What challenges and opportunities come from using artificial intelligence in customer communication? What influence can it have on customer satisfaction? A new study considers artificial intelligence from the perspective of executives, customers, and employees, providing a new view of the trending topic of AI.
How are companies using artificial intelligence to optimize the customer experience? How are customers receiving comprehensive implementation? What experiences have service workers had with artificial intelligence, and how does it affect their role and daily work? What do companies need to do to successfully utilize artificial intelligence to increase customer satisfaction? These questions are at the heart of the British Institute of Customer Service’s study “The Heart of Artificial Intelligence. Enabling the Future of Customer Experience.”
One central finding of the survey is that companies are mostly employing artificial intelligence with the motto “test and learn,” and so far only for relatively few applications. Only ten percent of the companies surveyed claimed to make extensive use of AI, whereas nearly 20 percent only utilize it in certain situations. 14.4 percent are still yet to use any AI at all, but are planning to implement it. Roughly 23 percent have no plans to use AI in their company.
Benefits and applications of artificial intelligence
Companies wanting to introduce AI give five reasons:
Optimization of productivity and efficiency
Better customer service
Better business decisions
Preparation for the future
And companies already using artificial intelligence give five of its main applications:
Analytics to support decision-making
Analytics to support employees
Direct customer interaction
To experience new paths, products, and services
Above all, it’s about using AI to supplement and support the employee team by, for example, automating processes or accessing relevant information through analytics. The goal is not to replace employees with AI, however. Tasks like processing complaints, consulting on high-price offers, and technical support still require the engagement of well-trained workers.
Qualification requirements climbing
For this reason, organizations require a higher level of expertise in customer support. As routine tasks are increasingly becoming automated, customer support staff are being tasked with the more demanding jobs.On the other hand, they need expertise in technology and data to, for example, integrate, interpret, and utilize structured and unstructured data sets. They also need to ensure that the use of AI is based on a deep understanding of customer experience and needs.
These new demands result in an increasing need for qualifications, and not just when employees have started their careers. As increasingly overarching skills are required, students of the arts and humanities, for example, should have access to a broader range of disciplines, particularly in the field of data and technology, according to the authors of the study. The overarching framework for cooperation between organizations, schools, and universities needs to be improved. In addition, companies need to become more proactive in defining and developing skills requirements.
And the customers?
Most customers would prefer to talk to a person rather than a bot.Roughly 13 percent would even forego using a product or service if they had to talk to a bot rather than a human customer service worker.18 percent would always want to talk to a person, especially in sensitive situations. For around 22 percent, however, having to interact with a chatbot would make no difference to their relationship with or view of the company.
The important thing is that companies are transparent when addressing customer concerns about data, security, and privacy. Customers need to feel that artificial intelligence can not only reduce costs, but also improve customer service.
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Skepticism among employees
The interviewed employees view artificial intelligence with “a mixture of apprehension and excitement.” Roughly 47 percent of employees in companies that use artificial intelligence have had experience with it in their day-to-day work – mostly through the automation of internal processes, support of customer advisors, image recognition, or analysis of voice data. These employees tend to think that artificial intelligence has improved their job as well as customer experience. The remaining 53 percent said that artificial intelligence has had little impact on their work and the experiences of customers.
In addition, the employees surveyed believe that artificial intelligence represents both an opportunity and a threat to future jobs, and many are uncertain about their futures. However, employees and managers are agreed that employee dedication and commitment are vital to the successful introduction and utilization of AI systems.This makes it important that companies communicate transparently, include employees in piloting and testing, and train them accordingly.
Key factors for successful deployment
The authors of the study have come up with various key factors that are crucial for the successful use of artificial intelligence in the area of customer experience. They include:
Building up knowledge about artificial intelligence at the board level to assess the impact on retail, customer satisfaction, ethics, and reputation.
Defining business opportunities in terms of customer needs, processes, required data sets, and new technologies.
Building data sets that support the effective preparation of artificial intelligence.
Developing skills in key areas (higher order customer service, data and technology applications, integration of technology, and customer experience).
Piloting, testing, and learning from the implementation.
Ensuring transparent compliance and governance to protect trust and reputation.
Involving employees and participating in the development and testing of artificial intelligence.
Building customer trust and confidence through transparency, proactive communication, and engagement.
Developing flexible organizational structures that enable hybrid, cross-functional teams to accelerate the preparation of artificial intelligence.