AI in Business: Opportunities and Challenges for Modern Business

It is mainly larger companies with more than 250 employees that already rely heavily on the use of Artificial Intelligence. It is important to distinguish between traditional AI and generative AI. Traditional AI systems are designed to perform specific tasks based on predefined rules and patterns. Generative AI goes a step further and can generate new, original content. 

Most commonly, organizations use traditional AI technologies for text analysis or text mining. The latter involves the use of machine learning, statistics, and linguistics to identify and analyze text patterns in unstructured data. Speech recognition and natural language generation technologies are also widely used. 

However, the areas in which companies use Artificial Intelligence vary widely, from data analysis and business process optimization to intelligent customer service. In customer service, for example, many companies are turning to intelligent chatbots and voice assistants that respond to customer queries in a personalized and contextualized manner, rather than simply providing predefined answers.  

In marketing, traditional AI enables personalized campaigns and product recommendations based on customer behavior and preferences. Generative AI enables the creation of new advertising campaigns, including text, images, and videos tailored to specific audiences. 

Production and manufacturing companies are also using traditional AI to improve the efficiency and quality of production. This includes controlling production processes, optimizing the flow of goods, and predicting machine failures. Generative AI goes a step further, suggesting new product designs or developing optimized production processes that a human engineer might have overlooked.  

In the financial sector, banks and insurance companies use traditional AI for fraud prevention and risk assessment. Generative AI extends these capabilities by optimizing processes and suggesting new, creative solutions. 

AI is revolutionizing many business processes. The following section looks at specific examples of AI applications in the modern business world.

Manufacturing and Product Development

In the industrial sector, AI is primarily used in the area of predictive maintenance, i.e., predicting the maintenance requirements of machines and equipment. Product lifecycles can also be optimized using AI. Product development departments are also using AI-powered digital twins to simulate or optimize products. 

Customer Service

AI has become indispensable in customer service, offering a range of benefits. For example, AI is used to analyze customer feedback and identify customer moods and trends in real time. This enables companies to respond quickly to feedback and increase customer satisfaction. The latter is also possible using predictive models that can anticipate customer queries and proactively suggest solutions before a problem arises. 

Project Management

AI-powered tools increase efficiency and transparency in project management. For example, AI is used to automatically generate status reports and schedules. It also helps project managers allocate resources optimally and create accurate project plans. AI-powered tools can also identify potential bottlenecks, risks or delays and develop data-driven strategies. Ultimately, AI can help project teams save time on routine tasks and focus on strategic and complex tasks. 

AI can be used in a variety of operational ways. The application examples above have already highlighted several benefits that we would like to discuss in more detail. 

• Increased efficiency and cost savings: AI-powered systems optimize the use of resources by automating complex processes, saving time and money. By freeing employees from mundane, routine tasks, they can focus on other, more important tasks. In this way, AI helps increase productivity and address the skills shortage.  

• Assist in decision making: AI systems can quickly analyze and derive insights from large amounts of data, assisting human decision makers. This is particularly beneficial in complex or time-critical situations where quick and informed decisions must be made.

• Flexibility and competitive advantage: The business world is changing rapidly and constantly. By using AI, companies can prepare for the future, increase their agility, and adapt quickly to changing market conditions by being more responsive to change and using resources more efficiently. Companies can also use AI to maintain their market position and gain a competitive advantage by developing innovative products.

• New insights: AI provides businesses with new insights on a regular basis as it constantly learns and optimizes itself. This enables organizations to continuously increase their business value. For example, by analyzing large amounts of data, AI can uncover hidden patterns and correlations that human analysts might miss.  

• Customer loyalty: In this area, AI makes it possible to create personalized offers and respond to individual customer needs. It also helps to better understand customer behavior and increase customer satisfaction. 

So far, this article has focused on the opportunities and benefits for companies using Artificial Intelligence. However, not every company is convinced by the use of AI, as shown by a recent survey conducted by the industry association bitkom: 12 percent of German companies stated that they currently still see AI as a risk (3). Let’s take a look at the three biggest risks and challenges.

AI’s Impact on Job Security

AI is probably met with the most skepticism when it comes to jobs. Many people are increasingly afraid of losing their jobs. These fears are not unfounded, as the impact of AI on the job market is predicted to be significant. Management consulting firm McKinsey, for example, believes that more than 20 million jobs in Germany alone could be at risk from automation – that’s almost half of all jobs (4). Workers in sectors where AI is used to perform repetitive, manual, routine tasks, such as manufacturing, are particularly worried. 

But despite the fears, studies show that AI will not only destroy jobs, but also create new ones. The Institute for Employment Research (IAB) predicts that while 1.5 million jobs will be lost next year, about 1.5 million new jobs will be created (5).

Lack of or insufficient AI Governance

Organizations that deploy AI must be responsible in their use of it. What sounds logical in theory is a big hurdle in practice. It is no surprise, then, that AI–governance is a key aspect of deploying Artificial Intelligence. When it is absent or poorly implemented, the following risks can arise:  

Operational and business risks:

• Faulty AI systems can lead to poor decisions that result in financial losses.  

• Lack of transparency in AI tools leads to AI decisions that are difficult to understand. This often leads to mistrust and can also lead to legal challenges.  

• Vulnerable AI systems are susceptible to manipulation and malfunction. 

Ethical and legal risks:

• Violations of privacy regulations: Inadequate AI governance can lead to violations of privacy laws and regulations.   

• Discrimination and bias: AI models can inadvertently adopt and reinforce biases from historical data. This can be a source of unfair decisions and discrimination against certain groups of people.  

• Compliance violations: Without robust governance structures, companies cannot comply with regulatory requirements such as the EU’s AI Act, which sets clear guidelines for the use of AI technologies. 

Lack of Knowledge

One of the main reasons why companies have not yet adopted AI is a lack of knowledge. Medium-sized companies in particular still find it difficult to identify suitable AI applications (6). Another factor is that AI applications often require large amounts of data and a high degree of customization, which is why offerings have been targeted primarily at large and midsize companies.  

The fact that there are now many different AI applications on the market for a wide variety of applications also contributes to the uncertainty that scares off companies – especially if they (still) do not have employees who are intensively involved with the topic of AI  

Only about one-fifth of German companies use AI, but the trend is upward. AI is mainly used in areas such as text analysis, speech recognition and process optimization. Larger companies are leading the way. AI offers benefits such as increased efficiency and improved decision-making, but also risks such as potential job losses and governance challenges. Lack of knowledge and uncertainty about appropriate applications are key reasons for reluctance to adopt, especially among midsize companies. 

References: 

(1) https://www.destatis.de/DE/Presse/Pressemitteilungen/2024/11/PD24_444_52911.html 

(2) https://www.destatis.de/DE/Presse/Pressemitteilungen/2024/11/PD24_444_52911.html 

(3) https://www.bitkom.org/Presse/Presseinformation/Erstmals-beschaeftigt-Haelfte-Unternehmen-KI 

(4) https://de.statista.com/infografik/8751/durch-automatisierung-gefaehrdete-arbeitsplaetze/  

(5) https://www.heise.de/news/Studie-Nicht-weniger-aber-andere-Arbeitsplaetze-in-der-Industrie-4-0-3464689.html 

(6) https://digitalzentrum-berlin.de/unternehmen-nutzen-kuenstliche-intelligenz-bisher-kaum