3 Things to Consider Before Implementing AI

Tricia Morris at 8×8 explains three things to consider before implementing AI in the contact centre.

For customers seeking self-service support on a brand’s website, chatbots are increasingly becoming the director of first impressions.

But when chatbots aren’t designed and/or deployed properly, the optimism the customer starts with in getting an issue resolved can quickly turn to frustration. In fact, 45% of customers say their interactions with chatbots have frustrated them.

If your organization’s CSAT scores have been burned by your current chatbot offering, you’re not alone. Many business and contact centre leaders who were told to quickly implement AI to solve a certain problem—maybe handle more customers more quickly while reducing costs or headcount—have found out the hard way that throwing AI at the problem can easily make things worse.

In most cases, taking a step back before implementing AI in the contact centre will help organizations move forward faster and with better results.

Take a Different Approach to Contact Centre Chatbot Implementations

Even when they are viewed as value centres, contact centres are still focused on saving money. Cutting staff has typically been a method for cutting costs, and today, the view is not very different, with AI being seen as a means to an end.

In the contact centre, Gartner predicts that conversational AI will reduce labor costs by $80 billion in 2026. But while most IT directors and CFOs are currently focused on reducing costs when it comes to AI implementations for the contact centre, the last thing the customer wants is no human agent to talk to when they experience self-service friction.

While 89% of consumers say they appreciate customer service chatbots for quick answers, 55% say that being able to get to a human agent, and particularly one with context of what they typed to the chatbot, is one of the most important aspects for them in a support experience.

Save Money (and Contact Centre Agent Jobs, Too)

A recent NPR article featured a story on an administrative software company that implemented a chatbot to save both time and money by answering repetitive customer questions, but also to assist new and underperforming agents with the responses that created the highest customer satisfaction.

Long story short: no agent jobs were harmed in the making of this AI success story, but this implementation led to a 14% increase in agent productivity, higher CSAT ratings, customers being nicer if and when they needed to talk with a live agent, and new contact centre agents and low performers rapidly improving.

We also recently spoke directly to a global vice president of support with a similar approach to AI and automation.

The organization saved more than one million dollars a year while improving customer satisfaction by 20%. He advised, “You can’t go at AI and automation projects with making cutting costs and cutting jobs your number one goal.

“If you do, you’re going to cut customer satisfaction, too. But if you approach AI and automation with a holistic look and what the customer needs, and how it can compliment people and processes, you can very likely have it all.”

Consider These Three Things First When Implementing AI in the Contact Centre

Taking a step back, what should organizations consider before implementing AI in the contact centre?

1. Listen to What the Customer Needs.

With the recent fervor around AI, contact centre and IT leaders need to remember first to focus on the customer, and then the technology. Ask “what do my customers actually need,” not just “what can this technology do.”

2. Define How AI Can Complement Both People and Processes.

Think about how conversational AI and Generative AI can complement current successful processes, versus replacing them or people.

3. Understand What Insights Are Needed to Be Effective and Improve.

Methods and metrics matter. Take time to truly understand the customer and pain points in their journey and what kinds of insights and measurements you will need to allow your organization to be effective and to understand what’s working / not working.