AI in customer service risks increasing human workload intensity

Shifting the service workload

Artificial intelligence is fundamentally changing the daily routine of customer service employees. For some workers, the technology acts as a helpful assistant that handles repetitive administrative tasks like note-taking and reading long disclosures. This shift allows these employees to dedicate more of their focus to the actual needs of the customer during a call.

However, the transition is not uniform across the industry. Some workers report that AI-generated notes are frequently filled with mistakes, requiring them to manually rewrite the information to ensure accuracy. In other cases, management has encouraged staff to use tools like ChatGPT to find answers, which can lead to complications when the technology fails to provide the correct information.

The goal for many companies is to create a balanced ecosystem of human and machine interaction. For example, ArvatoConnect, a customer experience company, intends for technology to manage 70% of all interactions. This leaves the remaining 30% for human advisors who are better equipped to handle sensitive issues or cases requiring significant judgment.

The risk of work intensification

A significant concern among researchers is the concept of work intensification, which describes how jobs can become more demanding over time. As AI takes over straightforward, routine tasks, human agents may be left exclusively with the most difficult and emotionally draining cases. This could create a high-pressure environment where workers are constantly dealing with frustrated customers who have already faced hurdles with automated systems.

Amanda Jones, a researcher at King's College London, notes that simple tasks often provide a necessary psychological respite for workers. When these easy tasks disappear, the intensity of the workday could increase considerably even if the total volume of work remains the same. Workers might find themselves moving from one high-stress interaction to the next without a break to reset.

Furthermore, there is a risk that workers will lose the opportunity to develop experience through handling basic queries. If employees are only exposed to the hardest problems, they may lack the foundational knowledge needed to solve them effectively. This creates a cycle where workers are expected to perform high-level work without the traditional training steps that once helped them prepare for it.

Impact on employee well-being

The customer service industry has long struggled with high rates of burnout and emotional stress. Nikola Mrkšić, the CEO of PolyAI, points out that contact-center agents often face maximum abuse for minimum wage while working under strict performance metrics. He suggests that AI agents can help shoulder this burden by handling the most repetitive and high-volume interactions that lead to employee exhaustion.

Despite these potential benefits, some employees fear that the push for automation prioritizes speed over the quality of the human experience. There is a concern that focusing on getting things done faster will result in customers becoming increasingly frustrated with the prevalence of AI. Workers who value the 'human touch' argue that people buy from people and that AI cannot replicate the feeling of a genuine, extra-mile effort.

The data suggests that workloads are already rising across the sector. A report by MaxContact found that more than half of surveyed contact-center decision-makers reported an increase in agent workloads in 2025. This rise in pressure, combined with the removal of simpler tasks, could make the remaining human roles significantly more taxing for the workforce.

Measuring success and quality

As companies integrate more AI, the way they measure success for human employees is beginning to shift. Instead of focusing on how quickly an agent can follow a script or hit an arbitrary time target, companies like ArvatoConnect are looking at the quality of the resolution. They want to ensure that human agents are exercising sound judgment and truly understanding the customer's specific needs.

This shift in metrics is intended to prioritize complex problem-solving over high-volume processing. By letting AI handle the routine, the human role becomes more specialized. The objective is to move away from a model where humans are treated as high-speed processors of simple data and toward a model where they are valued for their empathy and experience.

However, the success of this model depends on whether the technology can accurately filter the cases. If the AI fails to resolve a problem and passes it to a human, the agent must be prepared to pick up the slack immediately. The goal is to bridge the gap between customer needs and employee well-being, but the transition remains a work in progress for many large organizations.

The future of human interaction

The future of customer service will likely involve a hybrid model where the distinction between human and machine interaction is blurred. Companies like Virgin Media O2 have already launched AI voice agents to handle routine issues, aiming to free up human advisors for more sensitive cases. This represents a broader trend toward using technology to manage the scale of modern commerce while reserving human intervention for high-value interactions.

While some see this as a way to improve the lives of workers, others worry about the erosion of the customer experience. There is a tension between the desire for efficiency and the human desire for connection. As AI becomes more sophisticated, the challenge for businesses will be maintaining a sense of authenticity and ensuring that customers do not feel like they are being pushed through a digital maze.

Ultimately, the goal is to find a balance that prevents burnout while maintaining high service standards. If the transition is handled well, AI could remove the most tedious parts of service jobs. If handled poorly, it may leave human workers overwhelmed by the most difficult tasks, potentially leading to a decline in both employee satisfaction and customer loyalty.

Try it

Next time you contact a company's support, try to identify if you are speaking to a bot or a human by asking a complex, non-routine question about your specific account history.

Watch

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