AI becomes real in CX when it is invisible to customers

AI needs to be embedded as a core strategic element of every business process

Artificial Intelligence (AI) is not immune to the famous Gartner Hype Cycle and continues to attract speculation around its potential.

Recently, Google DeepMind CEO Demis Hassabis predicted Artificial General Intelligence (AGI) will arrive in five to ten years. While the broader implications continue to be debated, back in the real world of working with customers we are now moving beyond the hype phase. A lot of pilots are happening in the background, invisible to customers but are showing tangible progress. This reflects the old industry adage that the best technology is often invisible; what is clear in customer experience scenarios is that AI is beginning to have that effect.

Based on our internal projects and pilots across Customer Success, there are clear use cases for AI. Adopting or migrating ERP systems can be complex, especially if a customer is moving from an established on-premise environment to the Cloud. What we have found across the different stages of the lifecycle of implementing, onboarding and supporting our customers on their Cloud journey, is that AI can streamline processes, free-up staff to deal with more complex issues and provide more rapid responses to requests on demand. And this can all happen in the background while still improving the customer experience. For example:

• Over 100% capacity increase in the ability of the team to review complex code and a 25% reduction in the cost of resources required to accomplish this task

• 50% reduction in the initial effort to convert code, leading to an overall accelerated migration of complex code to the Cloud

• Over 30% of time savings to build high quality documentation for customer onboarding which not only improves productivity, but keeps the documentation consistent for every customer

Most importantly, these projects have built up our organisational understanding of AI and how it can potentially drive efficiencies and productivity gains. As a result of these pilots, we can share a number of key learnings:

• Data accuracy and integrity is crucial: when developing a customer onboarding tool, it was invaluable to have a clear knowledge base of support documentation and materials so we could be confident the AI would produce quality responses. Likewise, we are using AI with Gainsight to pro-actively identify customer pain points to manage risk and resolve issues before they become a problem

• AI without metrics is pointless: when evaluating where to focus efforts, there is always an element of trial and error. That said, given our focus on helping customers through their Cloud migration journeys, it is clear the projects which landed solved real problems and demonstrated tangible outcomes. Even if it looks like a cool project, be ruthless in rejecting AI proposals that do not solve real problems or pain points

• AI can accelerate transformation at scale: it was clear that using AI could dramatically increase the volume of activity we could undertake, such as automating the analysis and identification of legacy Visual Basic code. From a planning perspective, this should enable teams to be ambitious in goal setting, but it should be framed by robust methodologies – if the AI is operating autonomously you need to know it is operating within acceptable boundaries, which is why we ensure we have a human review the work that has been done

• Invisible to customers but still delivering value: by improving our internal processes and using systems like Gainsight to summarise key takeaways, insights and action points, we are freeing up our teams to concentrate on high payoff activities and the right next engagement. There should always be an element of qualifying how adopting AI will benefit customers, particularly in the world of customer experience. If it does not add value for customers, why are you doing it?

• Successful AI projects will disrupt: having the support of AI tools will free up resources for more complex and rewarding tasks. Equally AI can dramatically streamline steps in a process such as analysing code, which will change how your organisation works. It is crucial your teams are inspired to experiment with AI and embrace any potential changes. Your teams will be more invested in change if they see how it will benefit them and enable them to do more rewarding work.

The biggest takeaway of embracing AI in customer experience environments is start small but dream big. Using AI to identify legacy code has enabled us to build more than a tool. We now have a blueprint for scalable, automated quality assurance.

In another project we created a methodology for AI which could ultimately become a new benchmark for identifying and modernising legacy code. In the world of customer experience, AI must be seen as much more than a standalone efficiency tool. It needs to be embedded as a core strategic element of every business process that not only boosts productivity but fundamentally transforms how organisations like Unit4 deliver value to customers.

Michelle MacCarthy, is VP global customer experience; James Thomas is global VP customer success services at Unit4