Consumers are ambivalent about artificial intelligence. According to data collected by O’Reilly, majorities of consumers embrace AI in applications like smart home technology, home security, and travel booking. About half accept the use of AI assistants.

O’Reilly’s data shows consumers are far less trusting of AI in the workplace. Just 22% favor AI-driven automation processes. Only 11% favor using AI to drive business decisions, and there’s near-unanimous opposition to this use case in the logistics sector.

These attitudes may reflect an incomplete understanding of AI’s potential to improve the customer experience (CX), both by directly enhancing interactions with customer service agents and other customer-facing staff and by sharpening and accelerating insights on the backend to improve targeting, personalization, and product. Enterprises certainly see the potential here.

According to Gartner data from 2019, the number of enterprises using AI in some capacity rose by 270% in the prior four years to 37% of all enterprise organizations. The share is undoubtedly higher today.

The universe of customer-facing applications for artificial intelligence is growing fast. To fully realize its potential, business leaders need to look for use cases that enhance the customer experience rather than internal solutions that the customer never sees or feels. The goal here is to prove, one customer at a time, that AI is an ally.

How AI Benefits the Customer Experience

Let’s explore four AI applications with clear benefits for the customer experience.

1. Natural language processing illuminates audience and customer sentiment to improve product development and targeted marketing.

In 2019, apparel giant Urban Outfitters began building out a centralized customer experience platform that used natural language processing to turn an avalanche of user feedback into legible customer sentiment insights. Other brands have followed.

These insights aren’t necessarily profound and don’t immediately show up in iterative development processes. They’re often obvious, like “frustrated” or “excited” tags on feedback messages. But AI can sort through massive feedback volumes far faster than customer support agents and product teams, who have better things to do with their time anyway.

2. AI-enabled workflow automation frees agents to focus on the customer, not notes or spreadsheets.

On this point: The highest and best use of a customer support agent’s time is any task that directly contributes to successful ticket resolution. Depending on the support environment, these tasks can include walking a customer through a troubleshooting process by phone or live chat, researching a CX issue in preparation for a callback, or escalating issues that they’re not trained to address. They don’t include background processes or compliance activities like updating customer contact information, writing up call summaries, or taking notes in real-time.

A Zogby Analytics survey commissioned by cloud-based contact center platform Five9, found that 71% of customers agree that some kind of technology adoption like AI or machine learning will be needed to improve the CX.

With this in mind, workflow automation solutions are turning to intelligent virtual agents to automate the essential but time- and attention-consuming tasks, freeing human agents to give each customer their undivided attention. Attentive agents are much more likely to deliver relevant, helpful customer support in the moment — and reduce callbacks later.

3. AI-powered data analytics reduce analysts’ workloads, help departments collaborate across the organization and generate customer journey insights that humans may not see.

The same capabilities that allow AI-powered applications to sort through vast feedback sets to quantify and categorize customer sentiment also enable a wider array of CX-enhancing data analysis activities.

Pointillist broadly defines these activities as “customer journey analytics” and their endgame as “data unification” — the construction of an all-encompassing single customer view that incorporates the entire set of data shared during the customer journey. Pointillist’s 2020 State of Customer Journey Management and CX Measurement Report found a near-majority of customer experience leaders agreeing that the lack of a single customer view (and a corresponding single view of the customer journey) was the biggest obstacle to measuring and refining the customer experience.

A single customer view allows businesses to enhance the customer experience — manually and through AI-enabled automation and personalization — at every touchpoint or step of the customer journey. The automated processes responsible for collecting and analyzing its component data add value internally as well, by reducing analyst workloads and overriding (and eventually eliminating) organizational silos that hinder growth.

4. Automated, purpose-driven chatbots support and guide customers in real-time with minimal human oversight.

Customers shy away from generic chatbots because they’re aimless. They greet customers when they arrive onsite or ask them if there’s anything else when they appear ready to leave. Their work is helpful for brands’ efforts to gather prospect data and map the customer journey, but it’s not a value-add for the customers themselves. Instead, It’s annoying and frustrating.

To legitimately add value and improve the customer experience, chatbots need purpose. The State Farm mobile app earned a Webby award in 2020 for automating much of the claims process. Customers actually use this function because it’s easier and faster for them, too — because it improves the customer experience at a key touchpoint and removes friction from the relationship.

Customers want AI-enhanced CX. They just don’t know it yet.

Even as the set of customer-facing AI use cases grows, some customers themselves remain ambivalent at best about AI’s utility. Many want to believe that it can improve the customer experience but haven’t seen enough to be convinced.

For business leaders that have already committed to leveraging AI in customer service, marketing, and digital sales funnels, this sets up a pivotal challenge: to demonstrate convincingly to buyers and prospects that they want an AI-enhanced customer experience. Whether they know it yet or not.