Common Mistakes in Building a Customer Service AI Agent

Artificial Intelligence has become the customer service team’s biggest ally. In fact, according to Gartner, chat-based virtual agents will be the primary support technology for roughly 25% of companies worldwide by 2027. However, success hinges not only on technology but also on strategy. Enreach emphasizes the importance of having a partner who can guide the process—from planning and implementation to AI maintenance.

Good alignment between automation and customer experience

Drawing on its experience integrating AI Agents for businesses, Enreach identifies the main mistakes that are made and how to avoid them to ensure automation does not harm the customer experience:

1. Designing artificial or “IVR-like” responses: One of the most common mistakes is forcing the customer to express themselves with specific words (for example, requiring them to type or say “Inquiry” to convey their request). For the conversation to flow, the virtual agent should act like a human, use open-ended questions such as “How can I help you?” and not impose rigid terms. To get the bot to qualify intent with a single question, it’s vital to train it to detect synonyms and similar expressions.
2. Keeping the AI Agent isolated from internal systems: A bot that is not connected to the knowledge base or the company’s CRM is just an AI-powered IVR. The main purpose of introducing an AI Agent for customer service is to free agents from handling every inquiry and allow customers to resolve their questions or complete tasks at any time of day. To achieve this, it must be integrated with all tools that enable customer identification, locating shipments, changing a flight reservation, etc.
3. Not preparing the AI to escalate requests to agents: The gravest mistake is that the bot isn’t prepared to connect the customer with a human. Beyond the fact that there is no worse experience than wanting to talk to a human agent and being unable to do so, consumer protection regulations prohibit exclusive use of automated systems and require companies to guarantee access to a human operator at any point in the interaction. Therefore, the AI Agent must be able to transfer the call or chat to the best available agent and deliver the necessary context so the customer does not have to repeat information.
4. Applying AI only to customer-facing tasks: AI has many other functions in a customer service team beyond resolving external inquiries. Two of the most beneficial applications for contact centers are agent copilots and speech analytics. “With copilots to consult in real time on current prices or offers for products in your operation, agents ensure up-to-date and highly effective responses. Additionally, speech analytics provides metrics for each conversation immediately after it ends. Based on predefined parameters before implementation, the bot generates a call title and summary, evaluates agent attention, and detects the customer’s emotion, helping supervisors maintain better control of operations and team performance,” explains Iván López, AI Project Manager at Enreach.
5. Neglecting maintenance and continuous improvement: AI Agents are not a static solution. Many companies implement AI solutions thinking that once deployed, no further time and resources are needed. Although this technology is powered by machine-learning models that learn from each interaction, it will always be necessary to analyze conversations with customers, adjust responses, measure customer satisfaction, and continually update knowledge bases to achieve more precise answers.
6. Not defining a clear objective: Deploying a bot to handle customers without a clear idea of which inquiries and tasks it will resolve is too risky. To avoid wasting the investment or encouraging users to misuse the technology, we should prepare it for three key scenarios: resolve simple transactions end-to-end, escalate the conversation to agents when the customer asks (or the process requires it), and finally, detect “troll” questions to offer a standard response.
7. Choosing the wrong channels: It’s not about deploying a bot across all touchpoints (phone, web, WhatsApp, social media) without a plan, but about analyzing consumer behavior on each channel to determine whether offering immediate, around-the-clock responses helps boost conversions or reduces the volume of inquiries the team handles.

The real impact of well-implemented AI

When these mistakes are avoided and the right technology is implemented within a customer-centric strategy, AI outcomes have an immediate impact. Enreach’s internal data shows that a well-integrated AI can automate more than 50% of customer service without negatively affecting user experience.

This technology offers a dual strategic benefit for the contact center: first, it guarantees service to users who need after-hours answers or want to complete a quick transaction without waiting in line; second, it frees agents from handling every inquiry.

“The AI Agent in a contact center is not intended to replace agents but to augment the team as another member. By handling the most repetitive inquiries around the clock, it dramatically reduces wait times across all channels. It’s also important to note that AI can provide agents with up-to-date information about a product or service and assist in operational decisions related to quality and service levels,” concludes Iván López, AI Project Manager at Enreach.