part framework that helps organizations build true AI fluency through practice, iteration, and collaborative ways of working.

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AI | May 1, 2026

“Collaborative AI” is one of the most overused terms of 2026, often stretched to describe everything from multi-agent systems to solo prompting in tools like ChatGPT. This ambiguity hides what actually matters: how teams work together with AI in real-world settings. This piece cuts through the noise, challenging shallow definitions and offering a practical, experience-based perspective. Learn the difference between agent-to-agent workflows, individual AI use, and true team collaboration with AI—and why only one of these reflects the meaningful shift happening inside organizations today.