Customer service is evolving thanks to AI and machine learning. But as more companies embrace the technology to enhance their support functions, many don’t see the magical returns they expect just yet.
In its latest state of AI report, McKinsey found companies earning the highest ROI are more likely to follow several best practices, from strategy, data, and models to tools, technology, and talent.
This finding raises some questions. If AI proves the most successful when tied to big-picture business goals, is AI the sole innovation—or does innovation also depend on our approach?
Cutting through complexity
There’s no doubt technology-driven innovation in customer service has improved what we can do with support and how we show up for customers.
When I started in software support at InterSystems, we didn’t have a digital system. We had massive filing cabinets. We had pieces of paper and notebooks. That was a long time ago, before AI in customer service was even a concept.
When a customer had a problem, we had to rifle through filing cabinets to find everything we’d recorded about what we built for them. That was the only way we could backtrack to figure out a problem. At that point, innovation meant ditching paper. I wrote our first support application in 1988 and we’re still using it thanks to my colleagues who constantly enhance it.
These days, software solutions are much easier for users to work with, but they’re much more complex to support. In support, cutting through complexity means having access to as much information as possible. And the same is true for users – if you’re in manufacturing, it’s supply chain visibility. In healthcare, it’s interoperability to have a complete picture.
From a support perspective, the complexity of software solution and the systems in which they operate continues to grow at an increasingly rapid rate. Think about the core components: security, interoperability, performance, self-diagnostics, data quality, user interface, operating environments, development languages, 3rd party components, on and on.
From speaking with senior leaders of large support organizations, there’s a strong desire for analytics and – more importantly – insights into their data. They want this to improve the customer experience, reduce the need for support, and to pivot to proactive customer experiences.
How can we get there?
Using technology to reinforce, not replace
Some organizations might believe they’ll eventually be able to replace their entire support package with AI customer service solutions including AI chatbots, generative AI (LLM), and self-help. I don’t subscribe to this thesis.
Chatbots and self-help are useful for high-volume repeatable issues like password resets, getting started, and simple transactions. Generative AI has value in summarizing long streams of text and other data, but it’s still in a formative phase.
Some of these companies may overestimate the technology, but the main reason for many that hope to offload support is simple: they see the department as a cost center and they see technologies as a way to reduce costs. Customer experience innovation supposedly comes from reassigning responsibilities to a faceless workforce.
The cost center belief is an old one, and it’s fundamentally wrong in my opinion. There’s tremendous value in great customer service.
That’s why we’ve always taken a “do what it takes” approach at InterSystems. Making our customers successful makes us successful. The human touch is fundamental to that success.
So, I ask – how can technology help our people do a better job with less effort? Here are a few examples:
- Machine learning can identify potential anomalies in large amounts of data (i.e., log files)
- Chatbots can call, categorize a request, or dispatch human support
- AI can help identify overlap and request-related information
- Predictive analysis can leverage historical data to develop future insights today
- AI can identify opportunities to make proactive recommendations
How can these technologies help your organization to deliver better experiences and increase proactivity? I believe that technologies, such as AI, are no substitute for skilled support agents who can nurture relationships and navigate high-touch issues through empathy-based social skills and strategic thinking. AI can’t do any of that.
The impact of AI in customer service
Organizations that have a strong culture of service should consider high-touch customer support programs which combine AI with human-led help.
In an increasingly complex digital landscape, fulfilling the customer service obligation also means embracing new tools and technologies to help agents deliver solutions faster. When it comes to innovation, customer experiences shouldn’t suffer.
That’s the real power and promise of AI and machine learning in support – empowering our customer support team to work with our customers more effectively, not replace them entirely.
When paired with a strong culture of service, AI’s capabilities don’t just elevate the customer experience. They ensure we can deliver on a true promise of long-term partnership. That’s my approach to #InspiredService: we succeed when our customers succeed.