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Andrii Hrach
Team Lead SAP CX 

2025 – The Year of AI in Enterprise Solutions 

Business users have become more open to innovations. They are ready to invest resources in process optimization, freeing up employees' time, and consequently directing these efforts toward revenue growth.

Sapiens Tech continuously explores new opportunities to enhance SAP solutions for our clients. In this article, we share our approach and real-world use cases of artificial intelligence (AI) in combination with SAP C4C. 

Innovations from SAP: Joule Copilot and Other Features 

SAP actively integrates AI into its products. For instance, the new Joule Copilot in cloud solutions, including S/4HANA, has become a real breakthrough. More details about AI features are available in the SAP AI catalog
If you are interested in Customer Relationship Management, you'll find features, including the SAP CX AI Toolkit and Joule. You can explore feature descriptions, evaluate their benefits in numbers, and calculate costs on SAP BTP.

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What's new in SAP Sales and Service Cloud? 

For the SAP Sales and Service Cloud V2, the number of AI features and Generative AI (Gen AI) is impressive. All releases are available in the SAP roadmap, link to resource here.
Unfortunately, SAP Sales and Service Cloud V1 of these products was left without significant AI updates. 
However, there’s a solution! You can use integration with SAP CX AI Toolkit, manual here. Or SAP proposes the SAP AI Core service, where you can integrate partner models or your own models with your SAP solutions, leveraging SAP BTP capabilities. 

How do we use AI in SAP Sales & Service Cloud v1? 

Our SAP CX consulting team analyzed all available AI features from SAP and created a list of potential improvements for C4C version 1. 
Our methodology:

    Identified processes automated in the system. 
    Decomposed them into subprocesses that could be enhanced with LLM models. 
    Drilled down to the level of system objects, analyzing attributes. 
    Generated hypotheses and tested them. 

Business Case: AI for Visit Preparation 

One of the solutions we implement improves the Visit Execution process, particularly the preparation for visits. 
The problem: A Sales Representative performs more than 10 visits daily. Preparing for each takes 2–15 minutes. The data for analysis includes: 

    Visit history (Previous visits) 
    Plan-Fact report 
    Receivable report 
    Sales Order history (Frequency, Quantity, Products) 
    Ticket history 
    Contract details 
    Survey/task history 
    Promotions 

The solution: AI analyzes all this data, identifies deviations, and generates conclusions as a note. Recommendations are created in the native language of the Sales Rep or the Contact person.

Expected benefits:

    Reduction in preparation time by 15–30% 
    Increase in user productivity by 5–15% 
    Shortened onboarding time by 15% 

Implementation scheme:

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Screenshots of the final system result: 

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Below is a list of system objects that can be involved in AI integration: Account, Ticket, Route, Visit, Sales Quote, Sales Order, Lead, Opportunity, Contract, Reports.

If you are interested in our solutions or have your hypotheses that you want to test but are unsure about their implementation, write to us.
We are ready to help!

By the way, this text was also edited by ChatGPT :) 

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