While AI spawns new customer-facing and AI support roles, contact center leaders must consider the costs associated with retooling and upskilling their workforce.
The potential for AI to transform the contact center has long been evident. And, with each evolutionary milestone, the AI effect is becoming more real.
Automation across the customer service spectrum remains a fundamental driver of AI, but to understand its true value, contact center leaders need to focus on specific use cases. Improving customer experience may be the ultimate objective with AI, but no use case is more important than its effect on human agents.
The role of contact center agents can no longer be tied to the legacy model of responding to incoming queries as quickly as possible. That model yields poor CX outcomes, a lack of ROI and a working environment where agent turnover is a chronic problem.
How AI is affecting contact centers
Contact center executives have adopted AI rapidly. An AI-first focus is replacing legacy models and strategies. As part of this shift, contact center managers may re-think the role of human agents and how they need to work alongside AI rather than compete with it. While AI agents will inevitably replace some human agents, new roles present bigger opportunities where human agents can have more satisfying work and add more value to customers and the business than ever before.
The key here is the emergence of roles based on tasks that humans can do well and AI cannot. Human agents cannot compete with what AI does best, which is processing data and recognizing patterns at scale and speed. But humans are naturally better where human intuition is needed, such as empathy, reasoning and judgment.
Some of these roles are already in effect, and the industry is seeing a range of job titles that are new for contact center leaders. Titles like designer, integrator, orchestrator, trainer and architect may not come to mind in legacy models, but this is the lexicon of the AI-first contact center.
While these roles aim to help human agents provide better CX, the skill sets are different from legacy models. Contact center leaders will need to re-tool their workforce. And business leaders will need to re-frame their AI ROI in terms of what drives value for the business, namely capturing, processing and analyzing customer data.
New roles for new forms of CX
Clearly, the role of human contact center agents will change. But what exactly are these new roles, and why are they important as contact centers become more AI-centric? At a high level, these roles for human agents can be grouped into six types, split between two types of functions.
One function is customer-facing, where human agents do what they've always done: interact with customers. The other function is AI agent support, where this new breed of contact center worker provides behind-the-scenes inputs so chatbots can automate customer service in new and better ways.
AI tools enhance customer-facing roles
CX orchestrator
The conventional role of human agents engaging with customers and their queries is giving way to an AI-powered experience where agents can do so much more. In this Agent 2.0 role, AI handles routine elements of customer service and provides real-time insights to help agents deliver more personalized, targeted experiences that lead to better outcomes. This elevates the agent's role to a strategic facilitator -- or orchestrator -- managing multiple AI inputs to guide customers on their journey in new and effective ways.
Customer success facilitator
This emerging role is also more strategic, where the agent isn't focused solely on customer service. AI is introducing new strands of data into the contact center, especially from sales and marketing, where agents have a more complete picture of the relationship between the customer and business. This model is framed as customer success, where success is defined by resolving the customer issue, optimizing upselling opportunities and personalizing interactions that drive brand loyalty and customer retention. AI enables this by providing real-time insights about customer needs, sentiment analysis that signals buying intentions and next-best actions for proactive engagement.
CX specialist
Contact center agents never operate with a complete customer data set. And, prior to AI, agents would have to tap subject matter experts presuming they could be contacted in time.
AI makes it easier to incorporate specialized knowledge into every interaction. This is a prime example of how AI will have a dual effect on the contact center. AI will almost certainly replace low-skill agents -- unless they can upskill -- but new positions will arise, including CX specialists.
Aside from automating routine CX tasks, AI will also create new data sets with rich insights that are highly specific to a product, region, situation or customer persona. This role will require a new skill set with specialized domain expertise, along with the critical thinking that only humans can provide to extract insights from AI inputs to provide more personalized forms of customer service.
AI agents need technical support
Conversational AI designer
Conversational AI is another important term in AI-driven customer service. Customer service remains voice-centric. And, as AI evolves, the value it can extract from conversations increases.
However, that value can only be realized if bots -- AI agents -- can converse in human-like ways that make customers feel comfortable. The more effective conversational AI is, the more self-service can be automated, which is arguably the strongest driver for AI in the contact center.
Conversational AI designer is one of the many new contact center AI jobs that are not customer-facing roles. Contact center agents could fill these jobs as they look to upskill. However, these roles will likely be filled by workers with AI and developer-based expertise in areas such as scripting call flows. These designers will need to ensure human-like conversations and use language and messaging that aligns with the brand's communications.
AI agent trainer
Conversational AI is just one component of an AI agent. At a higher level, trainers will need to guide overall performance -- both for AI agents that interact with customers and those that assist human agents, also known as copilots.
While AI has inherent capabilities for self-learning, humans are needed for the foundational training that makes AI agents effective. This represents another new role for the AI-first contact center, focusing on quality control. Typical tasks include checking bots for accuracy, screening for bias, tailoring language tone to suit a situation and building empathy into responses. Equally important is training bots to draw from all threads of interactions to identify data points that translate into personalized CX.
CX data analyst
As the title implies, this role is about the data itself, and not how it's used for customer interactions. The data analyst role is not new, but the specific focus on CX is.
Human forms of reasoning, parsing ambiguity and critical thinking still produce the best results, especially in the context of customer service, which remains grounded in 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 trusted on its own to analyze outputs. AI excels at pattern recognition and detecting anomalies. But human forms of reasoning, creativity, parsing ambiguity and critical thinking still produce the best results, especially in the context of customer service, which remains grounded in meeting the needs of other humans.
Contact center changes usher in new costs
These are just a few of the roles that are emerging -- and changing -- as AI transforms the contact center. Other roles are sure to come. Jobs will be lost, but others will arise to meet the new models of customer service.
However this plays out, CX and business leaders must adapt to AI's impact on agents. Training costs will be incurred to upskill agents, as well as new spending to hire the AI-savvy workers that contact centers now require. AI-driven automation will continue to provide a good ROI. But human agents will remain central for CX, both for customer-facing roles and behind-the-scenes jobs that align with today's AI-centric customer service.
Jon Arnold is principal of J Arnold & Associates, an independent analyst providing thought leadership and go-to-market counsel with a focus on the business-level effect of communications technology on digital transformation.
