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AI-assistant – the Jeanne D’Arc of customer service processes

AI is one of the fastest growing focus areas for customer service development. According to Gartner, one in seven customer service interactions will be automated by 2027. There is a 14% improvement in the number of resolved cases following the introduction of generative AI, 35% for low-skilled agents. So it is clear that AI cannot be avoided when talking about the future of customer service. But what is the power of AI and what will it take to become a useful colleague?

Stratis - AI-asszisztens

Stratis - AI Assistant

Artificial Intelligence is a set of technologies that enable the processing of large amounts of data, various machine learning algorithms, generative models. AI focuses on reproducing or augmenting human intelligence, while automation (e.g. RPA) focuses on automating routine tasks to improve efficiency and productivity.

What fundamentally distinguishes AI from rule-based automation algorithms is its ability to interpret the information fed to it, recognise patterns and learn how to make good decisions based on them. This makes it highly scalable and its knowledge can be efficiently extended.

For customer services, the power of AI lies in:

  • Process large amounts of unstructured data, identify correlations, draw conclusions, support decisions e.g. process mining, predictive analytics.

  • Improving worker efficiency AI-assisted processes e.g. knowledge base information extraction, extracting information.

  • Automating repetitive processes, developing self-service systems e.g. document filing, email management, chatbot, generative AI.

But what does it take for AI to become a useful tool for customer services?

AI behaves in exactly the same way as a new employee. It needs to be trained. A new colleague, when they leave the classroom, has a general knowledge, learns languages, or, for example, how to program. And at work, he reads internal procedures, policies, gets to know how the company works. AI also needs to be familiarised with company documents, the information on the basis of which the company makes its decisions. It should then be shown our decisions.

This means that generic AI models alone cannot be deployed in a customer service department, they need to be further taught with our own knowledge base.

But it's not enough to collect our data, we also need a change of mindset to dedicate our resources to teaching AI in order to become a long-term effective employee.

Ultimately, implementing AI-based solutions can lead to benefits such as:

  • Better customer experience

  • Better SLAs

  • Lower training costs

  • Resource savings.

The efficiency of customer services using Stratis' A.N.I.T.A. solution has increased significantly by automating the management of incoming written enquiries, reducing unnecessary referrals by 90%. With its smart search functionality, customer service colleagues can efficiently find the information they are looking for in internal corporate documents, reducing learning time.

About author

Gaspar Sandor Szerzo
Sándor Gáspár

Head of the Artificial Intelligence Competence Centre

Analytics - Data Solutions

Gáspár Sándor has been leading Stratis' artificial intelligence division since 2020, bringing over 20 years of experience in data science. Together with his team, he develops machine learning-powered decision support solutions for large enterprises, leveraging our clients' existing data assets. Additionally, he assists in automating our clients' existing processes using deep neural networks-based NLP and machine vision solutions.

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