At SEION, we have already told you how to create an AI agent and the benefits it has for your company, but what happens when you create it and it doesn't work as expected? The errors it makes can be fixed with good training.
Training an AI agent involves configuring its instructions, documentation, and integrations with other systems so it achieves the purpose for which it was created. Remember that an AI agent is software that acts intelligently without a human telling it each step to follow, and for this, it is essential to have given it the proper instructions.
Steps to Train a Conversational AI Agent from Scratch
1. Review How You Created Your AI Agent
- Does the agent have a clear objective?
When something doesn't work, it's best to look back. To correctly create an AI agent, it's essential to have a clear mission for that agent, why you created it. And it has to be a specific function; you can't create an agent that serves to assist users who want to know more about your company and also knows how to manage internal invoices. These are two very different functions that should be in two separate agents.
- Are the integrations too limited or open?
The agents must be connected to your systems or tools to carry out the necessary tasks. For example, if you create an agent to manage existing clients, you will need to connect it to the profiles of those clients. However, you must consider the limitations because many errors can arise from them.
In the previous example, the agent should have a limitation to only view and send information about the client they are currently talking to; under no circumstances should they be able to provide data about other clients. That's the kind of scenarios you need to review in your integrations: what information the agent can access, when, and with whom they can share it, and how and where they record the information given to them by the user they are talking to. All this depends on a good integration.
- What platform did you use to create your AI agent?
There are multiple platforms and tools to create an AI agent; for example, if you have Microsoft, you could create it yourself with Copilot. There is also the option to create AI agents completely tailored to your company with custom software. Each option, accessible online tools or personalized software, has its advantages and disadvantages; choose the one that suits your company in the long run.
Comparison table:
2. Provide the Information It Needs
The agent needs to memorize what it will later have to practice. For example, if you create an agent to solve technical issues with your products, you must provide it with all the documentation for each of your products and their technical specifications so it can understand the problem the client is reporting and find a potential solution.
These documents, in PDF or the format of your choice, will be its knowledge, so ensure there are no errors or contradictions, or the agent will succumb to them.
3. Tell It How to Behave
In general, training an AI agent is like teaching a new colleague how you work: the documentation explains what the company is about and the products or services available, and the instructions tell them what functions they have. But regarding behavior indications, you have to go one step further.
As with any new colleague, you will give clear instructions on what to do: "Now you are the customer service expert for my company," "you need to provide information about our services to users and resolve their questions," etc., but you should also consider things you might assume with a person, like speaking concisely, addressing customer inquiries before offering or asking them something, not insulting or getting into confrontations… Don't take anything for granted; an AI agent doesn't know how to behave socially unless you instruct it to and it can cause trouble.
Additionally, it will help a lot if you give examples of what it can say. Another commonly overlooked aspect: you'll need to be clear about the target audience to provide instructions accordingly. For example, if it's the general public, you'll need to advise it not to use technical jargon while speaking.
4. Test It Extensively Before Launching It
If there is something crucial in training an AI agent, it is the testing part. This will take the most time and is where you can detect errors you couldn't foresee. Communicate with it as if you were a real user and continue the conversation until you see if it performs the actions you expected. Chances are you'll need to address some of the following errors.
The 5 Most Common Errors of AI Agents That Can Be Solved with Good Training
1. Why Does My AI Agent Make Up Information? Hallucinations
The most common problem with all AI is making up the answer, i.e., the so-called hallucinations. It usually happens when someone asks it for information that it has no answer for. It is resolved by indicating what to do when it doesn't have the answer: "don't make up this information, if you don't know how to respond to something because you don't have the knowledge, reply that you can't assist with this topic and pass the conversation to someone from the support team through your connector." This is a real example of an instruction that solved the hallucination problem for one of our agents.
If after giving these instructions it continues to make up a specific answer, review the documentation and other instructions to ensure there is no error or contradiction.
2. Why Doesn't My AI Agent Perform the Action It Should?
The goal of many agents is to execute an action, such as scheduling an appointment. Your AI agent might be perfect at carrying on the conversation with the client, asking the preferred time and day, and checking availability, but when it comes down to it, you don't see the appointment on your calendar.
If this is the case, the execution errors of the task are usually due to poor integration with the necessary tools. Check that the agent has access to all systems or platforms involved in that action, and that there are no unnecessary filters or limits.
3. Why Does My AI Agent Reveal Its Internal Configuration?
"I can't find that product in my documentation," "sorry, but my instructions tell me otherwise," are responses your agent may give if you don't tell it not to discuss its configuration, its knowledge documents, or in general the prompt it was created with.
If you don't want to disclose how you created and trained your AI agent, I suggest you make it very clear in its instructions.
4. Invisible Errors to You
It may seem ready after much testing, but no sooner after launching, your colleague from another department sees several errors. It is essential for other people to test your agent to generate different scenarios that you might not have thought of, especially if the AI agent is for another department.
For example, have you indicated that it always responds in the language it's addressed? Because it might be a great agent in Spanish, but not in English.
5. What Do I Do if My AI Agent Keeps Failing?
If you've tried all the solutions we suggest and others, and it still makes errors, it could be due to one of these two reasons. You might be placing too much trust in the AI: it is almost impossible to predict all the situations that may arise in a department, which is why it's always best to provide your agent the option to transfer the conversation to an employee when it doesn't know how to resolve it.
Or perhaps the agent you tried to create is too complex: there are many ramifications in your instructions depending on what the user says, many connected tools… Simplicity, for many reasons, is always better. Separating that agent into multiple agents with simpler missions might be ideal.
Extra: Data Protection
The error that few notice: being compliant with data protection legislation. Just as when someone registers in a form with their contact information, they must confirm that they have read and agree with the privacy policy, if your AI agent is going to collect and process personal data, it must seek the corresponding consent according to the regulations.
For example, you can instruct the agent to inform the user that their data will be used, send the privacy policy link, and ask for their consent before proceeding.
In summary, most errors can be detected by conducting enough real tests of the agent. To resolve them, indicate to the agent what to do in that situation in its instructions or review the documentation and integrations, where there might be errors, contradictions, or misplaced limits.
How Can I Predict What Errors My AI Agent Will Make?
Testing. We wish we could give you a simpler answer, but the reality is that only trial-and-error and experience will help you understand how an AI behaves, which is not the same as a human.
At SEION, we have reached these conclusions after deploying dozens of AI agents for our clients. We have trained agents for very diverse functions within companies in very varied sectors. From agents dedicated to qualifying leads for the Marketing department of an industrial manufacturing company, to agents that speak with clients looking to schedule or change appointments in a salon franchise.
If you want to resolve your questions about how SEION AI agents can help your company in particular, you can always schedule a call without cost or obligation here.
