The transformation driven by artificial intelligence in sales and customer service is less of a futuristic promise and more of an operational reality that is repositioning roles, metrics, and expectations within companies. The accelerated adoption of generative models and conversational solutions has enabled the automation of routine tasks, freeing up time for human teams to handle complex cases while simultaneously enhancing the personalization of interactions at scale—a phenomenon that has already led to the widespread use of AI by sales and service desk departments.
In practice, trends converge around several clear vectors: next-generation virtual assistants, AI-augmented agent workflows, predictive personalization, and knowledge models that combine search with answer generation. Traditional chatbots are being replaced by agents based on generative models integrated with corporate knowledge bases via Retrieval-Augmented Generation (RAG) techniques, which retrieve relevant documents and use these excerpts to generate more accurate and less hallucination-prone responses.
From a commercial standpoint, AI is reshaping the sales funnel by supporting automated prospecting, lead prioritization, proposal generation, and the preparation of tailored pitches for each customer. Tools that analyze real-time signals—such as browsing behavior, purchase history, and interactions across digital channels—now suggest approaches and even negotiation scripts for salespeople, increasing the efficiency of the sales cycle.
The direct influence of AI on purchasing behavior is also noticeable: during promotional periods and seasonal peaks, digital tools and assistants have boosted online sales and altered conversion and return patterns. Salesforce data indicated increases in chatbot usage rates by consumers and a growing share of purchasing decisions influenced by AI-generated recommendations, reinforcing the need to integrate service and sales models with e-commerce and CRM layers to close the value chain. At the same time, these gains bring operational challenges, such as increased returns in certain segments and the need to adjust logistics and post-sale policies in the face of higher volumes and AI-facilitated purchasing behaviors.
However, many organizations have invested heavily in GenAI pilots and still report difficulties in turning projects into sustainable value, whether due to data quality issues, lack of integration with legacy IT systems, or gaps in governance and internal competencies.
Looking ahead, the companies that thrive will be those that know how to delegate repetitive and scalable work to AI without sacrificing human interaction in moments of high sensitivity. Winning strategies will combine RAG models for response accuracy, robust data pipelines to fuel personalization, and upskilling programs for salespeople and agents, so that people and machines operate as a cohesive team. By 2025, selling and servicing will no longer be just a debate about technology but a strategic exercise in organizational architecture, where AI serves as a lever for efficiency, innovation, and—when well-governed—sustainable competitive advantage.
*Thiago Hortolan is CEO of Tech Rocket, a spin-off of Sales Rocket dedicated to creating Revenue Tech solutions, combining Artificial Intelligence, automation, and data intelligence to scale the entire sales journey from prospecting to loyalty. Its AI agents, predictive models, and automated integrations transform commercial operations into an engine of continuous, intelligent, and measurable growth.
