Introduction

There can be no doubt that AI is dominating discussion around customer service across a range of industries. According to Bloomberg, generative AI alone could grow at a CAGR of 42% to 2033¹. This comes at a time when standards of customer service are undeniably in decline, at their lowest level since 2015². The flurry of media interest and industry events around AI is due in part to the fact that this nascent technology is often put forward as a single answer to numerous complex challenges around the customer experience.

But despite all the recent hype around AI, this is nothing new. Indeed, the contact centre industry has long been a leader in the adoption of automation and self-service. The first Interactive Voice Response (IVR) deployment in a contact centre, where you interact with a machine to indicate your intent, occurred as far back as the 1970s, after which voice recognition as we would now recognise it started appearing in contact centres during the 90s and early 2000s.

In reality, the successful adoption of AI within contact centres is just as much art as it is science, with many factors at play: brand values, employee sentiment, legacy systems, and customer personas, to name just a few. Whilst machines certainly have their place in this journey, it is the human element that will determine what that place is, and the best methodology for the successful adoption of AI and other new technologies.

Taking all this into account, getting started on the AI journey can often be overwhelming, and the consequences of getting it wrong can be severe, both from a financial and reputational perspective. Customers may walk away, employees may become disenfranchised, and IT teams will ultimately be left with a failed project and a technological “orphan”.

In this whitepaper, Exponential-e will provide you with a practical guide to striking the perfect balance between humans and machines in the contact centre, with our methodology divided into four phases: Investigate, Interpret, Implement, and Inform, as shown in the diagram:

The Exponential-e Methodology for Implementing AI Technologies.

By the end, you will have the tools you need to establish what that balance looks like for your organisation and begin transforming the customer experience in a thoughtful and considered way, inspiring brand loyalty and sustainable growth. This guidance is all drawn directly from our many years of experience executing such transformational projects for organisations at all levels, across a range of sectors.

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¹ Generative AI to Become a $1.3 Trillion Market by 2032, Research Finds | Press | Bloomberg LP

² It is mission critical to turn around the decline in UK customer satisfaction ⋆ (instituteofcustomerservice.com)