Customers today have high expectations, and it’s up to you to meet them. They’re used to highly digital and personalised experiences, which mean they won’t stick around when any interaction with your business doesn’t live up to this standard. In fact, 39% of Americans report having had a customer service experience so bad that they stopped working with a business altogether.
Making sure your customer is receiving exemplary service at every step in their journey is therefore critical. Ideally, you would have the insight and intelligent processes to ensure a good customer experience every time. Then, the customer journey could look something like this instead:
- Your customer engages with your business through a variety of touch points such as your website, social media, email, online chat etc.
- From this, analysis bots drive deep insights into this customer’s profile and sentiments across these interactions.
- Cognitive bots automate appropriate interactions through conversational AI so that the customer can receive immediate support.
- If necessary, this interaction is then escalated to a human agent, in which Gen AI bots support the agent by automating tasks and making recommendations, leading to a faster resolution.
- Workforce solutions have also worked in the background to analyze engagement volumes and peak surges to optimize performance across all service providers, ensuring this customer’s experience is timely, smooth, and satisfactory.
- ML-based insights then drive engagement strategies and rapid adjustments based on the customer’s demands/sentiments.
Here we have a customer journey where customers receive instant and satisfactory support, wherever they engage with you, and analytics work to drive productivity and innovate based on customer demands. Too good to be true? Not at all. This is customer service with Gen AI.
The Right Approach to Gen AI Adoption
AI is already a staple across customer care that has undergone digital transformation. But Gen AI has introduced new frontiers, enabling organizations to go further with their customer support. Gen AI has been seen to increase NPS scores by up to 120 points, make self-service interactions three times faster, and automate over 50% of interactions.
It’s pretty clear that Gen AI has significant benefits for organisations looking to improve their customer service. But it’s important to assess and address challenges you may face with implementation and scaling. Your Gen AI adoption should be anchored on three key design principles:
- Empower the ‘human interface’
- Embed ‘ethics by design’
- Actively address risks
Empower the ‘Human Interface’
Many panic when they hear about AI implementations, envisioning the human workforce being replaced by robots. Whilst Gen AI does automate processes, when it comes to customer service it’s also able to support and empower agent interactions, rather than replace them. Gen AI can offer real time support to human agents, live-sourcing information and making recommendations to help reduce call times and improve agent efficiency.
For many customers, human interactions are more desirable, with 52% saying human customer service agents are less likely to frustrate them than chatbots. And it’s true, initial chatbot technology has left something to be desired when it comes to understanding and empathy. But with Gen AI, this can all change. Through semantic analysis, Gen AI can tailor responses to a customer’s moods and challenges, removing the cold, robotic responses that can alienate.
Embed ‘Ethics by Design’
A key reason behind failed AI initiatives is a failure to embrace it by employees. In fact, 69% of employees haven’t used AI to support their tasks at work, suggesting more groundwork is needed to help employees embrace Gen AI in the workplace.
It’s essential to maintain trust and build confidence in AI initiatives. This means taking the time to explain what Gen AI actually means and how it can support and benefit workers, address any concerns, and foster a culture of learning. This helps create a smooth transition for implementing Gen AI and works to improve ROI.
In some industries, there are also concerns over the ethics of AI when it comes to compliance and regulations. In finance, healthcare, or legal operations, mistakes could be catastrophic, leading to litigation. It’s vital that from the get-go, Gen AI strategy and design is placing compliance at the core, and are created with a ‘zero error design’ as the goal.
Actively Address Risks
As with any tech implementation, there are risks to introducing Gen AI to customer service operations. But this doesn’t mean you should shy away from it. It simply means you need to ensure you take the right approach.
When considering implementing Gen AI, don’t run before you can walk. Map out potential use cases, asses their risk, and start with the lower risk initiatives. From here, you can build out your skills as an organisation in Gen AI, repeat, and improve.
Understanding the risks of implementing Gen AI is essential to mitigating them. From regulations to governance and model risk, thoroughly examining exactly how Gen AI could impact each of these components and the necessary measures to prevent wrongdoing is a key step in establishing any Gen AI implementations in customer service.
The Future of Customer Experience
Gen AI is set to play a significant role in customer service, and for many organisations already is making a big impact for delivering on customer demand. But devising the right strategy and design is just as important as deciding to implement in the first place.
Looking for the right partner to transform your customer service? At Sutherland, we practice what we preach. Our experience-led design, next gen tech, and domain expertise combine to create exemplary customer experiences.
Learn more about how Sutherland’s AI-powered solutions can transform your customer experiences and drive business success
Sriram Panchapakesan is Sutherland’s CEO for Telecommunications, Media, Technology, Energy, and Utilities. Sriram has over 25 years of experience in CXO advisory and a strong track record in driving product engineering, analytics, and AI initiatives across the telecom, media, technology, manufacturing, and natural resources industries. He specializes in building and leading high-performance teams to deliver technology-driven business and digital transformation, as well as IT cost optimization programs.
Jeff leads our Customer Experience and Contact Center Transformation enabling impactful change.
