Is your contact center AI-ready?

What do the words pain and gain have in common? Well, they’re both halves of the well-known cliche—“no pain, no gain”—and they both have artificial intelligence (A-I) in them. 

We know…it’s a lame joke. But there’s some truth to it. AI-powered technologies are changing all aspects of life and contact center leaders know they can gain a lot with its adoption—gains in efficiency and improvements in agent and customer experiences. According to Execs in the Know’s 2023 CX Leaders Trends and Insights, 73% of organizations invested in AI in 2023, up from 48% in 2022. 

However, as the cliche says, all gains come with some pain. In the case of AI adoption, the pain might look like financial investments, change management challenges, or, in many cases, not being foundationally ready to fully reap its full benefits. 

In a recent Execs in the Know webinar, Sharpen’s Vice President of Marketing, Laura Bassett, discussed some of the innovative AI-powered technologies available to today’s contact centers. During the Q&A, one attendee asked a question that underscored a common pain point: 

“My contact center doesn’t have the resources or budget to implement all these cool new capabilities—what should I do to make sure we’re not left behind?”

The answer: Take steps now to ensure you’re ready to adopt AI later. Though your contact center may not have budget today, you will want to be ready when the time comes—whether it’s next quarter, next year, or in the next decade (though let’s hope that’s not the case!)

In this blog, we explore a framework based on three questions to help you assess if your contact center is AI-ready.

1. Do you know your greatest pain points?

With so many opportunities for improvement, many contact center leaders struggle with where to start their AI journey. Though you can’t—and shouldn’t— tackle everything at once, you will want to identify what to tackle first when the opportunity arises. 

The best way to do that is by identifying your greatest pain points. What are the bottlenecks, inefficiencies, and recurring issues plaguing your contact center today? Look across the breadth and depth of your customer, agent, and operational experiences and remember that ironically, your biggest pains might have the smallest roots. 

For example, you might see that the containment rate for your self-service IVR is really low and most customers have to route to an agent to complete the transaction. You might initially assume your IVR is broken or unable to meet your needs—an expensive problem—but upon closer inspection, you realize that there’s one data field that’s been mapped incorrectly between your CRM and IVR—an inexpensive, easy problem to fix.

Data is key to identifying and understanding your pain points and goes hand in hand with our next question—do you have a solid data framework? 

2. Do you have a solid data framework?

AI-powered technology is only as effective as the data it’s working with. Data is foundational for an effective AI implementation because the engines need good data to analyze, learn from, and act on. 

However, many contact centers’ data situations are messy, and as the saying goes—garbage in, garbage out. Contact centers aren’t alone in this challenge. According to McKinsey research, poor data quality is the main roadblock for 60 percent of tech executives looking to scale data solutions. 

But implementing new technology—AI-powered or otherwise—without first getting your data in order would be like installing a top-of-the-line car engine and filling it with dirty old gas. You can do it, but you won’t get very far or reap the benefits.

The good news is that you can take action now to get a better handle on your data and prepare for a more successful AI implementation later. Key things to consider include:

• Where is your data? Map out all the systems that generate and house data related to your CX and contact center operations. Don’t limit your mapping to systems or platforms owned by the contact center, but also include those used by other functions that impact your customer experience. Oftentimes organizational silos give rise to data silos. Collaborate across teams to identify and share data. Also, map out where and how your systems integrate today.
• What data do you have? Once you’ve mapped out where the data is, identify the data points themselves. Data types and points to consider include:
  • Customer data, including past interactions, company relationship history, sociodemographic information, location, and even behavioral information.
  • Agent data, including performance metrics, scheduling and other workforce management data, quality management scores, channel preferences, and more.
  • Interaction data across all the different channels your contact center supports, and depending on your organization, even channels owned by other functions. For example, if your marketing department interacts with customers on social media, map out those CX data points as well. 
  • Transaction and revenue data so that you can map contact center activity to revenue. 
• What data do you need? As you answer the questions above, you’ll likely identify key data points you’re missing to get a complete picture of your operations. However, recognize that you probably do have the data you need—somewhere and in some format. Instead, it might be a matter of how you’re looking at the data and whether your current analytics tools give you the insight you need. That’s where AI can help you turn random data points into prescriptive action (once your data is clean and organized, that is!)

3. Are you taking advantage of the tools you have in place today?

It’s tempting to look at AI as the solution to all your problems. But before AI, there were likely other systems and tools you implemented hoping to transform your contact center. Are you maximizing their potential and reaping the full benefits of those investments? Many contact centers aren’t. 

For example, I recently visited a prospective client’s contact center and observed their agents toggling, copying, and pasting between multiple screens to pull up an incoming contact’s profile. Could this contact center implement AI-powered automation to streamline this process? Of course. But you know what else they could do, but haven’t? Use open APIs to integrate their existing systems and incorporate agent screen pops.

Many contact centers haven’t maximized their existing technology due to limited expertise, lack of time to explore how to do so, or competing priorities—all of which are understandable. But, exploring the full potential of your existing capabilities before investing in new technology is important for two reasons. 

First, like the above example, you might already have the solution to the problem you’re looking to solve with AI. Why buy an expensive new steam cleaner when the vacuum you already have came with a great steam-cleaning extension—you just haven’t taken the time to attach and try it yet? 

Second, if you’re not using your existing tools to their fullest potential, why should you (or leadership) believe you’ll use your new AI-powered technology to its fullest potential? Before asking for more resources, it’s best to show you’re maximizing the existing resources with which you’ve been entrusted. This is not to say you don’t need or won’t benefit from implementing new AI capabilities—you undoubtedly will. Rather, just maximize what you have before adding more technology to your stack. 

Implementing AI: No one-size-fits-all approach

With all the hype around AI, it’s no surprise we’re all ready and excited to see how it can transform our contact centers. In every webinar related to AI in the contact center, I’m asked the same question, “Where should I apply AI first?” and each time I have to give the truthful, yet vague, answer of, “It depends.”

We all wish there was a standard AI implementation handbook contact centers could follow, but there is no one-size-fits-all approach. Just like no two contact centers are identical, neither are AI implementations. 

Each contact center is unique and different, and so each AI implementation will start, progress, and look differently. However, all contact centers should start by following the steps in this blog and making sure they’re AI-ready before embarking on their journey.

Be AI-ready with Sharpen

Laying the foundation for your AI journey is critical, and it’s best to be primed and ready to go when the opportunity arises. The Sharpen team is here to help you ensure you’re ready to implement new AI-powered capabilities and reap their full benefits to transform your contact center. 

To gain more practical insights on how you can use AI in your contact center, meet with one of our experts today!