Since the very beginning of commercial artificial intelligence products, customer service has been considered an obvious place to deploy AI, replacing those (relatively) costly and squishy humans with nice, clean, scalable computer software.
Certainly there have been some large-scale AI-powered customer service successes, but there have also been many costly failures.
So what’s the current state of play in the AI marketplace? Should customer service professionals in 2020 be afraid of losing their jobs to AI? Let’s find out.
What do we mean by AI-powered customer service?
Artificial intelligence is a broad term that can encompass many different technologies. Regarding AI in customer service, typically it refers to two core technologies: Machine Learning and Natural Language Processing (NLP).
Machine Learning is a form of AI that involves giving machines access to sources of data and having them “learn” the information without being explicitly programmed. Customer service generates large amounts of reasonably structured data, e.g., customers asking questions and support teams answering those questions.
Machine Learning then allows a system to take in that data, comprehend it in some form, and train itself to answer customer questions. Often that means using additional technology like Natural Language Processing (NLP).
NLP is how computers are able to “understand” written human languages in customer service emails, phone calls, or chats, enabling software to make decisions or take actions based on that understanding.
There are many more individual technologies that tend to be grouped under the AI banner, but the most prominent face of AI-powered customer service is the chatbot. A chatbot is a system that is intended to allow human customers to converse naturally with a piece of software and receive assistance or answers.
Chatbots are only one way to put AI into practice as a customer service tool, and even within the chatbot world, there are many variations. Let’s take a look at some commonly used models.
Different models for AI-powered customer service
The reality is likely to be far less dramatic, but AI can be engaged in many forms within customer service. There is no “best” way to implement AI; instead there are different approaches to be considered.
Before you you implement live chat as a customer support channel or choose live chat software for your business …
Replace the human with a convincing bot
This model is what underlies the “robots will take all the customer service jobs” fear. It assumes that technology will soon be so advanced that no humans need to be involved, and customers will be able to converse with a bot and never know or care whether it’s a person or a piece of software.
- Advantages: If you have the considerable scale and resources to implement and continually improve a high-quality system, it can lend to long-term cost savings and allow for faster customer service in many locations.
- Disadvantages: For most situations, the technology isn’t quite there to provide high-quality service when compared to human-powered support. If you’re not a huge enterprise, it’s unlikely to be feasible today.
AI in the front, people in the back
Any customer service professional knows there are plenty of repetitive questions to be handled. This model places AI tools as the first line of support to customers, handling the most common and most simple questions. Anything more complex or that fails to be resolved is handed off to the human team.
- Advantages: When well-implemented, this model allows scaling up the front-line support volume at a low cost and reserves the more expensive, creative, human-powered support for second-tier questions.
- Disadvantages: The human support team will often find themselves dealing with customers who have already had a bad experience with a chatbot that failed to help them. It also means missed opportunities to try different approaches and learn from the more common questions.
Using AI to augment humans
Think of this model as the “Tony Stark + Jarvis = Iron Man” approach. It keeps support teams directly in contact with customers, but it makes those teams faster and more effective by equipping them with AI-powered contextual data and solutions.
It places AI in the role of advisor, collecting all the information and sorting through it, while still allowing the support agent to decide what to pass on to the customer and how to do it.
- Advantages: This approach retains person-to-person service and allows for support teams to connect with customers and make judgement calls about the right approach, making them more informed with less effort.
- Disadvantages: Even though each agent can be faster and more effective, you do still need to invest in hiring and training the right people to take advantage of that power.
At Help Scout, we believe that for small and medium-sized customer-centric businesses, the best role for AI in delivering customer service is to empower the people who provide that service. Our CEO Nick Francis explored this idea with Benoit Gagnon from AI customer service software company Miuros:
As Nick and Benoit discussed, there are many ways to obtain value from AI in customer service without having AI ever reply directly to your customers. For example, AI could be used to:
- Show your agent the most useful knowledge base articles based on the customer’s question.
- Automatically categorize or tag incoming questions to save time.
- Discover patterns in your customer service reporting that might better help plan schedules or manage your team.
- Help triage incoming support and suggest priority cases.
Of course, no real-world implementation of AI-powered customer service will fit cleanly into one model. Every company will need to look at their existing capabilities and the tools and services available in the marketplace.
So what does the AI world look like in 2020?
The state of AI play in 2020
There is undeniable momentum around AI in 2020. Google’s Contact Center AI is now generally available and claims to have over 1 million developers working with it. IBM offers Watson, and both Amazon and Microsoft provide AI as a Service platforms.
Most AI services were initially aimed at enterprise companies, which have both the resources and the enormous training data sets to make effective use of the systems. For smaller businesses, there are still options to explore.
However, the growth in these AI service platforms will continue to drive down costs and offer new and innovative ways to add AI capabilities into business workflows, including customer service.
Companies like Miuros and MonkeyLearn are building tools that are designed specifically to help customer-facing teams be more effective and informed. We anticipate this sort of focused AI becoming more common in the next year.
So, is AI coming for your customer service job?
Well…maybe eventually, but probably not soon. Certainly there are “Future of Jobs” reports like this one, which forecast a net loss of nearly 10 million jobs by 2027 as a result of innovations in AI. But that’s only one possible future, and in the tech world, it’s a long way off.
It’s not only customer service professionals who are looking ahead to a world where AI is embedded in their field. Lawyers are having the same discussion and coming to a similar conclusion: The people who can adapt to use AI as a tool to deliver better work will thrive.
What do support professionals think about this future? For the most part, they think it’s fantastic. Any question a chatbot can answer on its own is probably monotonous work for a support professional.
The vast majority of support pros — 79% — feel that handling more complex customer issues improves their skills. A further 72% feel they have a bigger impact in the company when chatbots take on the easy questions.
AI can elevate and release customer service professionals into new roles that develop their skills, increase their impact, and improve their ability to participate in proactive, revenue-generating activities.
The biggest opportunity for bots and AI in high-value customer service is helping to make our human-powered support more informed, more responsive, and more efficient. The less time we spend searching past conversations and repeating ourselves, the more time that’s left for human connection and relationship building.
Artificial intelligence is (part of) the future of customer service
While the marketing around AI can be a little breathless, we’re still in the early days of artificial intelligence. It has clear potential to help companies deliver better service, and even at its best, AI will never be a “switch it on and empty out the office” type of product.
For most companies, there are huge customer service improvements still to be gained in more mundane areas like smarter processes, cleaner data capture, CRM capabilities, and providing your team with contextual data.
Doing that work now will put you in a good position to take advantage of AI tools as they become more capable and feasible, and your role can become more interesting and impactful.