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AI Application in Companies

Here's how Artificial Intelligence helps different industries and business sectors

Use case from the industry
Use cases from customer services & marketing
Use case from the transport sector

Artificial Intelligence Is Relevant for Companies in All Industries

Whether in industry, logistics, transport, or marketing: companies in various sectors use Artificial Intelligence (AI) applications to optimize a wide range of processes through automated tasks. You, too, can exploit the full potential of these technologies for all areas of your business.

For example, AI applications help you make better decisions by analyzing large data sets and identifying patterns and trends. Overall, companies that use AI can expect improved performance and increased competitiveness. Arvato Systems offers a range of sophisticated AI applications that take your company's efficiency and security to a new level.

Possible Areas of Application for AI in Companies

AI in the industry

In the industrial sector, Artificial Intelligence is used, for example, in the automotive, healthcare, and retail industries, to improve the efficiency of manufacturing processes, create schedules, manage resources, and monitor and optimize factory performance. AI also supports the development of new products and services.

AI in logistics

Artificial Intelligence has also found its way into logistics in recent years. With appropriate applications, companies can optimize supply chains, plan and optimize routes, and even manage inventories. AI also helps to anticipate problems. In this way, companies can expect possible disruptions and maintain a smooth flow of goods.

AI in customer service & marketing

Artificial Intelligence applications in customer service and marketing are becoming increasingly sophisticated. In customer service, for example, companies use chatbots to answer questions and provide support. In marketing, for example, AI helps personalize messages and target advertising. You better understand your customers and can optimize the customer experience.

AI in traffic

Artificial Intelligence is being used in transportation - both in vehicles and in systems that control traffic. Its main applications are navigation, driving assistance, collision avoidance, and traffic management. AI can help make traffic more efficient and safer and is becoming an increasingly important part of the modern transport infrastructure.

AI in cyber security

Artificial Intelligence is increasingly contributing to cyber and data security by enabling you to detect and defend against threats faster and more accurately. Appropriate AI applications detect vulnerabilities to potential attacks. AI can also protect against data breaches by identifying sensitive data and implementing protective measures.

AI in purchasing

The use of Artificial Intelligence in purchasing automates and accelerates decision-making processes. By analyzing data, artificial intelligence can help identify patterns and trends and recommend the best options for purchasing. AI applications also enable manage relationships with suppliers and negotiate better deals.

Practical Examples of AI Applications

Our practical examples of AI applications in companies show how diverse possible application areas are across industries. We'd like to give you an overview of various AI projects, their respective challenges, and suitable solutions with their advantages.

Use Case from Industry: AVVIA Intelligence

Our first use case from the industry illustrates how an AI application can save time and money by preventing machine breakdowns. By intelligently collecting sensor data, you can check the current status of your machines and equipment and actively prevent their failure, thus avoiding a production stop.

Initial situation

Machine failures are associated with high costs. These costs must be avoided. Due to the downtimes, other machine parts can be affected. This increases the risk of further machine stoppages and, at the same time, leads to a reduction in the machine's service life.


Through permanent analysis of the machine sensor data using Artificial Intelligence, the interrelationships of the individual sensors of your plant can be monitored and evaluated. In this way, you receive a forecast of upcoming events and anomalies in your plant and can initiate the necessary measures early.


Artificial Intelligence analyzes sensor data permanently in real-time and can forecast future events and downtimes. In the process, the AI algorithms are trained on your production parameters and the plant's needs. Thanks to the possibility of independently marking anomalies, the AI receives the most critical information first-hand and thus achieves a very high forecasting quality.

Arvato Systems' AI solutions are based on AVVIA Intelligence. It combines pre-developed AI modules for intelligent industrial solutions. These include automated text recognition, processing, predictive maintenance, and quality. AVVIA Intelligence uses Artificial Intelligence to analyze real-time permanent sensor data.


Here's how it works: Your specialists detect anomalies based on historical scenarios and real-time markers of faults. They can name, describe and store them at the plant and set up the AI themselves in this way. Adding the critical responsibility explanation to the anomaly warning means no plant knowledge is lost. For example, the AI can distinguish a simple startup from a paper tear or defective sensor.

Just like your plant, AVVIA Intelligence grows with you and adapts. A human feedback loop allows fully automatic and continuous improvement to be made independently and at any time.


In the Data & AI Competence Cluster, Arvato Systems bundles AI competencies across all necessary disciplines. Complemented by your plant knowledge and proximity to the machines, AVVIA Intelligence provides the full potential of anomaly detection.


Visualization of the plant status 
Possibility of predictive maintenance 
Early alarming with few false alarms at the same time 
Independent marking of events (no Data Scientist required) 
Plant knowledge flows directly into the AI and stays with you

Use Case from Customer Service & Marketing: Churn Prediction using Predictive Analytics

Churn management refers to the attempt to prevent customer migration to the competition and to promote long-term customer loyalty. Preventive measures allow you to stop churn in a targeted manner. To do this, identifying customers at risk of churn is helpful and necessary. AI applications can effectively support churn management.

Initial situation

If current customers complain about conditions, delivery times or service, for example, you can react at an early stage. But these signs are not always recognized in time and interpreted correctly. Often, there is simply not enough time in customer service and support.


A solution based on artificial intelligence predicts the churn potential of existing customers using a score and thus enables preventive intervention. The aim is to develop a warning system that recognizes potential cancellations in good time to initiate customer retention and recovery measures at an early stage.


Artificial intelligence analyzes and interprets data to identify the probability of churn in different customer segments. Based on this data analysis, the system calculates the probability of churn and signals the need for action.


Higher customer lifetime value 
Higher customer loyalty
Less churn
Churn Management with AI for Energy Companies

With data-driven churn management, energy service providers and utilities can proactively develop customized offer and support models.

Use Case from Customer Service & Marketing: Conversational AI

Another use case from customer service and marketing is Conversational Artificial Intelligence (AI). This technology allows simple and fast communication between users and computers through automated dialog systems. Conversational AI can be used for many purposes, such as customer support, selling products and services, collecting feedback, etc.

Initial situation

Digitalization has made targeted and always-available customer care and consulting more relevant than ever and can make a decisive difference in competition with other companies. However, this requires time and resources. If there is not enough staff available and users have to wait long for an answer or feedback on their request, this can reduce customer satisfaction.


Chatbots and voice assistants counter the enormous increase in text- and voice-based communication in customer support and automatically answer customers' queries - anytime, anywhere.


Conversational AI is an omnichannel solution that can use text-based (for example, chat) and voice-based (telephony, virtual assistants). The open architecture offers many channels and easy integration of new media. With Natural Language Understanding (NLU), speech recognition and understanding is selected and customized for relevant language markets. In addition, the platform remembers vital information that users enter in the chat (DSGVO compliant). Since asking for the same information multiple times is unnecessary, the dialog experience is significantly improved.

Arvato Systems' chatbot approach delivers a state-of-the-art solution that puts customer service first. Our chatbot platform relies on state-of-the-art tools, our long-standing expertise in customer experience management, and the know-how of our AI experts and software developers to develop a flexible and future-proof bot platform.


Fewer costs 
Time-saving possibility to answer customer questions
Constant availability
Higher customer satisfaction 
Targeted and effective use of resources

Use Case from the Transport Sector

Many local and long-distance public transport companies are currently at the start of their own Digital Transformation. In addition to cost pressure, municipal policy developments such as the climate and transport turnaround are placing additional demands on companies. This is why the need for digital data-based solutions is increasing in the transport industry to remain marketable.

Initial situation

Public transport operators in cities face the challenge of ensuring demand-oriented scheduling for millions of passengers. In many companies, demand-driven scheduling has been done via Excel:  Employees spend much time manually evaluating millions of Excel lines each year and planning vehicle deployment accordingly.


To derive concrete measurement data that can be analyzed at high speed and at the same time processed in a visually speaking way. In addition, every employee of public transport should have the possibility to get a quick and easy-to-understand overview of the current utilization figures.


To enable transit agencies to take advantage of today's digital opportunities, scalable solutions are deployed to meet on-demand scheduling needs.  Using business analytics tools such as Microsoft Power BI, transit employees can access visually presented analytics of daily ridership anytime, anywhere.

With applications based on Artificial Intelligence, we support you in your demand-oriented mobility planning. We provide our analysis and forecasting tools as Software as a Service (SaaS) - for dynamically optimized forecasts and transparency for better decision-making in the digitalized transport space of the future. Our platform solution ÖPNV digital - the digital passenger analysis service - offers transport operators two applications in one package: passenger analysis and passenger forecasting: 

  • Passenger analysis with Microsoft Power BI: Passenger analysis provides high-performance support for analyzing passenger movements using ready-made dashboards in your public transport network. Take a look at the Passenger Analysis demo here.
  • Efficient passenger forecasting: Passenger forecasting uses AI and machine learning to create its own dynamic forecasting models. 

Our overall package accelerates the gain of knowledge from passenger movements. It supports demand-oriented vehicle deployment planning and the design of demand-oriented transport services, thus additionally offering new services for public transport and its passengers.


Improved forecast quality through specially trained AI solution 
High-performance data processing from backend systems 
Possible integration into existing mobility apps 
Out-of-the-box cloud service with fast provisioning 
SaaS model with monthly billing
Low investment costs

AI Applications Can Optimize All Areas of a Company

AI not only accompanies people in everyday life. Today, companies can also use Artificial Intelligence applications in almost all business areas to optimize various tasks to concentrate on higher-level tasks. This saves valuable time and resources. However, AI does not replace employees in any way but supports them effectively in their day-to-day business. Specialists make precisely tailored decisions based on their knowledge, experience, and AI results. As technology continues to develop, there will be more and more opportunities to make processes more efficient with AI in the future. 

Your Contacts for AI Applications

Niels Pothmann
Expert for Advanced Analytics & Artificial Intelligence
Timo Salzburg picture
Timo Salzburg
Expert for AI Solutions