From Humans to AI: The Imminent Evolution of Contact Centers

According to a Gartner study, by 2025, 80% of customer service interactions are expected to be managed by AI, highlighting the radical change ahead. In an increasingly connected world, Contact Centers have been the fundamental pillar in interaction between companies and customers. For decades, they have evolved without pause, reaching extraordinary levels of efficiency and quality thanks to a combination of factors:

• Continuous improvement processes: The implementation of methodologies such as Lean and Six Sigma has optimized every aspect of the operation.
• Well-defined key performance indicators (KPIs): These indicators guide decision-making and resource optimization, ensuring that strategic objectives are met.
• Innovative technologies that complement human capabilities: From automatic call distributors (ACD) and interactive voice response (IVR) systems to multiple integrated communication channels such as phone, chat, email, text messages (SMS), and social media, as well as robotic process automation (RPA) and transactional chatbots.

This approach has allowed Contact Centers to achieve elevated levels of customer satisfaction and operational efficiency, where process optimization and technology complement the human ability to understand and solve problems, creating a virtuous circle.

Metrics in Contact Centers

One of the keys to achieving efficiency is to have clear and relevant metrics. Then, through an iteration and continuous monitoring process, advances are made that translate into lower costs, greater efficiency, and a better user experience.

Below are some of the main KPIs used in Contact Centers, accompanied by practical examples of how agents, supervisors, and operations leaders manage them:

Metric

1. Service Level (Percentage of calls answered within a specific time, e.g., 80% in less than 20 seconds) Agents prioritize calls and use queue management techniques. For example, during peak call times, they follow concise scripts to efficiently attend to more customers in less time.
2. Customer Satisfaction (CSAT) (Measures customer satisfaction post-interaction) Through communication and empathy skills, agents resolve complex problems. For example, an agent who calms a frustrated customer and resolves their issue in a single call increases CSAT.
3. Net Promoter Score (NPS) (Measures customer loyalty) Agents provide personalized service, recalling previous interactions and anticipating needs, fostering positive recommendations.
4. Abandon Rate (Percentage of calls abandoned before being answered) Agents try to reduce wait times by responding quickly. For example, during promotional campaigns, the team is reinforced to avoid long queues.
5. Average Speed of Answer (ASA) (Average time to answer a call) Agent availability and efficiency determine the speed of response. They implement quick responses without compromising service quality.
6. Cost per Call (Average cost of handling a call) They manage calls effectively to optimize time and resources, using tools like dynamic scripts and integrated information systems.
7. First Call Resolution (FCR) (Percentage of issues resolved on the first call) Agents focus on providing accurate and complete solutions. For example, a well-trained agent with access to all the necessary information resolves the issue without transfers or additional follow-ups.

A Paradigm Shift: AI as the Protagonist

It is no surprise that the landscape is rapidly changing with the advent of Artificial Intelligence (AI). We are witnessing a new era in all industries, particularly in Contact Centers. Technology is no longer just a complement to human talent; Artificial Intelligence is becoming the central piece.

Recent Advances in AI

The latest advances in AI are utterly amazing and are progressing at an unprecedented speed:

• Advanced language models: They can communicate in any language indistinguishably from a human conversation, allowing smoother and more natural interactions through text, voice, and even video.
• Reasoning models: Through techniques like chains of thought and reinforcement learning, AI can reason and make increasingly complex decisions.
• AI agents: These agents can complete complex tasks autonomously, from solving technical problems to proactively managing business processes.
• Collaborative AI agent systems: AI can work in teams of specialized agents. For example, one AI agent can take a call while another AI evaluates and suggests improvements in real time.

Looking to the Future

Could we imagine a not-so-distant future where Contact Centers are fully operated by AI agents managing the operation autonomously? I dare say yes.

The customer experience with human agents still presents challenges that AI can address more effectively:

Wait Times

Human Agents They can only deal with one call at a time, generating queues and wait times, especially during peak hours.

AI Responds instantly and can manage multiple interactions simultaneously. For example, an AI system can address thousands of customers at the same time during a promotional campaign.

Errors in Provided Information

Human Agents They can make mistakes due to lack of information or training, leading to incorrect responses.

AI Accesses real-time data and provides consistent and accurate responses.

Lack of Consistency in Attention

Human Agents Quality can vary depending on the agent or their emotional state, affecting customer satisfaction.

AI Maintains consistent and objective attention quality, based on data and behavior patterns, ensuring a uniform experience for all customers.

Faster, Cheaper, Better, Safer

AI offers:

1. Faster interactions: Instant responses without wait times.
2. Reduced costs: Lower operational expenses by eliminating the need for a large human workforce.
3. Greater precision: Consistent responses based on real-time updated data.
4. Greater security: Lower margin for human error and the ability to manage sensitive data with advanced security protocols.

Is it now?

No fully! AI is not yet capable of managing itself and does not possess emotional intelligence or complex reasoning at a human level.

Human interaction is still valuable in situations that require empathy, complex judgment, or managing sensitive complaints. For example, in cases of customers experiencing emotionally demanding situations, human connection can be irreplaceable.

Moreover, creating a Contact Center operated 100% by AI still faces important challenges.

Ethical and Privacy Considerations

The implementation of AI must be responsible and ethical. Companies must ensure:

• Data Protection: Compliance with regulations such as GDPR and adoption of secure data handling practices.
• Transparency: Informing customers when interacting with AI and how their data is used.
• Accountability: Establishing mechanisms to address errors or misunderstandings generated by AI.

Impact on Employment and Retraining

Automation raises concerns about the impact on employment. However, it also opens opportunities for agents to retrain in new skills. Roles such as data analysts, AI developers, and customer experience managers will be increasingly in demand. It is essential for companies to invest in training and professional development programs to facilitate this transition.

Integration with Existing Systems

Integrating AI with current infrastructures can present technical challenges. It is crucial to:

• Evaluate Compatibility: Ensure that AI systems are compatible with CRM systems and other existing tools.
• Plan Implementation: Develop a phased plan that minimizes the risks of service disruptions.
• Invest in Infrastructure: Consider updates in hardware and software to support AI efficiently.

Need for New Metrics

With the implementation of AI agents, some traditional metrics lose relevance and there is a need for new ones adapted to an AI-driven environment.

KPIs that lose relevance:

• Service Level: Becomes irrelevant as interactions are attended instantly.
• Schedule Adherence: Does not apply, as AI is available 24/7 without the need for breaks.
• Average Speed of Answer (ASA): Reduces to zero since AI responds instantly.

New KPIs

• AI Accuracy Rate: Measures the accuracy of the responses provided by AI.
• Customer Satisfaction with Automated Interactions: Evaluates how customers perceive interactions with AI.
• Efficiency in Automatic Problem Resolution: Calculates the percentage of problems resolved without human intervention.
• Data Update Time: Measures how quickly AI incorporates new information into its responses.

Note: To ensure that interactions remain satisfactory, it is vital to continuously monitor customer feedback and adjust AI accordingly.

Regulations and Compliance

Companies must be aware of regulations affecting the use of AI:

• Legal Compliance: Ensure that all operations comply with local and international laws.
• Audits and Monitoring: Conduct periodic audits to identify and correct potential non-compliance.

Key Questions

Contact Center operations leaders should reflect on how AI can transform their business models and how to prepare for this change. Below are some key questions:

What new capabilities could be achieved in an AI-operated environment?

What competitive advantages could be obtained in the short and long term?

How can AI improve personalization without compromising customer privacy?

What are the ethical risks associated with adopting AI?

Which traditional metrics need to be adjusted or eliminated?

What type of initial and ongoing investment is required to implement a fully AI-operated Contact Center?

How is the return on investment (ROI) measured for a transformation of this nature?

What AI integration strategies can coexist with human agents during the transition?

How prepared are current teams to adopt and collaborate with AI agents?

How should the organizational structure change to support an AI-driven model?

Conclusion

The future of Contact Centers is being redefined by Artificial Intelligence. While AI offers undeniable advantages in terms of efficiency, costs, and service quality, it is essential to balance technology with the human factor. Interactions that require empathy, understanding, and complex judgment still need the human touch.

Companies should begin preparing for this imminent change. This involves not only investing in technology but also in people. Retraining agents, redefining roles, and adopting ethical practices will be key to a successful transition.