How to Accelerate and De-risk AI-Automated CX

Savvy business leaders know that timing is everything when making changes to call center processes. AI integration is no different. Implement too hastily and run the risk of  poor execution that negatively impacts customer experience (CX). Implement too late, and you’ve fallen behind your competitors. 

Off-the-shelf AI tools are the safest route bringing the power ofAI into your current tech stack. These tools present much lower risk to your call center processes versus custom-built solutions. Custom development can be costly, time-consuming, and energy-intensive. A custom approach also does not easily lend itself to incremental testing which is vital to safeguarding your CX.

A smart, thorough implementation of AI into your CX journey can deliver  many benefits in short order, including reduced churn, increased sales, and lower costs.

The trick, of course, is knowing where to find the right tools—and knowing how to integrate them properly. Let’s explore how to do that. 

Understanding AI tools: a customer-first analysis

Accelerating your AI implementation while minimizing risk starts with understanding the different AI tools available and how to integrate them seamlessly into your existing solution stack. A customer-first analysis of each tool should be your north star for choosing the right ones—even if your ultimate goal is to cut costs.

Yes, improving CX and cutting costs can go hand in hand. With more effective AI-powered automation in your customer service, you can cut costs by reducing the number of contacts with human agents. On top of that, you stand to increase revenue by increasing customer loyalty. Happy customers are more likely to stick with you and recommend you to others.

But simply implementing AI tools for the sake of automation and efficiency won’t lead to that customer satisfaction. Think carefully about how your customers will experience the AI tools you deploy, and remember, your customers contact you because they have a problem that needs solving. Your goal of getting them to that solution more quickly and effectively should guide your AI strategy. You particularly don’t want to implement AI tools that actually become impediments to your customers accessing needed solutions.

Unfortunately,  almost 30% of US consumers blamed being unable to reach a human agent as a source of their disappointment with a brand. If your clients are reaching this point of frustration with your AI tools, it means those tools aren’t working.

AI tools strengthening human touch work best

Generative AI is outpacing all other AI tools for CX, and with good reason. Analyzing customer needs and using that information can speed up  problem resolution with less human power.

However, this does not eliminate the need for human interaction, and when your customer connects to an agent, that agent should be better prepared to address the customer’s needs quickly and efficiently. They can be with the data and call summaries that AI provides in advance of the agent’s contact with the customer.

Combining AI and human agents makes for the best CX experience. And, a seamless handoff to a live agent can be combined with other solution stack processes, like ecommerce, integration with Zendesk and other customer support services, shipment tracking, and mobile device compatibility. Optimizing your current tech ecosystem will provide the needed foundation to leverage AI.

Some smart customer-facing implementations of AI in your call center include translation  services to accommodate different languages and accent localization to mirror a customer’s accent, and live chat automation. Altogether, these solutions can enhance understanding and produce faster, more enjoyable interactions.

Your agents can benefit from AI integration on the back end too. AI tools can parse through large data sets to perform sentiment analysis that reveal customer emotions while also identifying areas for improvement. Predictive analytics can also anticipate customer behavior and probable needs for assistance. Each of these tools serve the customer, quicken the CX journey, and reduce the time it  takes a human agent to get to the heart of a customer’s issue.

While AI gets a bad rap as “an impersonal robot,” it can actually help personalize the CX journey. Even if your customer wants to speak to a human, using AI to collect data across various multi channel touch points can create a more accurate user profile. For example, you can incorporate past user interactions from chatbot dialogue and give human representatives a fuller picture of the customer before they start a conversation.

AI can harvest and analyze data in real time. Traditionally, call center interactions are recorded, then a quality assurance team will listen to a small subset of those calls, fill out scorecards, and provide training after the fact. With AI analysis, all calls are analyzed, scorecards are filled out automatically, and quality assurance team members can spend less time analyzing calls and more time driving training and product improvements.

Better data and faster access to it means a quicker, more efficient problem-solving journey. But, all of these tools must be implemented in ways that complement your current tech stack. Simply putting them in place without a broader strategy runs the risk of burning cash and resources on tools you may not need. Worse, it can complicate the CX journey, which is the antithesis of what you’re trying to do.

Upskill agents with AI

With AI bots, your agents can access information and training faster. For example, if you’re launching a new product, you’ll need to get your agents up to speed quickly on the product’s details. You could hold in-person or virtual training sessions over the course of two weeks. Or you can help your agents understand the product in a day or two with AI bots at the ready. Or you can do both, so live training is reinforced by bots on standby!

By training an AI model on a new product manual, for instance, a chatbot can become a single source of truth for product knowledge. So if a customer calls and asks a question that an agent doesn’t yet know an answer to, the agent can simply prompt the AI and receive accurate information.

Agents can be trained and guided in real time so they can learn new products and processes on the fly. Not only does that mean a better experience for your customers, it also builds employee morale and loyalty. Constant and easily accessible training and learning opportunities make for a better place to work.

Start your AI implementation journey with a trusted partner

Implementing AI tools can be a Herculean task if you don’t know where to start. Before looking at the latest AI technologies in the market, nail down the fundamentals of your CX journey – and areas for improvement. A CX strategy that leverages the right mix of tools, processes, and people can provide incremental value right away. 

More technically mature organizations may be in a better position to leverage AI out of the gate, but they still need to pay close attention to how they go about it. They may be tempted to build custom solutions. And while this may be the best choice for your business in the long run, a custom solution is labor-intensive, expensive, and time-consuming.

Another important consideration is that training AI models takes a massive amount of energy, which means it adds a significant amount of cost to your business before the AI tool is  ready to deliver higher quality CX, efficiency and cost savings.

From there, the costs of running a custom AI tool continue to add up. Between hardware costs like servers and NVIDIA chips, software costs to run everything, and human power costs like salaries to build and maintain the system, a custom AI tool is likely cost-prohibitive for all but the largest companies.

The carbon footprint of such tools is also astronomical. NVIDIA is set to ship 1.5 million AI server units per year, according to Scientific American. Running at full capacity, these servers “would consume at least 85.4 terawatt-hours of electricity annually—more than what many small countries use in a year.”

It’s vital to move quickly and adapt to evolving technologies, but it could take years to develop a custom AI tool. That’s why off-the-shelf tools are a great place to start. You can implement AI tools with lower risk and at a quicker pace.

CGS is a trusted partner that has guided companies just like yours through this often complex process. We start by assessing your unique CX requirements; then we coach you on tools and  common pitfalls to avoid. Once we figure out what your business needs are, we can help you deploy new AI processes into your current tech stack quickly and effectively.

Your AI solutions may include automation, big data analytics and insights, generative AI, or a combination of all three. During the implementation of these tools, it is vital to ensure the safety of your customers’ data—not only to build their trust but also to address one of the largest deterrents to effective AI use: customer data security.

Data breaches make the news, which means your customers are starting from a place of mistrust when it comes to confidence in responsible handling of their data. Any implementation of AI tools must include robust data management and safeguards for customer data.

The overwhelming promise of AI-powered CX automation stands to increase revenue and reduce costs, all while seamlessly improving the customer experience. Download our latest e-book for more tips on how to unlock efficiency with automation.