From finance to sales to operations, artificial intelligence (AI) and other self-learning automation are impacting every part of the business it comes across. AI is perhaps the biggest revolution of the modern age. Previously, a computer would blindly follow rules and the commands given to it by the user. However, with the use of AI, and Machine Learning, a computer can now find its own way forward. But what about customer experience (CX)?

That’s where things get tricky. People only interact with customer service when they have a problem they need the business to solve. That problem can be something as simple as the desire to buy a product, make a change to a policy, check a balance, or ask a simple question. However, other times it can be because users are having a major issue that’s about to cost the business a valued customer.

Imagine how frustrated it would get to deal with a buggy robot when all we want to do is talk to a living, breathing human being. That’s an easy recipe for customer churn; the exact problem making CX more efficient through AI is supposed to prevent. According to a recent report by PricewaterhouseCoopers, 49 per cent of all the participants are ready to pay or are already paying extra for either a ‘smarter higher-touch customer service’ run by AI that guarantees to solve the problems quickly over text messaging, or, preferably, one that also offers direct access to humans.

AI will open up opportunities for people to do more value-added work, apart from allowing for greater flexibility and work-life balance. Not only does one have to figure out how to best incorporate AI into CX; but also need to figure how to implement it quickly. As more and more companies implement machine-learning apps, chatbots, mobile messaging and other technologies into their customer service, it will be key to start adopting AI into the process now so that they can get over the learning curve and keep up with the competition.

Regardless of the tactics, one chooses to implement, here’s the basic strategy to follow when incorporating AI so that organization learn how to retain customers. 

Slow and steady.

Too much automation too fast can be hard to control for quality. Find a few use cases that are suited for AI that aren’t the high-value interactions and perfect those before moving on to higher-value tasks.

Automate the right things.

It’s a fair guess that more than half of the employees’ time is spent answering the same mundane questions over and over. The more AI is used to handle simple inquiries like “How do I change my email address?”, quicker will be the response for solving the customers’ basic problems while freeing staff up for more complex questions.

Measure, analyze, optimize.

Select the KPIs at the outset that you’ll be measuring to determine success. But don’t just look at AI performance; measure things like customer satisfaction and how the automation affects employees’ performance. For example, if a chatbot is handling all the easy questions, staff time per interaction may actually increase due to the more complex nature of the remaining interactions. Once the KPIs, have been set looking for ways to improve the technology that is being used while slowly introducing additional automation to move the needle further.

Augment, don't replace.

There’s a misconception that AI can, will or should replace human workers like customer service professionals. In reality, AI is best used as a tool that improves the customer experience and employees’ performance alike. In addition to using AI to handle the easy but time-consuming tasks that monopolize staff time, make sure customers always have a simple, direct way to escalate their issue to a human agent. After all, some things still take a human touch.