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Giving chatbots and voicebots the context to recognize customers, understand their histories and preferences, and predict their next actions, enables automation and blended AI to make customer experience faster and more frictionless. For many organizations, that’s becoming a major driver toward digitization.
However, as with most change management programs, success means winning the hearts and minds of managers and employees. Many will perceive such technologies as threats. Yet, artificial intelligence (AI) doesn’t have to be a disruptive force. In fact, it can be just the opposite. The key is to look above and beyond the financial savings and consider how to humanize your AI strategies. Let’s examine two cases.
Creating a Compelling HR Enabler
The terms early adopter and innovator are synonymous with Norwegian company, DNB — especially when it comes to developing mobile and digital banking services. Their interest in AI is not necessarily to cut costs through automation, but more about releasing human power to create value elsewhere.
Initially, DNB rearchitected its customer service to be bot-first. Core to this was a blended AI strategy — welcoming customers and directing them to the chatbot service, with swift human intervention if their issues weren’t resolved. Enabled by exposing Genesys APIs to the Digital Media Server, this seamless handover showed a 30% reduction in agent-assisted chat. That’s a decent savings when you consider human handling costs can be up to 75 times more expensive than customers self-serving.
However, DNB is eyeing an even bigger return. They’ve been exploring how AI could enrich careers by replacing dull, repetitive jobs with more expansive and rewarding ones.
To help make the transition, employees are openly encouraged to apply for reskilling. The program has had early success, filling several freshly created data scientist roles. One of their first tasks will be to analyze and improve AI-enabled customer journeys. Other new positions under consideration include AI trainers. So, instead of trawling through page after page of mind-numbing transcripts, agents can learn how to train and manage bots to do the heavy lifting. What’s next: AI-powered forecasting and scheduling, perhaps?
Developing AI Capabilities In-House
Dutch-based financial services group Achmea is also taking a more holistic approach. They started using chatbots around five years ago and have since developed a next-generation model using Genesys Bot Gateway.
Benefits include a 15% drop in handle time for health insurance-related contacts. Like most businesses, they have specific challenges. Such as training an influx of new hires, which tends to happen in October. Then Achmea must deal with huge traffic spikes at the end of the year. Chatbots have made managing these events much easier, too.
Its leadership felt it was important to develop an in-house capability. So, they created a whole new AI department with over 20 people — mostly from internal candidates, augmented with a sprinkling of external hires.
Set up as an autonomous trading unit, the department acts in a consultancy role, working closely with lines of business to design and deliver AI projects. Achmea will also complete the loop by leveraging contact center data and analytics to improve bot performance. The goal is to generate revenue, initially through internal transfer charging, and eventually becoming 100% self-funded.
To learn more about Genesys AI, check out the webinar, “5 things to consider when building chatbots.”
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