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Author's profile photo Paul PINARD

Automate Your Customer Service By Infusing Artificial Intelligence Into Business Processes

At SAP, our mission is to build intelligent enterprises by infusing our AI technologies into applications and business scenarios across all lines of business (HR, procurement, or finance), at scale.

In this blog post, let’s focus on two concrete AI applications in the customer service area.

Use Case #1 – Chat Optimization for Ticket Handling

As customers and employees increasingly communicate using chat technologies, users expect these tools to deliver intelligent responses. They also want companies to resolve their queries right away, within the chat window.
To help create a rewarding user experience, organizations need to automate chat activities.

What are the challenges faced by organizations today?

1/ Rising number of customer and employee conversations taking place in chat windows

2/ High user expectations for intelligent responses in the chat, including a simple way to resolve queries

3/ Need for a more engaging user experience during chats


What is the solution offered by SAP?

1/ An AI-powered chatbot that directly answers customers without requiring effort from agents

2/ Service ticket intelligence service that automates ticket classification, proposing solutions to facilitate the ticket-handling process

What are the benefits for our customers?

1/ Enhanced customer experience using solution proposals from past requests

2/ Smoother customer interaction with chat

3/ Reduced number of service tickets

4/ Streamlined customer service operations

Learn more about the AI-powered services used in this example, all available on SAP Business Technology Platform:

Dig deeper by watching this success story with our customer NHK Spring, one of the world’s leading spring manufacturers:

Use Case #2 – Service Request Handling

Thanks to digital transformation, customer interaction centers are responding to ever-higher volumes of requests. In shared service centers, agents must handle these requests across multiple channels, delivering more responsive service despite growing workloads.
To improve service levels, companies must automate rote processes, freeing knowledge workers to handle more difficult issues.

What are the challenges faced by organizations today?

1/ An increasing speed and volumes of customer inquiries processed by shared service centers

2/ Multiple communication channels that must be managed by agents

3/ High workloads and queued worklists

4/ A stressful work environment for agents trying to provide responsive service

What is the solution offered by SAP?

1/ An intelligent AI service that automates the classification and processing of customer service requests (see Figure 10)

2/ Machine learning models that categorize customer input from a variety of channels into internal service groups

3/ Automatic identification and extraction of business entities from the content of requests

4/ Automatic processing of standard inquiries supported by intelligent RPA technology


What are the benefits for our customers?

1/ Faster, more accurate responses to customers

2/ Fewer repetitive tasks for service center agents

3/ Greater focus on valuable creative tasks

Learn more about the intelligent technologies used in this example, all available on SAP Business Technology Platform:

Check this 4 minutes demo to see it in action:

These are just two successful examples of how artificial intelligence can significantly improve CX at scale when integrated into business processes.

Visit our AI use case repository to see other examples 🚀

We’ll add additional use cases in the next following weeks, so stay tuned!

Ready to implement AI in your business?

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      Author's profile photo RG Trial
      RG Trial

      Hi Pinard,

      I have been trying to train custom AI model for Business Entity Recognition from past couple of weeks. Can you please how we can structure training document as there are issues with let's say double quotes or data issue in so & so line?


      BER AI Model Training Job Issue

      Author's profile photo Komal Narsinghani
      Komal Narsinghani


      You can find details on the training data format here:

      If you are still not able to trigger a successful training, feel free to contact us and we can assist.

      Author's profile photo RG Trial
      RG Trial

      Hi Komal,

      Thank you very much. Format is in sync with what has been mentioned in the support document as mentioned. But continue to struggle with error. Attaching here the sample training document.

      {"id": 1, "text": "FRAMEWORK AGREEMENT, This Framework Agreement (the 'FA') is effective as of 23-Sep-2021 (the 'Effective Date') and made by and between (1) ASDFGH, a company organized under the laws of India, having a place of business at #100, Electronic City, Bangalore ('CCH'); and (2) QWERTY, a company organized under the laws of the USA having a place of business at #1594, Citadel, California (the 'Supplier') CCH together with Supplier, collectively, the 'Parties' and each, a 'Party'.", "meta": {}, "annotation_approver": null, "labels": [[0, 18, "contractType"], [76, 86, "effectiveDate"], [139, 144, "party1"], [185, 189, "party1OpsCntry"], [222, 253, "party1Address"], [272, 277, "party2"], [322, 324, "party2OpsCntry"], [356, 381, "party2Address"]]}