Use GenAI to make life easier for your employees and customers

Generative artificial intelligence (GenAI) is emerging as a productivity enabler, and cost savings and efficiency are becoming clear benefits of existing use cases in production. But the persisting noise around GenAI is that there is so much more benefit to creating additional value for customers and employees, and we’ve barely scratched the surface of its potential. At our HFS Research roundtable last quarter, supported by Movate, we huddled with 20 industry leaders to discuss the potential of GenAI for a simple, important, and not-so-easy-to-achieve goal: Make our customers’ and employees’ lives easier.

Complexities in our operations hinder customer experience

The premise of our roundtable discussion was, “Stop trying to delight customers! Just make it easy.” A famous Harvard Business Review article outlined the folly of pursuing “customer delight” when it doesn’t build loyalty and when basic processes and interactions are often riddled with hurdles for customers to overcome. The popularity of reducing customer effort to improve loyalty has since increased, but companies still struggle to get out of their own way when making things easier for customers.

“Complicated internal processes create complications for customers,” said Nadeem Saaed, Corporate Vice President, Digital Transformation and Operational Excellence at Verizon. When you observe customer sentiment, you’ll find it also reflects how employees feel, he says. So, putting employees first and understanding their hurdles is a foundation point for customer centricity.

Customer experience is most promising for creating customer value

Our research shows that customer experience (CX) holds the highest potential for GenAI value (see Exhibit 1). With all the promise of digital self-service, automation, and now GenAI, you’d think customer effort would be at an all-time low. But, the internal complexities mentioned above, plus confusion about which use cases make the most sense and how to implement AI solutions, have resulted in hesitation from business leaders. It won’t come as a big surprise that many initial pilots and initiatives for CX-focused GenAI solutions target the agents and employees servicing the customer to improve the employee experience (EX). The Movate team concurred that a major focus for clients right now is using GenAI to boost employee experience and productivity. Not only does this mitigate risks inherent in pointing GenAI directly at the customer by keeping a human in the loop, but it also allows companies to better understand GenAI’s capabilities and develop talent and expertise internally.

Exhibit 1: Leaders expect customer ops to create the highest value in the next 18 months

Sample: 104 enterprises actively exploring and deploying GenAI across the Global 2000
Source: HFS Research, 2024

We’re seeing the GenAI hype die down, and a clearer picture is emerging around practical use cases for the enterprise. As our EX=CX premise above indicates, GenAI-related improvements to CX start with the employee. Our delegates discussed pilots and initiatives already in production that help employees do their jobs more easily and efficiently. For customer-facing agents in the contact center, for example, we heard examples of GenAI improving processes like next best action and post-call work.

As these solutions evolve and improve, it seems we’re heading to a win-win-win of improved productivity, happier employees, and happier customers. As our colleagues at Movate suggested, another world of value creation is on the horizon, such as personalized messaging and advertisements or even total disruption of the contact center translation ecosystem as we know it.

Sid Victor, Head of Customer Experience Services at Movate, emphasized the importance of service providers becoming “ecosystem orchestrators,” guiding customers through the complex and rapidly evolving world of AI.

“This ecosystem approach has helped our clients to move beyond pilot programs to real projects significantly faster, focusing on areas like boosting agent productivity, deploying customer-facing virtual assistants, creating next best actions and offers, language translation, and several other ‘point’ solutions,” said Victor. “This practical, rapid implementation and value-realization focus also enables us to further our innovative commercial models, like outcome-based structures that directly share AI success and benefits with clients.”

The Bottom Line: GenAI is powerful, but it isn’t a panacea. Now is the time to invest in learning what GenAI can and cannot do.

So, it seems that GenAI can go a long way toward decreasing customer and employee effort, but we’re just getting started. Many enterprise leaders also resist the urge to focus singularly on GenAI, knowing full well that we still haven’t fulfilled the promises of basic AI and other tech that’s been emerging and talked about for years, such as cloud. So, while we feel the next chapter for the GenAI story will be to evolve from just productivity toward creation, it is not the whole story. Now, our call to arms must be to simplify our complexities and focus on better understanding our customers and employees so we can create better and easier experiences.