{"id":23387,"date":"2026-08-19T13:47:42","date_gmt":"2026-08-19T13:47:42","guid":{"rendered":"https:\/\/io4rh.com\/?p=23387"},"modified":"2026-08-21T14:37:09","modified_gmt":"2026-08-21T14:37:09","slug":"successful-ai-transformation-the-role-of-people-and-leadership","status":"publish","type":"post","link":"https:\/\/io4rh.com\/en\/blogue\/successful-ai-transformation-the-role-of-people-and-leadership\/","title":{"rendered":"Successful AI Transformation: The Role of People and Leadership"},"content":{"rendered":"\t\t
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\n\t\t\t\t\tSucceeding in Your AI Transformation: What If the Real Challenge Isn't Artificial Intelligence?\t\t\t<\/h1>\n\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Artificial intelligence (AI) is now at the heart of organizational transformation. Companies are investing heavily in new tools, launching more pilot projects, and accelerating their AI adoption initiatives. Yet, despite this enthusiasm, one question remains: Why do so many organizations still struggle to turn AI into real value creation?<\/div>
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The latest data from KPMG in Canada reveals a striking paradox.<\/div>
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Today, 93% of Canadian organizations report having adopted generative AI. Yet only 31% say they have fully integrated it into their operations and workflows. Even more surprising, only 2% report a measurable return on their AI investments.<\/div>
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In other words, the adoption of artificial intelligence is progressing rapidly. Value creation, however, is lagging far behind.<\/div>
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The challenge, therefore, is no longer whether organizations will use AI. The real challenge is understanding how to successfully navigate the AI transformation and how to create the conditions necessary to fully leverage it.<\/div>
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In this blog post, Karine Bergeron<\/a>, an industrial psychologist, draws on her expertise in occupational psychology to examine the specific impact of artificial intelligence on individuals, teams, and organizations.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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The Technological Reflex: Investing More in AI\u00a0<\/strong><\/h5>\n
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Faced with this reality, the reaction is often the same: invest more.<\/div>\n
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More tools. More platforms. More technical training.<\/div>\n
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These investments are significant. But they rest on an implicit assumption: if results are slow to materialize, it\u2019s probably because the technology isn\u2019t yet advanced enough or widely deployed.<\/div>\n
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However, if the problem were purely technological, the massive investments made over the past several years should already be generating more value. That\u2019s not what the data shows. This reality therefore compels us to look beyond technology and focus on a factor that is often underestimated: the human element.<\/div>\n<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The True Bridge Between AI and Value Creation<\/strong><\/h5>\n
AI doesn\u2019t just transform tools. It transforms work itself. It changes the way decisions are made. It redefines roles. It shifts performance expectations. It transforms our relationship with expertise. And as work changes, the human skills and abilities needed to perform well must evolve as well.<\/div>\n
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Technology is necessary. But it is not sufficient. Value is not created by technology alone. It is created when people develop the capabilities needed to integrate this technology into their way of working. The true bridge between artificial intelligence and value creation is therefore the development of human capabilities.<\/div>\n
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That is why a successful AI transformation cannot rely solely on the deployment of new tools. It must also be underpinned by a genuine organizational and human transformation.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The 4 Human Transformations of the Age of Artificial Intelligence<\/strong><\/h5>\n
When a technology transforms only the tools, people must learn to use new ones. When a technology transforms work itself, they must learn to operate differently. This is exactly what AI is bringing about.<\/div>\n
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Rather than offering generic training, a development plan tailored to an employee\u2019s profile can help identify the support that will have the greatest potential impact on that individual.<\/div>\n
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This type of approach is more motivating for employees, who feel that their specific needs are being addressed while also meeting the job\u2019s requirements.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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1. A cognitive transformation<\/strong><\/p>

Responses are instantaneous. Information is abundant. Recommendations are generated in a matter of seconds. Yet our abilities to think critically, exercise judgment, and use discernment do not automatically keep pace. The challenge is no longer access to information. The challenge now lies in the quality of reasoning and the ability to evaluate, question, and contextualize the information produced by AI.<\/p>

2. An Identity Tranformation<\/strong><\/p>

For a long time, expertise was one of the main sources of value for professionals. Today, some of this expertise can be generated or enhanced by AI. This raises a fundamental question: What still defines a competent professional when access to knowledge becomes nearly universal? Individuals must redefine their contribution, their value, and their professional identity. The AI transformation therefore requires us to rethink what constitutes the value of a role, expertise, and human contribution.<\/p>

3. A Behavioral Transformation<\/strong><\/p>

The presence of AI does not guarantee its use. Some people quickly embrace these tools. Others avoid them. Still others use them only superficially. The challenge, therefore, is not just technological. It is also behavioral and organizational.<\/div>
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To successfully adopt AI in the workplace, organizations must create an environment that fosters experimentation, learning, and the gradual integration of these new ways of working.<\/div>
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4. A Transformation in Relashionships<\/strong><\/p>

AI is also transforming the mechanisms of trust. How can we assess the credibility of a machine-generated response? How can we maintain trust among colleagues, managers, experts, and clients when expertise becomes harder to observe? How do we know when to trust AI and when to trust our own judgment? Relational dynamics must also evolve. In this context, trust, transparency, and the ability to engage in dialogue become essential drivers of organizational transformation.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Why Leadership is Becoming Central to the Transformation of AI<\/strong><\/h5>
These transformations are creating new human tensions.<\/div>
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And these tensions will not disappear with more technology.<\/div>
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They require new leadership and change management skills.<\/div>
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Leaders must now help their teams to:<\/div>
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