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Imagine artificial intelligence as a vehicle. For many years, humans have been in control, with AI serving as a helpful co-pilot that provides maps, data, and thoughtful recommendations. However, with the emergence of Agentic AI, this co-pilot has evolved to drive independently.
It is now capable not only of selecting the optimal route but also of recalibrating the journey in response to unforeseen challenges. Furthermore, by the end of the journey, it may even suggest a stop at an unexpected location, one you were unaware of but that significantly enhances the overall experience.
This may sound like a glimpse into the future, but it is already a reality. In this post, we will explore what Agentic AI is, how it differs from Generative AI (GenAI), and how it is being implemented in CX practical scenarios. Because yes, this technology has already become part of our present.
What is Agentic AI?
Agentic AI represents the natural evolution of artificial intelligence, with its development deeply rooted in the concept of Deep Learning. While we have grown accustomed to tools that rely on detailed instructions or predefined processes to operate effectively, Agentic AI introduces systems capable of thinking, deciding, and acting independently.
In the context of customer experience (CX), the fundamental difference between traditional generative AI bots and Agentic AI lies in autonomy. This groundbreaking technology no longer requires a predefined flow to dictate each step; instead, it acts with its own initiative. It can now evaluate situations, make decisions, plan actions, and execute them with remarkable proficiency, even when these actions involve interacting with various business systems, all without the need for constant human intervention. This concept, referred to as agency, empowers AI to design and execute its own workflows entirely autonomously.
According to Gartner®, by 2028, 15 % of daily work decisions will be made autonomously by systems powered by Agentic AI. This advancement heralds a new era where AI functions as a proactive collaborator, capable of transforming productivity and reshaping traditional operating models.
GenAI and Agentic AI: What Sets Them Apart?
Although GenAI and Agentic AI stem from the same foundation, their capabilities and focus are fundamentally different. Below, we examine their key distinctions:
1. Problem-Solving: From Individual Tasks to Complete Processes
GenAI systems excel at specific tasks, such as categorizing messages or answering precise questions. However, when it comes to managing more complex processes, like handling a customer complaint, they require constant oversight. You would need to break down the customer’s message, evaluate any attached images, check for coverage, and finally decide on the next steps. Each phase demands your supervision.
Agentic AI, on the other hand, takes full control. This technology is capable of independently completing the entire process. It does not require guidance at each step, and this is precisely what makes it so revolutionary. This extraordinary capability is poised to fundamentally transform how CX operations are conducted as we know them today.
2. Autonomy and Agentic AI: From “tell me what to do” to “I’ve got this”
The most significant difference lies in autonomy. While traditional systems require human instructions to operate, Agentic AI determines when to act, decides on the appropriate steps, and executes them without any assistance. Thanks to this independence and its advanced reasoning capabilities, these systems can operate proactively, even in constantly changing environments.
3. Memory and Tool Usage: A Leap in Business Adaptability
Another key limitation of traditional systems is their lack of long-term memory and limited ability to utilize external tools. In contrast, Agentic AI is what is known as ‘stateful’: it can retain context for days, weeks, or even longer. This enables it to learn automatically and improve its performance with every interaction. Additionally, it leverages APIs and knowledge bases to make informed decisions, making it even more effective and efficient.
Practical applications and the shift in business dynamics
Agentic AI has the ability to automate entire workflows. How does it achieve this? By personalizing every interaction. It can analyze purchase histories, evaluate and predict behaviors, and provide tailored recommendations or follow-ups. The result is increased customer loyalty and satisfaction, alongside improved business outcomes.
Here are some practical applications that illustrate its potential:
1. Automation with a human touch in telecom promotional campaigns
In the highly competitive telecommunications sector, virtual agents powered by Agentic AI are breaking new ground. They can manage telemarketing campaigns from start to finish, all while delivering a surprisingly human touch (here is an example).
How do they achieve this? By instantly personalizing each interaction. While they work with a reference script, they are not rigid; instead, they adapt their messaging based on the customer's responses and the information they retrieve from knowledge bases and business systems. This allows them to ensure that phone conversations feel empathetic and natural. Adding to this is the realism of the voices and regional nuances (supporting more than 200 languages in the case of Inconcert), enabling them to tailor promotional campaigns to specific markets and target audiences.
2. Streamlining insurance management
Imagine a customer of an insurance company reporting an incident via email, attaching photos of the damage. Without any human intervention, a virtual agent powered by Agentic AI can:
- Analyze the message and categorize it based on its content.
- Extract structured data from attached documents (such as images or PDFs).
- Query internal databases to verify customer information and policy terms.
- Request additional data if needed, while maintaining the interaction’s context.
- Calculate the reimbursement and update the claim’s status in the system.
In short, this approach streamlines the process and significantly enhances the customer
3. Optimization in the transportation sector
In the transportation industry, which plays a critical role in retail and e-commerce management, agents powered by Agentic AI are already solving complex challenges, such as locating lost shipments. For instance, if a package goes missing or a customer reports an issue, the agent can automatically communicate with carriers, warehouses, and customers to determine its whereabouts.
If a solution cannot be found, the system can manage the corresponding claim with the responsible partner, all without the need for human intervention.
Entering the era of intelligent autonomy applied to CX
With everything we have seen so far, it is no surprise that Agentic AI is emerging as a new paradigm that is once again transforming how we interact with companies and how this technology integrates into CX management, ushering in a new operational reality.
Learning to make the most of it is almost a necessity for any company that aims to grow in an increasingly competitive market, where intelligent autonomy will set the pace of progress. Choosing to leverage its advantages could be the tipping point between evolving alongside the market or falling behind.
In any case, Agentic AI is not the final destination but rather the beginning of a journey toward a more autonomous, intelligent, and connected future. Are we ready to let it take the wheel? Without a doubt, the future looks incredibly exciting…
