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With the advent of ChatGPT and other applications, AI has suddenly become tangible for the general public. While it was previously used primarily for specific, often invisible applications (think fraud detection in banking or predictive maintenance in industry), it now actively assists in content creation, enhancing customer experiences, and streamlining processes.
Within customer experience, three forms of AI are particularly relevant: generative, agentic, and predictive AI. In this article, we’ll break them down and explain how to leverage them effectively.
Generative AI is all about creation. It is trained on vast amounts of unstructured data (texts, images, videos) and can rapidly generate new content. Think blog articles, product descriptions, emails, images, or videos. The system predicts the most logical next step (in the form of text or visuals) based on the patterns it has learned.
In the realm of customer experience, generative AI is used for tasks like automatically responding to customer inquiries, writing personalized emails, or crafting marketing campaigns. This form of AI creates content that helps businesses communicate faster and personalize more effectively. Generative AI is an incredibly useful tool for producing large-scale content in a short amount of time, but it does have a drawback. Since it doesn’t have direct access to your systems or customer data, its output often remains generic and less contextual.
Agentic AI takes things a step further: it can independently perform tasks. When integrated with your internal systems, it can, for example, retrieve customer data, generate a return label, or initiate a payment—essentially doing what a human employee would, but in an automated way.
The key difference between generative and agentic AI lies in the level of integration. Agentic AI can work with data that isn’t publicly available, such as customer order histories, CRM data, or inventory levels. For instance, if a customer asks an AI agent when their order will be delivered, it will check the status in the order system and provide a specific answer. While generative AI primarily focuses on creating content, agentic AI makes processes smarter and faster by executing them from start to finish.
In customer experience, the greatest value of agentic AI lies in automating and optimizing service processes. By implementing agentic AI in customer service, businesses can often eliminate the need to escalate inquiries to a human agent. An AI agent can provide personalized answers and independently handle requests. The result? Shorter wait times, reduced pressure on support teams, and a smoother customer experience.
The third form of AI, predictive AI, works with structured data such as purchase history, website interactions, and email behavior. Using this information, predictive AI can make forecasts: What is the likelihood that a customer will make another purchase? Which product is most suitable for this person? What’s the best time to send a follow-up email?
In customer experience, predictive AI helps enrich customer profiles and personalize the customer journey. This allows businesses to not only make relevant product recommendations but also proactively address customer needs. Examples include:
Predictive AI makes customer communication less reactive and helps businesses anticipate the expectations of their visitors and customers.
While the three types of AI are clearly distinct, they often work together in practice. Consider a scenario where predictive AI forecasts that a customer is likely to respond well to a special offer. In this case, generative AI can draft an email, and agentic AI ensures that the correct product data and customer details are included, as well as processing any subsequent orders automatically.
Together, they create an integrated, personalized, and efficient customer experience—from predicting needs to generating content and executing actions.
Our products leverage all three forms of AI in the areas where they add the most value. For instance, predictive AI plays a significant role in our marketing solutions (such as Marketing Cloud, Customer Data Platform, and AI Engine), while generative AI assists in content creation and improving communication (e.g., in our Service Cloud). Finally, agentic AI powers HALO, our agentic AI platform that allows you to easily build AI agents capable of making autonomous decisions and performing actions. By combining the strengths of generative, agentic, and predictive AI, we help organizations elevate their customer experience to the next level.
And find out how the different types of AI can contribute to your business growth. Let’s talk!
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