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Why Chatbots Fail To Deliver Results & What Businesses Use Instead!
Agentic ai vs Chatbot – The Big Problem with Traditional Chatbots
Why Chatbots Fail To Deliver Results – The biggest problem with traditional chatbots is that they lack autonomy. These are systems given a set of rules to follow and a set of pre-programmed responses. A customer service chatbot can do a great job when a customer asks a question within the parameters that were set up for it to respond to. But as soon as a customer asks a question outside of those boundaries, the system is lost. It can’t solve multi-step problems.
A simple example of the failure of chatbots was my attempt to alter the delivery address for an online purchase of a sweater a while back. The chatbot was able to report on the status of my order but, when I asked it to alter the delivery address to which it was being sent, the chatbot’s response was to send me a link to the online FAQs for the purchase. I had to search the web to find a phone number to ring and, in the end, had to spend 20 minutes on the phone to someone who answered in a bored voice (and subsequently processed the alteration to the delivery address for me).
So, What Exactly is Agentic AI?
So what exactly is Agentic AI. Agentic AI is a different class of artificial intelligence which is not just answering questions of a script writer. As opposed to this it is trying to achieve a goal. The AI is reasoning about the situation, makes a plan and then uses different tools (APIs, databases, software etc.) to execute the plan. The AI is proactive.
Think of an AI in the form of super-efficient personal assistant to help with the task of booking a flight to New York for next Tuesday. One would not typically write out a script for an assistant such as this but instead inform them of the required task. They then figure out all of the required steps to complete the task in the most efficient fashion, such as check your calendar to ensure the correct date, book the best flights available, use a company card to make the booking and enter the required details into your digital calendar for future reference. The AI would do all of this in a similar fashion but in a purely digital environment.
They Can Actually Solve Problems
This is the main difference for us between agentic AI and chatbots. A chatbot informs you how to solve a problem (by referring you to an article). An AI agent solves a problem for you.
Let’s go back to this problem now. So you want to change the delivery address for an online order. You could set this up to have an AI assist you in getting this changed. The AI is set up to deal with online order systems. The AI would understand that you wanted to change the delivery address for that order. It would then access the online order system and verify that you are the owner of that account. Then it would check with the shipping carrier’s API to see if changing the address is even an option for this order. If it is an option then the AI would change the delivery address. Once the change has been made the AI would confirm with you that the change has been completed.
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Learning and Adapting on the Fly
Another advantage of agentic AI is that it can learn as it goes, becoming more efficiently dealing with problems over time. Ambiguity is also no longer an issue for an AI agent as it can handle situations in unexpected ways. The tool it was utilizing fails? No problem, it can attempt to utilize another. This is not something that can be said about traditional chatbots.
Agentic AI vs Chatbot: The Real-World Difference
Contrasting the two options provides a striking difference between the two technologies and makes it obvious that there is a lot more to both Chatbots and Agentic AI than there initially appears to have been.
For Customer Service
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Customer Service. A customer wants to return an item. A chatbot will say something like “Our return policy can be found here” putting the customer back to work. The AI agent on the other hand says “I’ve processed your return for the blue sweater that you purchased on May 15th. A pre-paid return shipping label has been sent to your email. Simply drop the package in the mail and it will be returned to you.” The AI agent has completed the task for the customer.
The agent would say something like, “I see you purchased the blue sweater on May 15th. I’ve already started the return process for you and a pre-paid shipping label has been sent to your email. Just drop it in the mail. Can I help with anything else?” This is a complete end-to-end solution to your problem.
For Internal Business Tasks
Chatbots are essentially useless for internal business tasks. But for agentic AI, this is an area where it can bring huge value.
So to run employee onboarding a company could create an AI agent that would order a new laptop, create the necessary accounts for email, and install necessary software, book the new employees into necessary meetings and introduce them to the rest of the team. The agent would automatically complete the numerous tasks involved in the onboarding of employees, greatly decreasing the amount of time that HR would normally need to complete the task. This allows the HR team to focus on more strategic tasks as opposed to boring, repetitive tasks that are perfect for automation.
Is it hard to implement?
This is slightly more complex to set up than a simple script-based chatbot, such as the above return example, but the return on investment for such a system is far greater. While a simple chatbot automates to answer basic questions, diverting human effort away from such tasks to deal with more complex issues, agentic AI actually reduces a company’s workforce required to deal with certain tasks.
FAQ
- What’s the main difference between agentic AI and a chatbot?
The main difference between a chatbot and agentic AI is action. A chatbot provides information. Agentic AI on the other hand, acts to complete a task to reach a goal.
- Is agentic AI the same as ChatGPT?
No, ChatGPT is not agentic AI, although agentic AI may use ChatGPT or similar models as its “brain” and then go on to use other tools and software systems to complete tasks.
- Can a small business use agentic AI?
Yes, it can be. As agentic AI becomes more mainstream, more platforms are emerging which allow businesses of all sizes to build and deploy their own AI agents. This doesn’t require a team of developers to set up.
- Is agentic AI expensive?
More upfront cost than a simple chatbot, however cost is decreasing. Then there is the cost of tasks automating and increasing customer satisfaction which will certainly offset the initial cost of the technology.
- How does agentic AI handle complex customer requests?
Agentic AI breaks down complex requests into manageable steps and then creates a plan for completing the request using the most relevant tools. For example, it may check a database to complete the first step of the process. It may then send an email to the next person in the process for them to complete the next step. It may even process a refund in order to complete the last step of the process and complete the customer’s request.
- Will agentic AI replace human agents?
No, I don’t think that agentic AI will replace human agents in customer service. AI systems are well-suited to handle repetitive, time-consuming tasks. Human agents will be better off focusing on the most complex, high-value and emotionally charged customer issues. Agentic AI will be a very powerful collaborator for human agents.
- What are some examples of agentic AI in action?
For example, there is AI that can plan and book an entire vacation in one chat such as flights, hotel and rental car. There is also inventory management AI that automatically orders more stock for you when it reaches a certain low.
Conclusion
So the bottom line is that agentic AI, as opposed to a chatbot, can actually deliver results. So if you are serious about making a real step change in your customer service as well as dramatically improving the way you manage to keep your internal processes up to date then you should continue to read on.
If you’re wanting to improve customer service and streamline your processes then looking into more than simple chatbots is probably for the best. The old way of customer service isn’t good enough anymore, and with agentic AI arriving on the scene solving problems for customers has never been easier.
