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The discussion began by highlighting a reality that is often underestimated: the adoption of AI does not depend solely on the quality of the tools. It also depends on the trust that organisations manage to build around these applications.
The study conducted by ChooseMyCompany in partnership with RSB, involving over 13,000 respondents, shows that AI is already widely present in everyday working life. Seven out of ten people say they use it in their professional lives, in one form or another. Perceptions are generally positive: a majority believe that AI can have a positive impact on their profession and create value for their company.
But this confidence remains fragile. More than six in ten respondents say they do not feel sufficiently supported in using generative AI at work. In certain sectors or groups, this figure can reach 80%. In other words, employees do not reject AI; they are asking to understand it better, to be trained, reassured and involved in its integration.
One of the most interesting findings of the study concerns the link between AI and engagement. Employees who use AI report feeling more confident about their professional future, more motivated, better able to see themselves in their organisation’s future, and more likely to recommend their company.
This finding suggests moving beyond a defensive view of AI, often associated with fears of job displacement or dehumanisation. When made accessible, explained and integrated into practices, AI can become a driver of learning, employability and collective confidence.
For Celica Tellier, the most advanced companies share three key practices. Firstly, leaders use AI themselves and state this clearly. They demonstrate how it benefits them, but also what they choose not to delegate to it. Secondly, they ensure no one is left behind, including non-technical roles and frontline teams. Finally, they create spaces for experimentation: workshops, AI-dedicated weeks, internal ambassadors or concrete use cases generated by the teams.
Shing Gan offered a complementary perspective by introducing the concept of the corporate AI narrative, that is, the way in which leaders explain how AI creates business value. For him, the AI narrative is not merely a communication exercise: it can become a strategic resource.
In a world where every company claims to “do AI”, differentiation no longer comes solely from technology, but from the credibility of the narrative. Investors, customers, analysts and employees no longer simply ask whether the company uses AI. They seek to know whether its narrative is clear, consistent, aligned with its actual resources and backed by evidence.
Four dimensions underpin this credibility: the clarity of the message, consistency over time and across leadership, the alignment between AI ambition and the company’s actual capabilities, and the avoidance of AI washing. A company that promises too much, without concrete evidence, risks undermining its reputation rather than strengthening its position.
To build lasting trust, organisations must go beyond marketing messages. They need a genuine AI communication system, capable of translating technical capabilities into understandable business outcomes.
This involves developing the ability to bridge the gap between technical language and business challenges, creating a shared narrative playbook for executives, tech teams, finance, HR, legal and business units, and establishing a framework for evidence governance. Before claiming that an AI application improves productivity, reduces costs or transforms the customer experience, the company must be able to rely on data, pilot schemes, measurable results or control mechanisms.
This requirement is all the more important given that transparency regarding decisions is a major factor in engagement. If employees do not understand why and how AI is being deployed, they risk perceiving the transformation as a top-down, opaque or threatening decision.
AI does not automatically create trust. It can even have the opposite effect if it is presented in an excessive, vague manner or disconnected from the reality on the ground. To become a sustainable driver of transformation, it must be accompanied by a clear narrative, robust governance and a genuine effort towards collective ownership.
Trust is built when the company can explain what it is doing with AI, why it is doing it, what limits it sets itself and what value it seeks to create for its employees, customers and ecosystem.
