{"id":54714,"date":"2025-07-08T08:23:30","date_gmt":"2025-07-08T06:23:30","guid":{"rendered":"https:\/\/enreach.es\/?p=54714"},"modified":"2025-07-08T13:36:51","modified_gmt":"2025-07-08T11:36:51","slug":"types-of-ai-you-need-to-know-if-you-work-in-customer-service","status":"publish","type":"post","link":"https:\/\/enreach.es\/en\/blog\/types-of-ai-you-need-to-know-if-you-work-in-customer-service\/","title":{"rendered":"3 types of AI you need to know if you work in customer service"},"content":{"rendered":"

Keeping up with the rapid advances in artificial intelligence<\/strong> can seem impossible. This post provides a quick and clear overview of the various types of\u00a0AI for customer service<\/strong><\/a> currently available in the contact centre solutions market.<\/p>\n

TYPES OF AI USED IN CONTACT CENTRES<\/strong><\/h2>\n

1. CONVERSATIONAL AI<\/strong><\/h3>\n

It\u2019s the technology that allows machines to interact with humans in a natural way<\/strong>. It is trained on large volumes of data (texts, recordings, video calls) to understand the semantics of human interactions<\/strong>.<\/p>\n

Despite the name, it\u2019s not limited to chat channels<\/strong>: it can also be used for voice, without pressing buttons or using specific commands.<\/p>\n

The most well-known conversational AIs among the general public are assistants like Siri<\/strong> or Alexa<\/strong>, although these are less sophisticated than the conversational AIs available today.<\/p>\n

HOW DOES CONVERSATIONAL AI WORK?<\/b><\/span><\/h4>\n
    \n
  1. The user makes a request (prompt<\/em><\/strong>)<\/li>\n
  2. The AI analyses<\/strong> the message<\/li>\n
  3. It identifies the user\u2019s intention<\/strong><\/li>\n
  4. It generates and delivers a response<\/strong><\/li>\n<\/ol>\n

    EXAMPLES OF CONVERSATIONAL AI IN CONTACT CENTRES<\/strong><\/span><\/h4>\n

    In the contact centre industry, conversational AI is used in voice channels as a replacement for traditional IVRs<\/strong>. Its main advantage is that it allows users to freely state the reason for their enquiry<\/strong>, instead of choosing from a limited menu.<\/p>\n

    In text channels, we find bots or virtual assistants<\/strong> that, just like in voice, are able to understand open-ended questions.<\/p>\n

    Regardless of the touchpoint<\/em>, what sets conversational AI apart from older intent-detection technologies is that it doesn\u2019t rely on commands or keywords<\/strong>. It understands full messages, can interpret the user’s emotional state and responds accordingly\u2014as a human agent would<\/strong>.<\/p>\n

    While a machine can\u2019t feel empathy<\/strong>, it can generate empathetic responses like: \u201cI\u2019m sorry your order hasn\u2019t arrived yet.\u201d<\/em><\/p>\n

    2. GENERATIVE AI<\/strong><\/h3>\n

    GenAI<\/em> is the technology that allows machines to create content from scratch<\/strong> (text, images, code, etc.). For example, ChatGPT<\/strong>.<\/p>\n

    It is trained on large amounts of data (articles, posts, images\u2026) to recognise patterns<\/strong> and generate new content accordingly.<\/p>\n

    A conversational bot may include a generative AI model<\/strong>, allowing it to interact in a more creative, natural and personalised way.<\/p>\n

    HOW DOES GENERATIVE AI WORK?<\/b><\/span><\/h4>\n
      \n
    1. The user makes a request (prompt<\/em><\/strong>)<\/li>\n
    2. The AI understands what kind of content it needs to create<\/strong><\/li>\n
    3. It generates a new text<\/strong> (such as a summary or a reply)<\/li>\n
    4. It delivers the content ready to use<\/strong><\/li>\n<\/ol>\n

      EXAMPLES OF GENERATIVE AI IN CONTACT CENTRES<\/strong><\/span><\/h4>\n

      An example of generative AI in contact centres is speech analytics<\/em> solutions<\/a><\/strong>. Based on the transcription of a call or chat history, the AI can generate a title and summary of what was discussed<\/strong>, categorise the conversation<\/strong>, assess the customer\u2019s satisfaction<\/strong> and score the agent\u2019s performance<\/strong>.<\/p>\n

      3. AGENTIC AI<\/strong><\/h3>\n

      Unlike generative AI, agentic AI is proactive<\/strong>: it doesn\u2019t wait for instructions. It can make decisions autonomously<\/strong>, set priorities, and perform actions without direct human input<\/strong>.<\/p>\n

      This means it doesn\u2019t need a user prompt<\/em> to operate<\/strong>. It reacts automatically when its environment changes.<\/p>\n

      HOW DOES AGENTIC AI WORK?<\/b><\/span><\/h4>\n
        \n
      1. It detects an event<\/strong> or need (without being asked)<\/li>\n
      2. It interprets the situation<\/strong> and defines a goal<\/li>\n
      3. If the task is complex, it breaks it into smaller steps<\/strong><\/li>\n
      4. It checks the conversation history<\/strong><\/li>\n
      5. It takes action in external systems<\/strong> (CRM, email, etc.)<\/li>\n
      6. It resolves<\/strong> the task and updates<\/strong> the system (e.g., logs it in the CRM)<\/li>\n<\/ol>\n

        EXAMPLES OF AGENTIC AI IN CONTACT CENTRES<\/strong><\/span><\/h4>\n

        A clear example of agentic AI in contact centres is copilots<\/em><\/strong> integrated into contact centre software<\/a>. While the agent is speaking with a customer, the system detects that the issue is related to a delivery. It then proactively checks the CRM<\/strong>, sends an alert<\/strong> to the logistics team, and suggests a response<\/strong> so the agent can inform the customer that the issue is being handled.<\/p>\n

        The challenge with these agently powered copilots<\/em> is that they can feel intrusive<\/strong> to customer service professionals. That\u2019s why many software providers choose to integrate them in a less proactive way, allowing the agent to activate the flow manually<\/strong>, for example by pressing a button.<\/p>\n

        EXPLORE THE WORLD OF ARTIFICIAL INTELLIGENCE FOR CUSTOMER SERVICE<\/strong><\/h2>\n

        Fill this form to get expert advice.<\/p>\n