2024 Trends: How AI Will Reshape Customer Service Teams

ChatGPT and generative AI hit the mainstream a year ago. In 2023, there was a ton of hype and noise about the power of AI to reshape everything on customer service teams. But for all the hype, change has been slow. For many CX leaders, 2023 was a year of dipping a toe in the water of automation and AI. 

As 2024 begins, it’s clear that AI won’t eliminate customer support teams – but it will reshape them. 

Yes, customer support teams will be smaller, as artificial intelligence can now handle many of the simpler tickets. 

There are many more ways that AI will transform the way support teams are structured and operate. 

In 2024, AI will provide customer service teams an opportunity to rethink the roles of both people and technology, to reimagine the entire customer experience. CX leaders will find creative and impactful ways that their customer service teams can work with AI effectively.

If you want to implement AI successfully across your customer experience, there are four major things you need to grasp—four things that have dramatic impacts on your customer service team.

1. AI enables CX teams to completely rethink the way they measure quality and customer satisfaction

Traditional ways of measuring quality in customer support come at it from two angles:

  • Customer satisfaction (CSAT), as the main KPI providing direct insights into customer sentiment about how a specific interaction is handled. 
  • A quality assurance (QA) program where teams define a scorecard that covers what they believe are the most important customer service behaviors, then regularly evaluate a small sample of interactions. These evaluations are then used to identify coaching opportunities and process improvements. 

Both of those approaches have shortcomings. 

CSAT ratings typically include feedback about established processes or the product—things an agent can’t easily influence, even if they provide a fantastic experience. And scaling a QA program can be very time-consuming. Either you analyze a small proportion of interactions, hoping they give you enough insights to work with, or you evaluate a higher proportion, which requires building out a large QA team. 

Pulling deeper insights from your customer feedback wasn’t easy either. 

Voice of the Customer (VoC) projects used to require dedicated data analysts responsible for processing mountains of customer feedback data and presenting the results in a digestible format for customer service teams. Using this kind of intensive feedback analysis to measure support quality was unreasonable—it was used only for larger business priorities.

AI has completely changed this entire picture. 

Suddenly, VoC tools have become incredibly accessible at a fraction of the cost.

These VoC tools—like Level.ai, Klaus, and Observe.ai—integrate with your support ticketing tool and can analyze 100% of your customer interactions—with no additional effort being required. 

They’ll provide insights about the biggest contact drivers and trends in customer feedback, but they also let you measure customer sentiment and quality in basically real time. They eliminate the overhead of a massive QA program—although you’ll absolutely still need humans involved—while giving you an even greater depth and quality of insights.

Rather than having a team of QA specialists manually reviewing individual interactions, your team will shift towards a few VoC analysts monitoring your entire customer experience. Assisted by AI, these analysts will have a clear understanding of the trends across all of your customer conversations, giving you insights and tangible ways to improve your customer experience. 

These tools will enable you to:

  • Catch issues before they cause significant harm – for example, a common bug or a broken coupon code can be detected and fixed quickly
  • Coach team members in near real-time based on customer sentiment analysis
  • Identify common product issues, so the CX team can pass on feedback to other departments
  • Identify trends in agent behavior, so new trainings can be rolled out

… and much more. 

But they are costly, and not all customer service teams will rapidly adopt them. Unless significantly cheaper versions come on the market, CSAT and traditional QA teams will remain critical tools in a CX leader’s toolbox. 

2. You need to develop new, highly skilled roles

You can’t provide great customer service simply by rolling out an AI solution. AI is powerful, but it works best in tandem with humans who have significant expertise in their fields. And that’s why many customer experience teams are creating dedicated roles to improve their AI implementation. 

Those roles include:

Conversation Manager 

Pioneered at companies like Intercom, Conversation Managers focus on the whole customer experience journey – ensuring humans and AI are working together to provide a seamless customer experience. 

Knowledge Manager 

Knowledge Managers are responsible for keeping the knowledge base up to date. Everything your AI does is based off the content it’s trained on, so an outdated knowledge base is a sure path to a low ROI and a bad experience.

With AI in place, a Knowledge Manager’s responsibility also expands into making sure that the content is not only written for people, but also in a way that makes it effective for training AI systems. 

Whether you dedicate someone to this role full-time or have multiple team members pitching in, optimizing your knowledge base has to be a top priority for effective AI usage. 

Voice of the Customer Analyst 

VoC analyst is a role that’s been around for some time, but is undergoing a massive transformation. Given the capabilities of AI-powered VoC tools, this role is shifting into a replacement for traditional QA analysts. 

Rather than conducting audits of individual interactions, VoC analysts continuously monitor VoC systems. Their focus is on extracting valuable insights and trends from customer feedback, which in turn inform training programs and drive process improvements.

AI Calibration Specialist

This is a dedicated role responsible for continuously monitoring and fine-tuning the performance of AI bots and other automations, ensuring that they deliver accurate and contextually relevant responses. 

AI Prompt Engineer

This role is more technical than the AI Calibration Specialist. They’re responsible for correcting the AI and refining the underlying code that it’s based on. They might also try to break the AI using “red teaming,” a systematic analysis to identify vulnerabilities, weaknesses, and potential areas of improvement by simulating the actions and tactics that a malicious actor might employ.

3. Your agents will shift from generalists to specialists

Any effective AI solution will be capable of handling customer tickets requiring a broad but basic understanding. 

What does that mean for your team? Your agents will have to level up by focusing on more complex tickets, which requires a deeper level of specialization. That means: 

  • They’ll need more training. Sometimes they’ll need significantly longer to build the same level of confidence as they might have been able to in the past. 
  • You’ll have to lower your occupancy expectations. Agents might need more breaks to recover between calls or tickets because the cases they handle are draining.
  • They should be upskilled, so they have specific areas of expertise. The cases that will make it past the AI will require more in-depth knowledge.
  • Agents might take on more revenue-generating roles. If conversational AI buys you some extra capacity, shift your agents from providing retention-based resolutions to revenue-generating activities. For instance, have them start proactive chats to improve cart conversion in e-commerce. 

4. You can dramatically improve your speed-to-competency

Conversational AI tools like chatbots are often customer-facing. They’re built to interact with your customers. 

But there’s obviously been a massive boom in tools powered by generative AI intended to assist your agents: by summarizing their tickets, helping them rephrase or rewrite macros so they’re always personalized, or pulling related answers from previous tickets.

Working with AI tools internally increases the capacity of every one of your agents. Letting your agents interact with AI systems before you roll them out for your customers is also one of the best ways to ensure new systems are trained properly. 

The important thing to keep in mind here is that different agents will respond differently to AI tools. 

An AI assist tool that suggests actions to your agents can be very helpful for new agents, who might appreciate the extra guidance. It will enable new agents to get up to speed more quickly. But the same tool could be intrusive and annoying for tenured agents, who rather find it distracting. Studies have shown that AI assist tools provide fewer benefits for agents with 6+ months of tenure. 

Some tips for working with AI assist tools: 

  • Provide comprehensive training to show your agents how to get the most out of it.
  • Take a step back and let them play around with it freely. See what the adoption rate is like when you don’t push anyone to use it. Are they actually finding it helpful?
  • Compare the effectiveness and performance of team members who use it against the ones who don’t. It’s possible that people consciously avoid using it because they find that it doesn’t make them faster or allow them to deliver higher-quality responses.
  • If agents are performing better when they use it, turn them into advocates to encourage  buy-in from your remaining team members.

AI powered tools, implemented well, will positively impact many of the most popular customer service KPIs. 

Combine AI with a human touch  for exceptional customer experiences

AI should be transformative for your business, your customers, and your team. 

With all the hype around AI solutions in customer service, partnering with an experienced AI solutions provider often provides a massive opportunity. Peak Support can help you implement new AI tools, or optimize the ones you already have. 

Peak Support builds exceptional customer service and back-office teams for innovative companies. We deliver high quality support and extraordinary value in as little as 3 weeks​. If you’re interested in implementing new AI solutions or optimizing your existing tech stack, contact us

  • We’ve built a highly experienced team with the technical acumen and creativity to build transformational AI programs. 
  • We can build your AI solution quickly without you having to restructure your team first.
  • We hire the best agents so they can comfortably respond to and handle your more advanced tickets. 

The best quality in the business process outsourcing (BPO) industry, delivered by humans and enabled by best-in-class technology. Talk to our team today to see how we can help you with your new AI implementation.