Make Your Logistics Ready for the AI Revolution: TAL 2025 Speakers Share Their Experience
Aimtec
29. 5. 2025
9 minutes reading
The automotive industry stands before a revolution. The rise of artificial intelligence is changing established processes and bringing new possibilities. But what obstacles are companies having to overcome so that they can deploy AI effectively? The experts and industry leaders appearing at Trends in Automotive Logistics 2025 – with the tagline “Digital. Future-Proof?” – are sharing their experience and viewpoints on the key challenges in deploying AI.
Tobias MayrGeneral Manager IT Inbound LogisticsBMW Group
Tobias leads a global IT team for inbound logistics at all the plants of BMW Group, and he has a twenty-year career in IT roles across multiple continents behind him.
At TAL 2025, he spoke about the road to logistics digitalisation at BMW Group and about the comprehensive logistics analytics platform that helps them to respond to the market developments. He also described their standardised global template based on the SAP S/4HANA system.
What are the main challenges when deploying AI in industry, and how can you overcome them?
1. Data quality and availability
In automotive, data is often fragmented and inconsistent.
Solution: Introduce reliable data management processes that take care of data collection, cleansing and standardisation throughout all your departments.
2. Integration with your legacy systems
Your legacy systems may not be compatible with modern AI technologies.
Solution: Develop a gradual integration plan that enables modernisation and ensures new solutions can work together with existing systems. Consider the use of middleware to bridge the gaps between technologies.
3. Compliance with regulations and security
Because of the regulations in automotive, it can be challenging to ensure compliance with security standards when you’re deploying AI.
Solution: Study all the regulations right at the start of development so that you can understand all the requirements. Don’t forget strict testing and validation to ensure your artificial intelligence systems meet the security standards.
4. A lack of qualified workers
There’s a lack of experts who understand both AI and the automotive industry.
Solution: Invest in the development of your existing employees. Work with educational institutions and create programmes to prepare future talents for roles in the areas of AI and automotive technologies.
5. Cultural resistance
Your employees may be defensive towards the changes that AI deployment brings, due to fears of a shift in jobs or unfamiliarity with new technologies.
Solution: Support a culture of innovation and constant improvement. Inform people clearly about the benefits of AI and involve employees in the deployment process to gain their support.
Tomáš BrotzAutomation Engineer for Automotive StandardsSiemens
Tomáš joined Siemens as an expert in the standardisation of industrial automation after more than twenty years of experience with global projects in automotive.
At TAL, he discussed the benefits of standardisation, technical solutions and examples of practical implementation in the course of industrial automation.
What are the main challenges when deploying AI in industry, and how can you overcome them?
Michal ŠtěrbaChief Executive OfficerGZ Media
CEO and Board Member of GZ Media, the world leader in vinyl record manufacturing, which has recently expanded into the USA and Canada.
In his talk, he presented a smart logistics, automation, and AI integration project—covering its inception, development, and the benefits it has brought to production efficiency. He explained what makes their transformation truly revolutionary.
What are the main challenges when deploying AI in industry, and how can you overcome them?
Thilo JörglManaging Partner, impact media projectsTEST CAMP INTRALOGISTICS
Thilo is a journalist and an expert in supply chains, automation and robotics. He heads impact media projects GmbH, and he is engaged in the leadership of several major logistics initiatives.
He spoke about the impact of the Silicon Economy on supply chain management and the role of artificial intelligence, and he also presented an award-winning automation solution that was put through its paces at TEST CAMP INTRALOGISTICS.
What are the main challenges when deploying AI in industry, and how can you overcome them?
1. No real added value
A lot of companies want to use artificial intelligence just because people are talking about it, not because they’re looking for clear added value, for example in customer satisfaction, the development of cross-selling and upselling, process optimisation and the improvement of quality.
2. A lack of communication
If users aren’t told about the use of artificial intelligence, they can’t even be aware they’re communicating with an AI-supported system. Later on that can lead to a loss of trust and rejection.
3. A low-quality database
Artificial-intelligence systems typically identify repeating patterns in large amounts of data; if the database is insufficient, their results are not relevant.
4. Blind faith
Even though IT systems sometimes display amazing “intelligence”, they’re not always suited for AI, for example if it’s not possible to provide data that can be sufficiently put to use in operations.
5. A lack of transparency
In light of the many influencing factors and methods determining the results from AI, it can be difficult or even impossible to sufficiently understand how a given result has been reached.
Rostislav SchwobSupply Chain Solutions DirectorAimtec
Rostislav serves as a board member at Aimtec and has spent many years leading projects focused on the digitalisation and automation of logistics and manufacturing worldwide. He stood behind the creation of Aimtec DCIx and plays an active role in the company’s strategy and the development of products that reflect the latest trends and customer needs.
What are the main challenges when deploying AI in industry, and how can you overcome them?
But if feedback isn’t easy and natural, people won’t provide it, because they won’t see the point. Yet when the whole process is set up well, we get a functional solution as well as a system for permanent change.
Mojmír BarákLogistics Systems CoordinatorŠkoda Auto
Mojmír Barák is currently the head of the Digital Delivery Center at Škoda Auto Logistics, where his team works to accelerate the company’s digital transformation.
In his talk, he presented not only their current and future AI plans, but also the challenges that need to be overcome on the way to a future powered by artificial intelligence.
What are the main challenges when deploying AI in industry, and how can you overcome them?
Václav KopeckýHead of Key Accounts – Czech RepublicSTILL Czech Republic
Václav leads the team of managers in charge of Key Accounts at STILL ČR and boasts over twenty years of experience in logistics. In recent years, besides conventional solutions, he has mainly focused on automation projects implemented across multiple market segments.
At TAL, he took part in a panel discussion on trends in Czech logistics, where he shared his experience with deploying automation technologies at customer sites.
What are the main challenges when deploying AI in industry, and how can you overcome them?
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