Total Automation of Customer Service Will Not Happen

Since the emergence of generative artificial intelligence in businesses, one scenario has become prevalent in many technology discussions. Customer contact centers would be destined to gradually disappear in favor of chatbots capable of instantly responding to consumer requests. The promises are appealing. Cost reduction, permanent availability, capacity to simultaneously handle thousands of conversations, and improved productivity are among the most frequently cited arguments.

Yet a recent study published by Gartner challenges this vision. According to them, 50% of companies that have reduced their customer service workforce due to artificial intelligence will need to rehire staff by 2027 to perform similar functions, albeit under different job titles.

This forecast is a strong signal. It suggests that the ongoing transformation is not simply a substitution of humans by machines. Rather, it reveals a profound reshaping of customer service professions.

Massive AI Adoption in Contact Centers

Gartner’s study shows that artificial intelligence is now firmly embedded in customer relationship strategies.

According to data collected by the firm, 74% of organizations already have at least one AI use case in production within their customer service operations. This rapid adoption is explained by several factors.

Companies face increasing pressure on operational costs. At the same time, consumers demand ever faster responses available at all hours. Generative models precisely address this dual constraint.

Conversational agents can now automatically handle simple requests such as:

  • order tracking;
  • returns management;
  • refund requests;
  • common administrative questions;
  • product information requests.

For many executives, these capabilities open the prospect of significant personnel cost reduction.

This logic explains why 63% of leaders surveyed by Gartner report gradually reducing their workforce through natural attrition, while 31% are considering or have already implemented direct layoffs.

Yet behind these figures lies a more complex reality.

The Programmed Disappearance of First-Level Support

The impact of AI on certain professions is nevertheless very real.

First-level support is probably the function most exposed to automation.

Historically, these employees had the mission of identifying the nature of the problem, providing standardized responses, and directing requests to the appropriate departments. These tasks largely relied on predefined procedures and knowledge bases.

However, these are precisely the activities that large language models now master efficiently.

This evolution is not entirely surprising for field practitioners. In an interview with EntrepreneurIA, Gilles Cymbalista, Vice President of Data, AI and Automation at CGI France, already explained that level 1 support tickets were natural candidates for automation. Repetitive requests, highly structured and based on standardized procedures, are precisely those that generative AI systems now handle most efficiently.

Companies find that AI systems can instantly respond to thousands of simultaneous requests without fatigue, without waiting time, and at an extremely low marginal cost.

This evolution naturally leads to a decrease in first-level agent needs.

But this disappearance does not necessarily mean the end of human customer service.

The Paradox of Automation

Gartner’s main finding lies in an unexpected paradox.

While many companies hoped to massively replace their teams, they are gradually discovering the limits of automation.

Generative systems excel in repetitive and predictable situations. However, their effectiveness significantly decreases when interactions become ambiguous, emotional, or complex.

A customer facing a financial dispute, a health problem, a contractual error, or an exceptional situation expects more than a statistically probable answer.

They seek contextual understanding, accountability, and sometimes even a form of empathy.

However, these dimensions remain largely human.

According to Gartner, this reality explains why companies that have eliminated positions will need to create new functions in the coming years.

The question is therefore no longer whether humans will disappear.

The real question is identifying which human skills become irreplaceable.

The Emergence of the Complex Situation Manager

The customer advisor profession is rapidly evolving toward a higher value-added role.

Simple requests are gradually absorbed by automated systems. Human employees now mainly intervene when the situation exceeds the algorithm’s capabilities.

This evolution profoundly transforms the profiles sought.

Companies increasingly value:

  • analytical ability;
  • emotional intelligence;
  • negotiation;
  • crisis management;
  • contextualized decision-making.

Tomorrow’s advisor resembles less an operator following a script than an expert capable of handling atypical cases.

This evolution helps revalue certain professions long considered low-skilled.

Why Gartner Predicts Rehiring

Gartner’s forecast is often interpreted as proof that AI projects don’t deliver on their promises. The reality is probably more nuanced.

Companies are gradually discovering that certain human functions remain indispensable. But they are also becoming aware of another phenomenon: first-level positions historically played an essential role in training future experts.

In his interview with EntrepreneurIA, Gilles Cymbalista mentioned an “organizational blind spot” rarely considered in automation strategies. Level 1 positions often constituted the gateway to level 2 and 3 functions. This is where employees acquired their knowledge of products, procedures, and customer situations before evolving to more expert functions.

When these positions disappear, companies must rethink how they develop their internal skills. This reflection provides complementary insight into Gartner’s forecast. Rehiring may not only be related to chatbot limitations but also to the need to rebuild skill development pathways.

The Unexpected Return of the Human as Competitive Advantage

Another phenomenon deserves the attention of executives.

As automation becomes widespread, human interaction becomes a differentiating element.

In many sectors, consumers are already beginning to distinguish companies according to the quality of their human support.

When a significant problem arises, the ability to speak with a competent person becomes a major satisfaction factor.

This phenomenon is particularly visible in:

  • banking;
  • insurance;
  • healthcare;
  • tourism;
  • luxury;
  • professional services.

In these sectors, human service is no longer just a cost. It becomes a constitutive element of the value proposition.

Some brands could even make premium human service a commercial argument.

New Jobs Created by AI

Gartner’s study also reveals a particularly interesting trend.

While certain positions disappear, new functions emerge.

The firm indicates that 42% of organizations are currently creating specialized roles related to artificial intelligence in their customer service operations.

Among the most sought-after profiles are:

  • conversation designers;
  • AI agent supervisors;
  • automation analysts;
  • AI quality managers;
  • algorithmic governance experts.

These professionals no longer directly respond to customers. Their mission is to design, monitor, and improve automated systems.

This evolution illustrates a phenomenon observed in many technological revolutions: technology eliminates certain tasks but simultaneously creates new expertise.

This issue also leads to rethinking training models. Gilles Cymbalista believes that artificial intelligence could itself become a learning tool, through simulated environments allowing employees to train on fictional cases before handling real situations. As level 1 positions decrease, these systems could play an increasing role in knowledge transmission and preparing future experts to supervise AI systems.

An Evolution Comparable to Previous Technological Revolutions

Economic history shows that major technological innovations rarely produce the effects announced in the short term.

Industrial automation did not eliminate human work. It transformed it.

Computers did not eliminate administrative jobs. They changed their content.

The Internet did not destroy commerce. It created new business models.

Artificial intelligence seems to follow a comparable trajectory.

Companies that view AI as a simple cost reduction lever risk missing its true potential.

The most successful organizations are often those that use AI to augment human capabilities rather than replace them.

The Governance Challenge

This transformation also raises major strategic questions.

Who will be responsible when AI makes a mistake?

How to ensure regulatory compliance?

How to avoid algorithmic biases?

How to protect customers’ personal data?

These issues explain the growing importance of human oversight functions.

The European Union, through the AI Act, is reinforcing this requirement for human control in many sensitive areas.

Companies will therefore need to maintain internal skills capable of understanding, auditing, and correcting automated systems.

Toward a Hybrid Human-Machine Model

The vision emerging today is one of close collaboration between humans and artificial intelligence.

Machines will handle the majority of simple and repetitive interactions.

Humans will intervene when situations require judgment, creativity, empathy, or legal accountability.

This hybrid model seems to correspond more to the reality observed in the field than the scenarios of massive replacement often mentioned in recent years.

Gartner’s forecasts thus constitute a useful reminder for executives.

Artificial intelligence profoundly transforms customer service, but it does not signal its disappearance.

It simply redefines the place of humans.

Conclusion

Gartner’s prediction that half of companies that eliminated positions due to AI will need to rehire by 2027 may mark a turning point in the debate on automation.

The initial enthusiasm around replacing employees is gradually giving way to a more mature vision of artificial intelligence.

Organizations are discovering that value does not only lie in automating simple tasks but in the intelligent combination of human and algorithmic capabilities.

As Gilles Cymbalista already emphasized in his analysis of the impacts of level 1 automation, the challenge is not only technological. It also concerns how companies train, develop, and transmit their skills. This question could become one of the major organizational challenges of the generative AI era.

The future of customer service will probably be neither entirely human nor entirely automated.

It will be hybrid.

And in this environment, the most sought-after skills could be precisely those that machines still struggle to replicate: judgment, empathy, creativity, and understanding of complex situations.

Sources

Gartner (2026), Gartner Predicts Half of Companies That Cut Customer Service Staff Due to AI Will Rehire by 2027.

Gartner (2026), Gartner Survey Finds 85% of Service and Support Leaders Are Expanding Human Agent Responsibilities Despite Expectations of Mass AI Layoffs.

Gartner (2025), Only 20% of Customer Service Leaders Report AI-Driven Headcount Reduction.

Cymbalista, G. (2026), L’intelligence artificielle à l’épreuve du réel : data, processus et souveraineté, EntrepreneurIA/Yunova Consulting.