The end of email floods: categorizing and handling emails with AI

Handling the same emails day after day is a tedious task that regularly causes frustration for affected employees. Fortunately, AI can now provide strong support in this area, maintaining or even increasing service quality without sacrificing control. AI systems have advanced to the point where some emails no longer need to be handled by humans. In this article, we will explore how AI systems handle emails, what they do, and how the response quality is ensured.

The challenge of email floods

Many teams and companies struggle with the daily flood of emails. Customer service departments and front-office teams, in particular, are often overwhelmed by a constant stream of inquiries that need to be processed daily.

The same issues arise repeatedly, similar questions, the same clicks to insert predefined templates, and fill in placeholders…

The work becomes monotonous and time-consuming, with many repetitive tasks that reduce productivity and overshadow the true potential of skilled employees.

The result of email floods: dissatisfaction among the team and frustrated customers due to slow handling of inquiries.

What AI can do with emails

Understanding and summarizing content
AI reads the text of the email, understands attached files, and checks whether all necessary information is included. Long emails can be presented as concise summaries.

Categorizing emails
Emails can be classified into topics such as bookings, refunds, or complaints. Irrelevant messages like newsletters are filtered out in the process.

Prioritization
Based on sentiment analysis or categorization, emails can be prioritized—helping teams stay organized and improve customer service.

Routing and archiving
AI can forward emails to the relevant departments or partners and archive them if they are important for future reference.

Pattern recognition at scale
AI can analyze large volumes of emails to identify recurring patterns and surface the most pressing issues that need improvement.

Generating responses and drafts
AI can generate reply drafts using flexible templates. These can either be sent automatically or handed over to employees for review and personalization.

AI can even automatically execute follow-up processes. For example, generating and sending vouchers when necessary, making bookings, or processing cancellations in the database.

How does email categorization with AI work?

To evaluate the value of such AI systems, let’s first understand how they operate.

The simple explanation

AI is trained with historical data — emails that have been processed in the past.

Based on this, the AI can recognize processing patterns and apply them in the future.

The AI learns to mimic past human behavior, such as whom emails with specific content were forwarded to in the past.

The detailed explanation

For those more interested in the technology, here’s a more detailed explanation:

The AI system receives text, for example from an email.
This text is sent to an embedding model, which creates a numerical representation of the content.
This numerical representation is then fed into a neural network. There are two possibilities here:
- A pre-trained neural network.
- A custom company-specific neural network that can be specifically tailored. Such systems take into account the different language preferences of a company.
The AI system then proposes a categorization, e.g., “90% chance that this is a complaint,” and tags the email accordingly.

The AI model requires historical data already tagged with the corresponding categories to work effectively. Working with untagged or unlabeled historical emails is also possible but requires additional preparatory work.

The benefits of email categorization and handling for customer service

Integrating AI into the email processing workflow can provide many benefits.

The benefits of email categorization for customers

Faster processing/solutions for inquiries
Immediate responses to inquiries, no matter the time of day or if it’s a holiday
Improved customer experience due to quicker feedback
Consistent service quality

The benefits of email categorization for employees and the company

Less manual work
Fewer routine tasks, more time for strategic work
Higher employee satisfaction
In predefined cases, emails are processed automatically without human intervention
Particularly useful for complex email processing, which previously often required extensive onboarding for employees — AI only needs to be “onboarded” once

A practical example of email categorization: Sunny Cars

Sunny Cars, a leading car rental service provider, faced the challenge of efficiently handling a growing volume of customer inquiries.

By implementing AI in collaboration with ONTEC AI, the company was able to optimize several processes. This included the automatic classification of inquiries with over 90% accuracy, automated creation of summaries for extensive inquiries, and sentiment analysis to prioritize issues.

These measures led to optimized processes and a significant reduction in processing time.

→ Details in the Sunny Cars case study

Limitations of email categorization with AI

Like any technology, AI has its limitations. These include blockers and some factors that must be considered and planned for during implementation:

Data dependency

An AI system is only as good as the data it is trained on. To work effectively, the system needs high-quality, comprehensive, and relevant training data.

This data must be well-structured and representative of real-world use cases. If, for example, historical data is incomplete or incorrect, the AI could draw wrong conclusions and provide inaccurate results.

Companies must ensure they collect and prepare the right data to unlock the full potential of AI.

ONTEC AI helps its customers implement their own email categorizer. For this, we develop a company-specific neural network tailored to the company’s data situation.

Data privacy

Companies must ensure they comply with applicable data protection laws when processing emails and other personal data. This is particularly regulated by the GDPR in the EU. It’s important to choose a trustworthy AI provider who securely stores and processes all personal data.

EU AI Act

The EU AI Act regulates how AI can be used within the EU, particularly with regard to ethical usage. Certain use cases are restricted to prevent misuse.

For example, AI use in recruiting is limited. AI cannot be used for automated evaluation of job applications or decisions without human involvement in the decision-making process. Companies must be aware that not every use of AI is legally permissible in all areas.

Errors and control

Technology is never perfect and can make mistakes. In email categorization, misunderstandings may occur. For example, an email containing feedback might be incorrectly categorized as a complaint. Such errors could affect the efficiency and quality of email processing.

It’s crucial that companies have the ability to monitor the AI regularly and intervene manually if needed to correct mistakes and continuously improve the AI’s performance.

For example, an additional confirmation by employees can be introduced — if the AI is uncertain, it can proactively ask the employee for their evaluation: “I think this email contains a cancellation request, is that correct? If yes, please click OK.”

Another option is that the customer can confirm whether the categorization is correct. Imagine the AI categorizes and automatically sends a confirmation email to the customer: “We have received your email and recognized it as a cancellation. If you want to cancel, click OK now.”

This ensures not only the quality of the AI’s work but also increases trust in AI and understanding of how it works.

Summary and Key Takeaways

Automated email handling with AI can significantly increase the efficiency and satisfaction of both customers and employees by taking over repetitive tasks. With the right implementation and careful review, companies can benefit from stable service that operates 24/7.

AI can read, categorize, summarize, and extract relevant information from emails; emails can be automatically answered or forwarded; for complex inquiries, a reply draft can be suggested for employee confirmation.
Integrating AI into email processing leads to less manual work, faster processing of inquiries, higher employee satisfaction, and consistent service quality 24/7.
Limitations such as data privacy and the quality of training data must be taken into account.
Especially in the early stages of implementation, it’s advisable to include control options over the AI system.