As you know, the use of Artificial Intelligence (AI) technologies in the contact center is increasingly widespread. However, its practical implementation is not free of complications.

Thus, in a recent article published by Call Center Helper, entitled “Top Mistakes Businesses Make with AI in the Contact Centre”, this question is thoroughly analyzed. Here you can read the original article, and below we offer you a translation and adaptation of this interesting content:

The mistakes of Artificial Intelligence within companies and contact centers



Helen Billingham of Enghouse Interactive lists a number of errors that contact centers often make when installing chatbots for the first time.

In this sense, there is a great debate in the market about the use of robots and Artificial Intelligence (AI) and their future role in the contact center, often raising exaggerated expectations.

Many people talk hypothetically about what robots could do in a customer service context. But very few are actually using an AI approach to connect with customers today.

There is no a unique answer regarding this subject

Some organizations will continue to use human service as an essential part of their differentiation and value proposition, but most are introducing a growing element of AI and automation as they move towards an increasingly self-service approache.

In 2011, analyst Gartner predicted that by 2020 customers would manage 85% of their relationships with the company without interacting with a human being. But, as chatbots and other types of AI are implemented, a number of pitfalls emerge that companies must be aware of.

Here we outline some of the main problems and how companies can avoid them.


Failing to provide bots with an adequate job description




Companies are increasingly inclined to introduce robotic technology (including chatbots) in the contact center to help them with their operations. This offers significant potential benefits.

A recent Accenture study found out that, in a global level, CIOs (Chief Information Officers) and CTOs (Chief Technical Officers) argue that conversational robots will play a critical role in the enterprise architecture of the future.

In fact, 60% of the executives surveyed for this study said that bots can “enhance your organization’s ability to handle customer inquiries by networking with other bots,” while 57% believe they could “deliver personalized customer service to the visitors of a web being more conversational ”.

However, most bots fail to meet expectations in the first instance since most organizations do not connect the acquisition of the bot with a defined business goal.

Do not make the same mistake. After all, if you don’t know exactly what you want the robot to do, how are you going to train and develop it?

Like a human being, the robot needs to have access to the latest relevant knowledge and all the information necessary to be able to offer its best work. Otherwise, the value they can provide would quickly crumble.

Also, you should think about how your new robot fits into what we would call SPRO model (Strategy, Processes, Resources, Organization).




From a strategy point of view, consider what you are trying to achieve, what business you are in, who your customers are, and which is the best way to interact with them.

From a processes point of view, what specific processes would help you achieve those goals and interact with those who are most important to your business?

You should also take into account what resources you need to better achieve your final goals.

Finally, you need to get organized to find the right way to meet your objectives in relation to strategy, find out what you are trying to do and develop your processes correctly.


Neglecting the proper integration of the robot within the organization

Many companies implement robots and then neglect their proper integration within customer service operations. In this sense, it is a mistake to think that robots can handle each and every interaction . In this sense, they cannot show empathy and are not good at dealing with complex issues.

When designing your customer journey map and build the infrastructure that will support it, you must make sure you have a route to perfectly scale any interaction from the robot to a human being, without losing context in real time.


customer journey

Forgetting the need for training

As with any human agent or channel of interaction, you should measure the performance of the robot in relation to the business objectives, and then focus on implementing the corresponding improvements.

For sure you wouldn’t expect a new worker to catch up with all your processes without any internal training. So why should you expect it from a robot?

Treat your automation systems and chatbots like human agents. Make sure to train and support them and monitor their progress on a regular basis to drive continuous improvement.


Do not using AI as an operational hub within your business




Artificial Intelligence can help companies monitor and understand customer interactions, and use that knowledge to provide better self-service quality. However, it can also help the company decide which human agent is best suited to handle each issue .

It is not just about matching the skills of an employee with the nature of a client’s inquiry, but also about matching the profile of an agent with the profile of a client, to ensure that the two of them understand each other. This is important because, regardless of the issue, if people bond well, the relationship tends to be more productive .


Neglecting the need to keep knowledge management up-to-date

According to the principle of “if you put garbage, you take garbage”, any robot can only be as good as the knowledge that is made available to it.

Therefore, you must ensure that when a question is answered in the contact center, that knowledge is stored and sent to the knowledge management system (KMS, knowledge management system ) , so that clients, bots and human agents can feed on it.

If you envision the automation effort within the contact center as an iceberg, the small part that stands out would effectively be artificial intelligence, while the part that remains hidden would be knowledge management.

AI can have many benefits, but how can it be used for decision making when you really don’t know anything? You can indeed learn, but you need relevant data to do so.

That is why it is so important to have processes and procedures that allow you to provide accurate information and intelligence to the KMS.

Regarding this, many companies rely too much on their employees as a source of knowledge . They have come to accept a situation where, on a daily basis, most of the company’s knowledge goes out the door and may never come back.

Companies need to find a better way to capture knowledge forever. In this way, the use of knowledge management systems would allow them to take advantage of people’s intelligence, so that if those people left the company, the organization would be better prepared and more flexible to handle it.


Do not protecting yourself from the possibility of your bot “rebelling”

Finally, although Artificial Intelligence and robotics technology are constantly advancing, companies must realize that their AI systems are not immune to a possible hack .

Thus, you should protect yourself against the possibility that your chatbot becomes “evil”, for example. We are already seeing cases in which hackers take control of bots and provide them with false information, so that, for example, they direct customers to a fraudulent website.

Also, make sure you have adequate security and threat protection technology to deal with these types of situations.

Looking to the future

Undoubtedly, exaggerated expectations regarding the use of AI in customer service operations will continue to exist. Robots are not going to take over the contact center anytime soon, so striking the right balance between automation and human management is a must for any organization that wants to be successful .

However, today, most businesses are introducing an increasing level of automation in their customer-facing operations and many are increasingly using chatbots and other AI systems to offer their customers what they need.

That, without a doubt, is a great responsibility for any company. And, as they implement it, organizations must avoid all those hurdles and pitfalls of which they are often victims.

Following the advice we’ve outlined should help you avoiding the hassle of transitioning to a more automated future.


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