Artificial intelligence (AI) is changing the business world at a rapid pace. Companies around the world are using AI to optimize their processes, reduce costs and increase their competitiveness. The various use cases for AI go far beyond the field of marketing. However, the challenge remains to translate the theoretical use cases into real use cases and thus make them measurable. Where and how exactly can AI be used sensibly in day-to-day business and generate a real impact?
AI vs. antibiotic resistance
We are only just beginning to fully exploit the potential of AI. Artificial intelligence (AI), for example, solved a ten-year scientific problem on antibiotic resistance in just 48 hours. Researchers at Imperial College London developed the hypothesis that superbugs use genetic elements of bacteriophages to move between hosts.
Professor José R. Penadés tested Google’s AI tool Co-Scientist by entering a summary of the problem. The AI not only confirmed his hypothesis, but also generated four other plausible theories, including a completely new one. This is now being researched further.
Despite the speed of the AI, Penadés emphasizes that it does not replace human scientists, but rather serves as a powerful tool. The AI was only able to deliver its results so quickly because it was based on targeted preliminary work by the team.
This example shows how AI can revolutionize research by validating hypotheses and providing new approaches. In particular, it could play a decisive role in the fight against antibiotic resistance in the future. (Source in german t3n)
AI vs. eye diseases
Another study in the field of ophthalmology produced similar results. The diagnostic results of ophthalmologists were examined in comparison with general practitioners and ChatGPT 4.0.
The two examples mentioned from the medical field impressively illustrate how artificial intelligence (AI) serves as a supportive tool for people. It does not replace specialists, but offers valuable help, especially with long-standing, difficult-to-solve problems. As soon as AI is fed with the relevant data, it can enable enormous progress. Although it cannot solve complex challenges independently, it can provide decisive impetus.
It is not possible to simply feed an AI with the instruction to cure a disease such as cancer. However, by combining global research data and various theories, it can generate new insights and reveal previously unknown research approaches. These examples show that AI can create innovative theories that have not yet been researched. This opens up new possibilities for science and medicine and holds great potential for the future.
AI vs. mining
Artificial intelligence is also revolutionizing the search for raw materials. An industry in which high-tech is less expected. The startup Earth AI uses state-of-the-art algorithms to discover valuable minerals such as cobalt, copper and gold in unexpected places – and with an impressive hit rate. Traditional search methods had a hit rate of just 0.5 percent. Thanks to Earth AI, it rose to 66 percent! The technology tracked down previously overlooked mineral deposits – including copper, cobalt and gold in the Northern Territory and silver, tin and molybdenum in New South Wales.
Earth AI is not the only company using AI to search for raw materials. The start-up KoBold Metals also discovered large copper deposits with the help of AI – for example in Zambia. The digital treasure hunt has therefore long been in full swing.
And it is precisely this approach that should be transferred to the economy and SMEs in particular.
8 AI use cases in the business world
1. Marketing and sales
Personalized advertising: AI makes it possible to tailor advertisements precisely to the needs and interests of the target group. AI uses machine learning to analyse consumer behaviour and optimize in real time.
Sales support through chatbots: AI-based chatbots can be used in sales processes to qualify leads and interact directly with customers without human intervention.
Sentiment analysis: AI recognizes customer sentiment in social media or reviews and enables companies to proactively respond to negative feedback and improve their brand perception.
2. Customer services
Automated service requests: AI-supported systems answer customer inquiries quickly and efficiently, reducing waiting times and increasing customer satisfaction.
Speech recognition and transcription: AI-based technologies can recognize spoken language and convert it into text. This helps to create logs for customer inquiries and improves knowledge bases for future inquiries.
3. Logistics and transportation
Supply chain optimization: AI can predict delivery routes, detect bottlenecks in real time and suggest alternative routes to shorten delivery times and reduce costs.
Predictive routing: Based on current traffic data, AI predicts the best routes for deliveries, optimizing not only speed but also emissions.
4. Human resources and HR management
Automated recruitment: AI helps to find suitable candidates for job advertisements by automatically analyzing CVs and applications and filtering out the best applicants.
Predictive HR analytics: AI-based systems analyze employee data and predict which employees are most likely to leave the company, allowing proactive measures to be taken to retain them.
5. Healthcare
Diagnoseunterstützung: KI wird zunehmend in der medizinischen Diagnostik eingesetzt. Sie analysiert medizinische Bilddaten und hilft Ärzten, schneller und genauer Diagnosen zu stellen.
Robotergestützte Chirurgie: KI-gesteuerte Roboter verbessern die Präzision in der Chirurgie, indem sie genaueste Bewegungen ermöglichen und so das Risiko von Fehlern reduzieren.
6. IT and information security
Automated security monitoring: AI-based systems monitor networks in real time and identify potential threats before they can cause damage.
Behavioral analysis: AI helps to identify atypical user behavior that could indicate security vulnerabilities or potential attacks.
7. Research and development
Automated simulations and hypothesis generation: AI is used to generate new hypotheses and test them quickly using simulations. This saves time and speeds up the innovation process.
AI in pharmaceutical research: By analyzing large amounts of data, AI can suggest new drugs and treatments that might have remained undiscovered without it.
8. Finance
Algorithmic trading: AI-based systems analyze financial markets in real time and automatically make decisions about buying or selling shares and other assets.
Fraud detection: By analyzing transaction data, AI can detect fraudulent activities and initiate immediate countermeasures.
Conclusion
AI offers enormous potential for companies in various areas. Whether in marketing, logistics, customer service or research – the possibilities are virtually unlimited. Companies that use AI efficiently can not only increase their efficiency, but also secure their innovative strength and competitiveness in the long term. The integration of AI technologies is therefore not just a question of increasing efficiency per se; it is a decisive factor for long-term success in an increasingly digitalized world. The future belongs to companies that are prepared to adapt these technologies and think innovatively – because this is the only way they can survive in the face of global competition.
