AI Application Cases in Practice
Be inspired by our AI application cases
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.
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: AIoT Leverage and Automation Platform (AILA)
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.
Arvato Systems' AI solutions are based on the AIoT Leverage and Automation Platform, or AILA. It combines pre-developed AI modules for intelligent industrial solutions. These include automated text recognition, processing, predictive maintenance, and quality. AILA Sensor 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, AILA Sensor 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, AILA Sensor Intelligence provides the full potential of anomaly detection.
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.
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.
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.
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.
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.
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.