Artificial intelligence (AI) is a part of the business world today, whether companies accept it or not. In fact, AI is transforming customer care industry practices and changing the competitive landscape for contact centers and many other businesses. Every company can leverage AI in different ways in order to create efficiencies and improvements within their enterprise—and contact center environments are a prime example of this.

Over the last few years, we’ve seen a huge shift in how businesses view AI tech—from apprehension, to curiosity, to realizing that this technology is necessary to maintain a competitive edge. If your contact center is at the beginning of its AI journey, the great news is that you have an opportunity to build a solid foundation for your AI strategy that will be sustainable for years to come.

Start with Sparks, Not Fireworks

On the surface, developing a strategic direction for AI in your contact center might seem like an easy task, when in fact it can be quite challenging. The approach is very different from a regular business strategy. An AI strategy should be designed to support the overall business strategy of the CX program, and maintain a similar overarching focus.

With the recent uptick in adoption of this tech, many industry veterans attempt too much too fast, making huge investments in solutions that require not only an overhaul of their entire tech stack but also extensive planning and many months to see any ROI.

As the CX landscape rapidly evolves, this can leave organizations spending a lot of money while still being left behind. That’s why Laivly advocates for starting your AI journey with simple, achievable wins that make a big impact for your business. This approach allows you to take incremental steps forward and pivot as appropriate, while also preventing you from getting stuck in a state of perpetual planning.

Create an Incremental Roadmap, Leaving Room for Detours Along the Way

An AI strategy needs to begin with a goal, just as in any strategy. You have to ask the question: what are we trying to accomplish? This will typically stem from a current inefficiency or area in need of improvement within the customer care program. From there, the next step is to understand the scope of AI’s capabilities and how this fits into your contact center’s needs.

Which part of your contact center’s day-to-day operations can be streamlined using this technology? For example, a program should see the benefits of automating case notes almost immediately, as this not only reduces after-call work but also improves QA and handover processes.

There is something also to be said about taking unexpected detours on your AI and automation journey. When you start simple and expand incrementally, it leaves room for you to lean into things that are working for your CX program—even if they weren’t initially on the radar. 

The Role of Data, Infrastructure, and Algorithms in Creating an AI Strategy

When creating an AI strategy for your contact center, it’s important to look at a variety of factors that will have an impact, such as data, infrastructure, and algorithms. Put simply, AI could not exist without data, and this has been a contentious issue as more organizations adopt this new tech. It’s key to be very clear about how data is collected and used by any solutions partner you choose, as this has the potential to affect your customers’ security and your business’s reputation. Infrastructure is another necessary consideration with AI models, so you’ll want to find a vendor that can adapt to your existing infrastructure  and the needs of your company. Finally, you should remain aware of what algorithms will be utilized in order to deliver the most value and minimize risk. For instance, generative AI has been shown to hallucinate without proper guardrails in place, so a vendor like Laivly, with specialized language filters in place, can prevent unwanted errors.

Just as there are some things that AI can’t compete with humans on (like making genuine connections with customers), there are also some things that AI can do better. For example, AI is really good at recognizing patterns in large sets of data. Often when a person looks at large sets of data, they already have some sort of story they’re looking to tell—whereas AI looks at data more neutrally, and this unbiased perspective can help customer care programs uncover their blindspots and address root causes of issues.

In most cases, Laivly  first uses AI to collect data (metrics like AHT and ACW) for each client, which can then be used as a baseline to determine the best use case to target first, then implement the right AI or automation solution. This approach also helps identify priorities and where AI will have the most value.

Ultimately, road-mapping your AI strategy may seem daunting, but it will save your organization time and resources in the long run. No matter the size or scope of your contact center or customer care program, leveraging artificial intelligence solutions can take your business to the next level. The buzz around AI may have ebbed and flowed over the last several years, but as this 2019 article from Towards Data Science shows, choosing the right use cases has always been an excellent place to start strategizing.