Top 10 Ways of using AI in Enterprises

by | 21. March 2022 | Basics, Basics

In 2022, we are celebrating the 10th anniversary of [at] – Alexander Thamm. 

10 years ago, we were the first consultancy in the German-speaking area to take up the cause of Data & AI. Today, we can say that artificial intelligence has the potential to make an important contribution to some of the major economic and social challenges of our time: AI plays a role in the energy transition and climate change, autonomous driving, the detection and treatment of diseases and in pandemic control. AI increases the efficiency of production processes and makes companies more adaptable to market changes through delivering real-time information and predictions.  

The economic significance of this technology is growing rapidly: More than two-thirds of German companies now use artificial intelligence and machine learning.  

With #AITOP10, we show you what’s hot right now in the field of Data & AI. Our TOP10 lists present podcast highlights, industry-specific AI trends, AI experts, tool recommendations, and much more. You get a broad cross-section of the Data & AI universe that has been driving us for 10 years now.  

Enjoy the reading – and feel free to expand the list! 

Top 10 Ways of using AI in Enterprises 

Artificial intelligence is finding its way into all industries and plays an ever-increasing role at all levels of companies’ value chains. The new technology opens many possibilities for developing new business models and enhancing processes. Several companies are already using AI intensively, but many are still lagging. Yet countless use cases prove that artificial intelligence offers real added value for companies. 

10th Place: Quality control

Production quality and yield are two of the most important performance indicators in the industry, regardless of whether it’s an automaker, a semiconductor, smartphone, or beverage manufacturer. Low production quality leads to more losses, lower revenue, and higher financial costs. The use of artificial intelligence can contribute significantly to the improvement of production quality at many points in the manufacturing process. AI-based solutions provide a more detailed analysis of production data and can detect minor changes in real-time. As a result, the quality of parts, such as semiconductor plates or painted car doors, can be improved and defects can be reliably identified using AI-based vision inspection. Another issue is a slowly changing production process. In contrast to humans, the KI does not “acclimate” to slow changes but can reliably detect them. Further information: https://www.alexanderthamm.com/en/usecases/error-detection-for-painting-robots/ 

9th Place: Financial planning and forecasting 

The data-driven and automated forecasting of future revenues, expenses, and other business parameters has become essential to most businesses by today. With the help of artificial intelligence, KPIs can be predicted and analyzed faster and more accurately. AI-powered software tools can detect compliance violations, conduct market analysis, and calculate and display key performance indicators in real-time. This enables businesses to plan and deploy resources more accurately and respond quickly when any irregularities arise. Further Information: https://www.alexanderthamm.com/usecases/forecast-invoice-payment%e2%80%8b%e2%80%8b/ 

8th Place: Supply-Chain-Optimization

Today’s large corporations face new challenges with their own supply chains on a daily basis: Every day, Amazon must track and monitor 1.5 billion products. Wal-Mart processes over one million customer transactions every hour. In this case, a strategic supply chain must be developed and, more importantly, monitored. An AI-monitored supply chain can meet shorter delivery times, avoid penalties, and maximize efficiency by linking warehouse, supplier, and production data.  

7th Place: Increasing long-term customer loyalty 

Only the happy customer is a loyal customer. But what does it mean to be a “satisfied customer”? With the help of AI, the entire customer journey can be comprehensively analyzed and clear problem areas identified. Especially personalized products, content, and service offers play an important role in this context. 

Customers can be classified easier and statements about their future purchasing behavior can be made. Predictive analytics, chatbots, and personalized offers using recommender systems can help businesses retain more customers and increase the likelihood of repeat purchases. A key factor in any purchase decision is the price of the product or service. In this case, AI can be used to strike the right balance between profit and affordability for the customer. Self-learning algorithms recommend optimized prices based on previous transactions as well as competitor prices, assisting the customer in making a positive purchase decision. 

6th Place: Logistics optimization

Logistics, with its intricate networks, is a suitable field for artificial intelligence. For example, future production and transport quantities can be forecasted by intelligently evaluating a wide range of data sources, from sales numbers over supplier costs to manufacturing cycles. An event-based and dynamic route planning improves transportation efficiency and saves money. The reading of freight and delivery documentation, as well as their automatic integration into current systems, is another task that can be done by AI. This accelerates processes and minimizes the likelihood of human errors. AI-assisted warehouse planning can also help to reduce storage costs. 

5th Place: Fraud detection

Fraud is a serious issue in all transactions of the financial services sector. In 2020, a total of $32.39 billion was lost globally due to payment fraud, such as wire transfer fraud, card fraud, and credit fraud – and this figure is rising. AI models can detect and block fraudulent transactions in real-time. With each identified example of fraud, artificial intelligence learns from previous incidents and improves its accuracy of detecting fraud.  

4th Place: Customer Interactions

In many businesses, chatbots currently allow faster and more direct engagement with customers. Advanced ML language models, such as GPT-3, provide a better understanding of complex questions and can answer them precisely. The start-up Algolia, for example, has developed software that analyzes the context of consumer requests and provides exact replies using the GPT-3 language model. In this manner, resources in the customer care sector can be optimized, and customer inquiries can be prioritized. 

3rd Place: Process automation

Robotic Process Automation (RPA) with the support of AI is the accelerator of business processes. In many business areas, repetitive tasks must be done from time to time. With RPA, these tasks can be automated by using Software-Robots that emulate human actions interacting with digital systems. Intelligent process automation opens new business and revenue opportunities as well as accelerated process excellence.  By using this technology, employees can spend more time doing really important tasks.  

2nd Place: Generating Customer Insights  

If you know your customers, you know what their needs are. Social Media promoted a radical shift in customer behavior. AI-powered customer orientation enables companies to respond better and faster to their customers’ needs. ML-Software helps to monitor, scan and collect data from different communication channels like social media and reveals insights into social sentiment and customer behavior in real-time. With the use of this data, marking strategies can be effectively adapted and optimized. Further Information: https://www.alexanderthamm.com/en/usecases/virtual-salesman/ 

1st Place: Improving customer experience and loyalty

Helping customers to make a purchase decision through a product tailored to their needs is a top priority for any business. According to a McKinsey report, 75% of content consumed by Netflix users and 35% of products bought on Amazon are suggested by their algorithms. With the use of AI, creating a dynamic customer experience becomes reality. Through individual offers and information, every customer receives the right decision-making aids at every touchpoint of his customer journey. Virtual assistants, predictive personalization, and AI-supported customer need analysis are creating a dramatic shift in customer decision-making. 

These are possible ways of using AI to make enterprises more competitive, curated by the [at]editorial team and based on insights from over 1300 use cases in AI. 

How are you using AI to enhance your business? Feel free to share it with us and let us know about your experience with using AI. 

<a href="https://www.alexanderthamm.com/en/blog/author/lukaslux/" target="_self">Lukas Lux</a>

Lukas Lux

Lukas Lux ist Werkstudent im Bereich Customer & Strategy bei der Alexander Thamm GmbH. Neben seinem Studium des Sales Engineering & Product Management mit dem Schwerpunkt IT-Engineering beschäftigt er sich mit den aktuellsten Trends und Technologien im Bereich Data & AI und stellt diese in Zusammenarbeit mit unseren [at]Experten für euch zusammen.

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