AUTOMATION AND TALENT
There has always been a conversation, a dialectic, between automation and people in the workplace, one that is now being highlighted with the practicality of AI. But in practice, automation does not( and never has) eliminate the need for talent. Instead, it changes what talent is needed.
As AI absorbs routine tasks, the interactions left for humans become more complex, emotionally charged, and consequential. That shift is raising the skills bar, even as labor markets continue to constrain supply.
At the same time, hiring challenges persist. Time to fill remains high. Attrition remains stubborn. And despite new tools, innovative technologies, and louder promises, contact centers are no closer to solving their talent problem than they were years ago.
AVOIDING THE DESTRUCTIVE SPIRAL
This tension raises an uncomfortable question. If expectations continue to rise, but the labor pool does not expand in parallel, what are the unintended consequences? And who is most likely to be excluded along the way?
The answer is not keeping the bar where it is or lowering it. The problem is narrowing the pool of candidates needed to jump over it through requirements and proxies that do not improve performance.
Such practices can disproportionately screen out capable candidates, shrinking the workforce pipeline until there are too few people to staff open positions. Which can then result in long queues, angry customers, and frustrated agents: risking their turnover that together may lead to a destructive spiral.
In this article, which I have further divided into three parts, I focus on three skill areas where the hiring bar is rising fast: digital and AI fluency( Part 1 here), emotional intelligence( Part 2), and finally language skills( Part 3), which will have my conclusion of these points.
For each, I outline the unintended consequences of how organizations are currently screening for these skills. I then suggest a more sustainable approach: measuring skills directly and prioritizing readiness and ramp potential, rather than relying on background-based proxies that narrow the talent pool.
Importantly, this approach does not require complex technology or purchasing new tools. Instead, it requires clearer definitions of job skills and more structured and consistent evaluations.
Contact centers have always been skills-based jobs. Even in“ entry-level” roles, success has depended on communication ability, problem solving, and emotional control under pressure. What has changed is the level and breadth of those expectations.
As routine work is absorbed by automation and as service interactions become more complex, organizations continue to raise the skills bar, often without fully accounting for how those higher requirements narrow the available talent pool.
... THE INTERACTIONS LEFT FOR HUMANS BECOME MORE COMPLEX, EMOTIONALLY CHARGED, AND CONSEQUENTIAL.
INCREASING DIGITAL / AI LITERACY REQUIREMENTS
Digital skill expectations in contact centers have expanded rapidly in a brief period of time, initially driven by moving large contact center populations home in response to the COVID-19 pandemic.
To enable agents to work remotely, hiring and workforce readiness guidance emphasized the practical ability to function independently at home: reliable internet, appropriate hardware, headset quality, secure connectivity, and baseline troubleshooting skills without onsite IT support.
That focus has not disappeared, but the definition of digital literacy has changed. Today, digital literacy is not simply the ability to use a computer and follow a process. In many modern contact center environments, it now includes these abilities:
CONTACT CENTER SKILLS
• Navigating multiple systems and knowledge tools in parallel.
• Interpreting policy and account information in real time.
• Documenting accurately while maintaining customer rapport.
• Completing authentication steps and compliance scripts correctly.
• Switching between tools quickly under time pressure.
Omnichannel service further raises the bar:
• Writing becomes part of the role, not an occasional task. Agents must produce clear, appropriately toned written responses in chats and emails, while also working within structured workflows and meeting quality expectations.
• Video-enabled customer interactions introduce some additional skill demands, but, as I will explore in depth in a separate discussion( see BOX), not in the way they are often assumed.
AI adoption adds yet another layer. As AI copilots, automated knowledge systems, and AI-generated call summaries become more common, contact center talent is increasingly expected to demonstrate AI literacy as well.
This does not mean understanding how models work. Instead, it means knowing how to use AI-enabled systems effectively, including these abilities:
• Asking strong questions and using query tools correctly.
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