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Artificial intelligence applied to customer experience has made a strong entry into the business landscape. We are talking about agents capable of understanding, reasoning, and acting without human intervention. The issue is that not everything marketed as Agentic AI truly fits the definition. In a market that is buzzing with innovation, many solutions adopt trendy terminology without delivering the promised capabilities. This phenomenon is known as agent washing, and it is important to know how to identify it before making strategic decisions.
What is AI agent washing?
You have probably heard of greenwashing in the context of sustainability, or AI-washing in the tech world. In customer experience, we now have our own version: AI agent washing.
The term, coined by Gartner, refers to a practice that is becoming increasingly common: selling a basic rules-based chatbot, a traditional IVR, or even a limited assistant as an “AI agent”. In reality, these are older-generation technologies, rebranded to ride the AI wave, without offering the core features that define a true autonomous agent.
A “repackaged chatbot” might be able to answer simple questions, but it cannot understand context, adapt to changes, reason, or execute complex tasks. A true AI agent, on the other hand, is capable of holding natural conversations, remembering past interactions, connecting with your systems, and acting autonomously.
To visualise it better:
- A traditional bot replies with a fixed menu: “Press 1 for bookings, 2 for customer service...”
- A GenAI-powered agent can understand a sentence like “I want to change my flight to Friday” and offer you personalised options.
- A fully autonomous AI agent not only understands your request, but also checks availability in your CRM, verifies your identity, and changes the date directly — all without human intervention.
The concerning part is that, from the outside, it can be difficult to spot the difference. And that is where agent washing comes in: when a solution is marketed as agentic AI, but when you look closer… there is no real AI behind it.
Why is AI agent washing dangerous for your business?
At first glance, falling for agent washing may seem like just a poor technology choice. But in reality, the negative impact goes much further. When a company invests in a supposedly intelligent solution that does not actually deliver, the consequences usually appear quickly:
1. Strategies that start to crumble
The promise of transforming customer service with AI becomes a source of frustration when the solution does not meet expectations. The result: projects that do not scale, limited functionalities, and goals that are never achieved.
2. Wasted resources
Investing time, money, and talent in technology that fails to deliver expected value comes at a double cost: what is lost, and what is no longer gained. Often, part of the work must be redone with a new AI agent provider.
3. Loss of internal trust
When an AI project fails due to inflated expectations, teams become demotivated and resistant to future technology initiatives. This slows down internal innovation just when it is most needed. According to industry reports, the adoption of AI agents is still relatively low. One of the main reasons is the gap between what is promised and what is actually delivered. It is not that companies do not believe in the value of AI, they have simply had setbacks along the way.
4. Reputation at risk
In industries where customer service is critical, a poor experience with a bot that does not understand or cannot resolve issues can have a direct negative impact on brand perception. Even worse: that experience spreads quickly on social media.
How to Identify agent washing
It may seem difficult at first to determine whether a solution truly has AI agent capabilities or is simply using the label. But it is not that hard if you know what to look for. Let us use a practical example: booking a trip.
Imagine a customer writes: “Hello, I would like to book a flight for Friday morning from Madrid to Lisbon.”
How would each type of solution respond?
- A traditional bot or IVR would offer a rigid menu such as: “Press 1 for flights, 2 for hotels,” or reply with: “I do not understand your request. Do you want to book a flight? Reply yes or no.”
- A GenAI-powered bot would understand the intent (book a flight), extract key entities (origin, destination, date), and provide a more natural response. For example: “Perfect! What time would you prefer to fly on Friday?”
- A real AI agent would not only understand the request, but also check real-time availability in the systems, verify the customer’s identity (if returning), and complete the booking or suggest alternatives. All of this would happen without any human intervention.
You can explore this comparison in more detail in the article: Types of Bots vs. AI Agents in Customer Experience.
The 3 keys to identifying a true AI agent
To avoid being misled, these are the three core capabilities that differentiate a true AI agent:
1. Reasoning: It understands what the customer wants beyond keywords, identifies intent, and manages complex cases.
2. Autonomy: It can operate without human intervention, make decisions, and execute tasks in real time.
3. Integration: It connects with your systems (CRM, ERP, booking platforms, etc.) to query, update, and resolve within context.
We explain this in more detail here: What is a virtual agent?.
Quick checklist to detect agent washing
To help you, we have prepared a quick checklist with key criteria to help you distinguish between a repackaged chatbot and a true enterprise-level AI agent:
- Request demonstrations of reasoning, memory, and autonomy.
- Verify that it can integrate with your systems (CRM, ERP, channels, etc.).
- Test how it works across all channels, voice and text, and whether it can maintain context when switching between them.
- Ask for real, verifiable success stories.
- Request a demo tailored to your use case.
At Inconcert, we believe that AI should not be just a marketing slogan, but a real tool that enables you to optimise your CX operations from day one. That is why we develop virtual agents like Inagent, with advanced cognitive capabilities, natively integrated into our omnichannel ecosystem.
Would you like to see what a real AI agent can do? Request a demo.
