The potential for AI to transform contact centers has long been clear. And with each evolutionary milestone, the impact of AI becomes more real.
Automation across the customer service spectrum remains a fundamental driver of AI, but to understand its true value, contact center leaders must focus on specific use cases. Improving the customer experience may be the holy grail of AI, but no use case is more important than its impact on human agents.
The role of a contact center agent is no longer tied to the traditional model of responding to incoming queries as quickly as possible. This model creates a work environment where CX performance is poor, ROI is lacking, and agent turnover is a chronic problem.
How AI is impacting contact centers
Contact center executives are rapidly adopting AI. The focus of AI-first is to replace traditional models and strategies. As part of this change, contact center managers are likely to rethink the role of human agents and how they need to work with, rather than compete with, AI. While it is inevitable that AI agents will replace some human agents, new roles present greater opportunities for human agents to do more satisfying work and add more value to customers and businesses than ever before.
The key here is that roles will emerge based on tasks that humans can do that AI cannot. Human agents cannot match what AI does best: process data and recognize patterns at scale and quickly. However, humans are naturally better at areas that require human intuition, such as empathy, reasoning, and judgment.
Some of these roles are already in place, and the industry is opening up a wide range of new roles for contact center leaders. In a traditional model, titles like designer, integrator, orchestrator, trainer, and architect might not come to mind, but this is the glossary for an AI-first contact center.
These roles are aimed at helping human agents deliver better CX, but the skillset differs from the traditional model. Contact center leaders need to restructure their workforce. And business leaders need to reframe AI ROI in terms of what drives business value: capturing, processing, and analyzing customer data.
A new role for a new type of CX
It is clear that the role of human contact center agents will change. But what exactly are these new roles, and why will they become important as contact centers become AI-centric? Broadly speaking, human agent roles can be grouped into six types, divided into two types of functions:
One function is customer-facing, where human agents do the same thing they always do: interact with customers. Another feature is AI agent support. This new breed of contact center workers provides input behind the scenes, allowing chatbots to automate customer service in new and better ways.
AI tools enhance customer-facing roles
CX orchestrator
The traditional role of human agents responding to customers and their inquiries is being replaced by AI-powered experiences that empower agents to do more. In this Agent 2.0 role, AI takes care of the mundane elements of customer service and provides real-time insights to help agents deliver more personalized and targeted experiences that lead to better outcomes. This elevates the role of agents to strategic facilitators, or orchestrators, managing multiple AI inputs to guide customer journeys in new and effective ways.
Customer Success Facilitator
This new role is also more strategic, with agents not only focusing on customer service. AI is introducing new data into contact centers, especially from sales and marketing, giving agents a more complete picture of the customer-business relationship. This model is configured as follows customer successsuccess is defined by personalizing interactions that solve customer problems, optimize upsell opportunities, and drive brand loyalty and customer retention. AI enables this by providing real-time insights into customer needs, sentiment analysis that indicates purchase intent, and next-best actions for proactive engagement.
CX specialist
Contact center agents don't work with complete customer data sets. Also, before AI, agents had to assign subject matter experts, assuming they could reach them in time.
AI makes it easy to embed expertise into every interaction. This is a prime example of how AI can have a dual impact on contact centers. Unless low-skilled agents can be upskilled, AI will almost certainly replace them, but new positions will be created, including CX specialists.
AI not only automates routine CX tasks, but also creates new datasets with rich insights that are highly specific to products, regions, situations, and customer personas. This role requires a new skillset with domain expertise and critical thinking that only humans can provide, extracting insights from AI input to provide a more personalized form of customer service.
AI agents require technical support
conversational AI designer
Conversational AI is also a key term in AI-driven customer service. Customer service continues to be voice-centric. And as AI evolves, so does the value that can be extracted from conversations.
However, that value is only realized if bots (AI agents) can converse in a human-like way that makes customers feel comfortable. The more effective conversational AI is, the more self-service you can automate. This is arguably the most powerful driver of AI in contact centers.
Conversational AI designer is one of the new jobs in contact center AI that is not a customer-facing role. Contact center agents may take these jobs to improve their skills. However, these roles are likely to be filled by employees with AI and developer-based expertise in areas such as call flow scripting. These designers must ensure human-like conversations and use language and messaging that aligns with brand communication.
AI agent trainer
Conversational AI is just one component of an AI agent. At a higher level, trainers need to coach the overall performance of both the AI agent that interacts with the customer and the AI agent that assists the human agent, also known as the co-pilot.
Although AI has self-learning capabilities, humans are required for basic training to make AI agents effective. This represents a new role for AI-first contact centers with a focus on quality control. Common tasks include checking the bot's accuracy, screening for bias, adjusting the tone of language depending on the situation, and building empathy in responses. Equally important is training the bot to extract from every thread of an interaction and identify data points that can be translated into personalized CX.
CX data analyst
As the title suggests, this role is about the data itself, not how it is used to interact with customers. The data analyst role is not new, but it has a particular focus on CX.
Human reasoning, ambiguity analysis, and critical thinking continue to produce the best results, especially in the context of customer service based on meeting the needs of other humans.
While AI is generating an overwhelming stream of new customer data sets, the technology is not yet mature enough to be fully relied on alone to analyze the output. AI is good at pattern recognition and anomaly detection. However, human reasoning, creativity, ambiguity parsing, and critical thinking produce the best results in the context of customer service, which is still based on meeting the needs of other humans.
Contact center changes introduce new costs
These are just some of the roles that are emerging and changing as contact centers are transformed by AI. There will definitely be other roles as well. Jobs will be lost, but new jobs will be created to accommodate new models of customer service.
No matter how it unfolds, CX and business leaders will need to adapt to the impact of AI on agents. There will be training costs to improve agent skills, as well as new spending to hire AI-savvy employees, which contact centers now need. AI-driven automation continues to provide superior ROI. But human agents will remain at the heart of CX, both in customer-facing roles and behind-the-scenes work aligned with today's AI-centric customer service.
John Arnold is a principal at J Arnold & Associates and an independent analyst providing thought leadership and go-to-market advice focused on the business-level impact of communications technology on digital transformation.
