What stops you from implementing Artificial Intelligence (AI) for your contact center?
Do you know that 80% of the CX leaders plan to increase their investments in contact center AI?
Do you know that 50% of the CX leaders feel that without AI, customer satisfaction will decrease, and productivity will decline?
Not investing in future technologies like AI would not only impact metrics like customer satisfaction and productivity but would also affect broader business goals like increasing revenue and customer lifetime value.
Looking at this summary, it seems evident that every contact center should implement AI as both a strategic and a tactical tool to grow their organizations. However, this has not been happening.
CX leaders attribute lower adoption of AI to the following reasons – misalignment of business with technology, security threats associated with AI, and skill gaps within the organization.
Misalignment of business goals
Remember that your business should lead your technology, and never let technology lead your business. Often, your business goals are not aligned with your AI strategy, which can lead to wasted resources and technology misadventure.
Let me give an example of how you can align your business goals with your AI strategy. Assume that your goal is to increase customer lifetime value and thereby the revenues.
Now, how do you make use of AI to achieve this goal?
Before you hit upon your data and intelligence strategies, start with some questions like what is their current customer lifetime value (CLV)? What are the factors that influence the CLV? What data do you need to understand which customer is likely to go up the value chain?
Based on this, you create the AI model and start understanding your data. With this data, you derive intelligence to achieve your strategic goals. This is a straightforward example that I have given to figure out how you should align your business goals with your AI strategy. The possibilities, however, are many.
Whenever we talk about AI, we talk about the positive impact that it can have on a business. However, there are a lot of negatives that you need to be aware of.
The fundamental component of AI is large sets of data. You create a model with these large data sets and reach your business objectives. Over time, these models get more and more intelligent and start providing near-accurate predictions.
How do you ensure the privacy of those data while still making use of it to make your predictions? You need to have stringent data privacy policies in place, and the customers should be made aware that their data is being used as a part of your AI strategy.
Besides, there is a risk of system manipulation where you can manipulate your AI algorithms to make false predictions. This can be detrimental as they are not easy to pick out.
It would help if you guarded against these vulnerabilities to get your AI to work positively for your organization.
Do you have the necessary resources to build, train, maintain, and enhance AI solutions? This is the biggest bottleneck that most organizations come across. You usually depend on external resources to develop your solutions – they come at a high cost and don’t understand your domain. So, you spend substantial time training them on your domain and your business goals.
Based on these inputs, the AI experts build your solution and continue to maintain it for long before you start to see results. This can make a considerable dent financially for your organization.
Contact centers in the last decade have transitioned from cost centers to profit centers. Contact centers are increasingly using technology to enhance their customer experience function, with AI being adopted increasingly.
AI needs to be looked at holistically with all its associated challenges. As an organization, you need to have a lot of patience to see results from your AI strategy, and the good news is it can only get better.