In recent months, a study conducted by Yale's Chief Executive Leadership Institute highlighted critical insights regarding the deployment of Agentic AI across various industries. The analysis emphasized a proximity framework which illustrates the importance of understanding customer interactions with AI systems. The key component of the study is the categorization of AI deployments based on their proximity to the customer: direct-proximity, mediated-proximity, and background-proximity. Each category presents distinct risks and benefits, and the framework advises firms to deploy AI carefully, particularly regarding how close the AI can interact with customers. The findings underscore that errors in AI deployments may not be immediately obvious to consumers. Instead, they surface later as churn data or complaints, potentially damaging long-term trust between a business and its customers. This risk is exacerbated when AI is set to operate in contexts where customers are inadequately equipped to handle potential failures. Such failures, felt most acutely in direct-proximity interactions where customers are aware they are dealing with AI, can lead to frustration and adversarial relationships with human representatives. Additionally, the analysis points out that successful deployments of Agentic AI require a balance. Businesses should maximize automation where it can effectively enhance customer experience while ensuring that they maintain clear governance and oversight structures. Maintaining a clear distinction between tasks performed by AI systems and those carried out by human employees is crucial to mitigate risks of customer dissatisfaction and ensure transparency in decision-making processes. The insights from various senior technology leaders across 13 industries helped in establishing this framework, emphasizing that the right pace of deployment is nearly as critical as the right place. In essence, the strategic recommendations derived from the proximity framework advocate for a cautious approach, pushing organizations to prioritize deployment where the AI interaction remains invisible to customers. The research makes clear: the firms that will thrive are those who can discern how close to engage their AI systems while retaining a focus on the human aspect of customer interactions. By ensuring that customers are not left to navigate failures independently, businesses can foster a more trusting relationship, ultimately leading to higher customer retention and satisfaction rates.