Artificial Intelligence has long played an important role in companies. However, new applications like ChatGPT are currently accelerating the accessibility and speed of their spread. At the same time, the criticism ranges from a lack of empathy to scenarios of a global seizure of power. It becomes clear: regulation of AI is important and necessary, because it can no longer be stopped!
AI is now not just something for large corporations. Smaller or medium-sized companies can also benefit sustainably from AI . In this blog post we look at the areas in which companies can use AI for themselves and give examples of possible applications:
Automation of tasks and processes
The use of AI-supported automation can bring companies high efficiency and cost advantages. Particularly monotonous tasks are well suited to be taken over by an AI. In the case of error-prone activities, e.g. B. the quality can also be ensured. This is particularly important in areas of production or healthcare. However, AI-supported automation can also be used to make processes more sustainable, e.g. B. through more efficient use of raw materials and energy resources. Another potential area for applying AI is software development. AI also supports this by performing simple programming tasks. In the future, more complex approaches will also be added if there is enough data and learning effects.
The examples listed make it clear that the possible field of application for AI-supported automation is very broad and harbors many efficiency advantages. The resulting time savings also free up more resources for employees. Overall, this not only increases productivity, but also promotes creativity. Employees are relieved of monotonous tasks and can invest more time in things that require more human thinking. All in all, a possible win-win situation for everyone involved.
Improved market and customer understanding
When incorporating AI into research or analysis, companies can benefit from better market insights. AI can provide support here because it is able to process and evaluate large amounts of data quickly. This is a major advantage, especially in market research. An example is the implementation of target group analyses . AI-supported methods enable complex evaluations that can combine different data sources and data types (e.g. image data). This leads to quick and reliable statements about the behavior and needs of customers. Also individual customer surveys can be performed using AI. During an online survey, the AI can detect deviations in the answers and ask additional control questions to ensure the validity of the statements. In this way, companies can better understand the needs of their customers and possible market trends. They can in turn incorporate the knowledge gained into product developments or their range of services. But you can also better understand what the key success factors are in the market and how market competitors fulfill them. These include e.g. B. important product features, delivery readiness or pricing. With such insights, companies can continuously improve their strategies and act close to the market.
Improved customer services and experiences
Customer services can be improved through the use of AI. Chatbots can interact with customers individually and in a personalized way. This brings advantages for companies and customers at the same time. These include e.g. B. 24/7 availability, shorter response times and the processing of a higher volume of inquiries. Users can thus use services individually and flexibly in terms of time. Companies, on the other hand, can make their customer service even more customer-oriented and at the same time book efficiency advantages for themselves.
In addition to customer service, AI can also be used to improve the customer experience. Customers receive all the information they need or additional recommendations at the relevant touchpoints with the company. This makes the shopping experience much more pleasant. In addition, the customer experience be personalized and individually tailored to individual customers, e.g. B. in the form of relevant content or product offers. Even if the technology is not that advanced yet, in the future AI will be able to recognize emotions and intentions of customers and adapt to them. This gives companies the opportunity to create unique experiences or WOW moments for their customers. This has a positive impact on customer satisfaction and can also be used as an important differentiator. Customer experience can be an important success factor, especially in saturated markets where product-level differentiation is difficult.
Optimization of sales efficiency and processes
Due to the processing of large data sets in a short time, AI can also help companies to optimize their annual sales and revenue targets. An analysis of existing customer data helps to identify purchasing patterns, individual preferences and unmet needs. This enables an improved assessment of which services individual customers or customer groups might be interested in and where a personalized offer makes sense. This can increase the probability of a degree. The relevant data analyzes can also be used to identify necessary improvements to your own services. So lost sales opportunities z. B. be the result of a missing product feature. Targeted pattern recognition can help to recognize this. This enables early adjustments to the product before the relevant feature becomes a hygiene factor. AI can also be used to optimize sales business processes (e.g. sales forecasts) in order to achieve greater sales efficiency. Based on existing data, special features such as seasonality, competition or existing trends can be included in the sales forecast. This helps to act with foresight and to shorten reaction times in the event of deviations from the plan. competition or existing trends are included in the sales forecast. This helps to act with foresight and to shorten reaction times in the event of deviations from the plan. competition or existing trends are included in the sales forecast. This helps to act with foresight and to shorten reaction times in the event of deviations from the plan.
Content creation for marketing purposes
With the help of AI, companies can also use their data to develop content strategies. By analyzing content and its popularity, approaches can be derived to make content more attractive for customers. In addition, customer reactions can be analyzed and necessary adjustments can be derived, even in real time. That’s not all: AI also helps to make the content creation process more efficient and creative by suggesting ideas or taking on tasks in the creation. The best-known applications include ChatGPT or Dall-E. These make it possible to create content in the form of text and images and only in fractions of the normal time. This brings huge potential in terms of efficiency or personalization. We encounter content generated by AI more and more frequently in everyday life. However, they are not always directly recognizable. One often speaks of deep fakes. These are fakes of people or events in audio, photo or video form. With a little imagination, it quickly becomes clear what dangers deep fakes can entail in connection with social media.
Data-driven management and decisions
Data is an important basis for business success for companies. The use of AI can help to process and interpret large data sets from different company areas or sources quickly and precisely. In this way, important patterns can be identified. These can in turn be used as a basis for objective decisions or serve as forecasts. So more facts and fewer assumptions. Depending on the company structure, individual company areas can be viewed or compared, up to a cross-area representation.
In this way, AI can support sales, resource, production or investment planning and provide reliable statements. Of course, reliability is based on the quality of the data used and a defined learning process. Both should be continuously enriched with additional data and further developed. Analyzes are becoming more and more precise and lead to better decisions. However, AI can also be used to automate decisions. An example is the purchase of raw materials. Data sources (e.g. ERP or supplier contracts) and parameters (e.g. prices, exchange rates or shipping costs, etc.) can be defined here and used for automated decisions and orders.
Development and retention of employees
The shortage of skilled workers has now reached all sectors. In order to counteract it, companies must also break new ground in the development and retention of employees. AI can help to support employees in their personal development and to achieve greater loyalty to the company. You can e.g. B. can be used for individual and needs-based training. This not only keeps employees up to date, it also promotes career opportunities. With the help of data analysis, possible developments or risks can also be identified. In this way, potential becomes visible and problems (e.g. knowledge deficits) can be tackled at an early stage.
Companies such as IBM ( Watson Classroom ), Google ( Qwiklabs ) or Siemens ( Siemens Learning Center ) are already using AI-based platforms to train their employees. But even smaller companies that do not have their own solution can benefit from AI-supported learning platforms, e.g. B. by external providers such as Udemy , edX or educated. This also enables the development and growth of employees. As mentioned at the beginning of the article, AI can relieve employees by relieving them of repetitive, monotonous tasks. In this way, individual abilities and strengths can be better supported and potential can be promoted.
Improved IT security
The topic of IT security is becoming increasingly important and poses a major challenge for companies. Especially with a growing and distributed IT infrastructure that has to reconcile a wide variety of architectures, systems and applications such as cloud, mobile and ERP. Here AI can help companies to develop modern and individual security systems. Through complex data analysis, AI enables early detection of threats and vulnerabilities. Response times can be significantly reduced in this way. This is e.g. B. possible through a continuous analysis of network and data traffic, user behavior or server activities. Here, too, companies can use AI to automate processes and use the resulting efficiency advantages for themselves.
In the future, AI will be able to detect cyber attacks at an early stage and combat them efficiently. Due to the individual requirements, however, every company must find the right AI solution for itself and, if necessary, adapt it to its own use case.
The examples listed above make it clear that AI can be used in many areas of a company. She is able to perform various functions or tasks. As a result, companies have to decide for themselves how they want to use AI and for what purpose. Should e.g. For example, is efficiency to be increased in a company division or is it more a question of maximizing sales, or both? No easy questions to answer. But one thing is clear: if companies manage to activate the extensive amounts of data for themselves (e.g. for pattern recognition), they can exploit the potential of AI for themselves and thus develop new business opportunities.