Thomas Carlitz is an accomplished IT executive with extensive experience in leading teams in start-ups and large companies. He has successfully integrated Artificial Intelligence (AI) into numerous core business processes across various industries. Many AI applications continue to grow in importance and are being used by more and more companies and industries to optimise their processes. As Head of the Competence Center for Data AI at COCUS, Thomas Carlitz creates innovative AI solutions with his teams and drives AI development in companies.
AI development and trends: logistics, education & healthcare
1. How can companies and industries benefit from AI development?
“There are a large number of potential AI applications in many industries. In logistics, for example, AI optimises truck routes, shortens delivery times and reduces costs. In the education sector, it enables personalised learning content through data analysis, while in healthcare it improves diagnosis and treatment through expert knowledge. Wherever large amounts of data are available, AI can promote success and increase efficiency and decision-making quality.
Statistics prove the relevance of AI development: according to a recent survey, 25% of respondents see the greatest improvement through artificial intelligence in the workplace in time management, followed by an increase in productivity at 24%.
This makes it clear that artificial intelligence offers tangible benefits both in specialized areas and in the day-to-day business environment.”
Current challenges in the use of artificial intelligence
2. What problems does artificial intelligence pose for implementation in companies?
“I see the current legal situation regarding data protection, which is not always clear, as a challenge in the field of artificial intelligence. It is important that companies are aware of how they want to use their data before uploading it to publicly accessible systems. As such systems are accessible to everyone, careful consideration and planning should be given to what data should be used for in order to minimise risks and ensure sufficient data protection.
A recent survey of senior executives in Germany from 2023 shows that 41% of companies see a lack of technical staff as the biggest obstacle.
A further 30% report the lack of a governance model, while 29% identify the lack of a clear adoption strategy as a problem.
These obstacles make successful AI development difficult and require targeted measures to facilitate adoption.”
How companies can effectively introduce artificial intelligence
3. What role does data quality play in the success of AI projects in companies?
“Data quality plays a crucial role. It is important that companies ensure that the data is correct and well prepared before it is fed into the system. The training of AI systems in the company should be carefully monitored to ensure that the results are reliable and that the system does not draw false conclusions on its own.”
4. How can companies ensure that their employees benefit from new AI solutions and use them sensibly?
“It is important to raise employees’ awareness of the responsible handling of data, especially when anonymised data or a proprietary system is used. To this end, companies can offer targeted training on how to use AI. These measures increase employees’ understanding and responsibility in dealing with AI, enabling them to use the solutions sensibly and effectively.
A recent survey shows that 83% of respondents expect AI to bring significant changes to office work.
Interestingly, 23% of workers say they find AI applications helpful in their day-to-day work, while 24% see them as detrimental to their work.
These mixed views show how important it is to promote acceptance and understanding of AI in companies.”
Future AI development in companies and industries
5. Which AI development will be particularly relevant for companies in the coming years?
“Over the next few years, intelligent systems will become increasingly personalised and more tailored to specific sectors and industries. This specialisation will enable companies to use AI solutions that are precisely tailored to their needs. However, the extent to which these systems can be sharpened and adapted to specific industries will also depend heavily on future legislation.”
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