Artificial intelligence is reshaping the global economy, with differing levels of adoption and impact across major regions. Speaking at the Brussels Energy Club, Istvan Czilik, CEO and founder of Revenue.AI, presented insights into how AI is projected to contribute to GDP growth in the coming years—particularly in the United States, where the technology’s influence appears set to outpace that of Europe.
Referencing recent market forecasts, Czilik noted that by 2030, AI’s contribution to the economy is expected to be significantly greater in North America than in Europe. These projections are based on existing trends in investment, digital infrastructure, and integration of AI across industries. “The data suggests a larger economic impact in the US, but that presents a valuable opportunity for Europe to further develop its AI strategy,” he explained.
In conversation with EU Today Editor Gary Cartwright, Czilik discussed some of the underlying factors. While regulatory frameworks may play a role in shaping adoption rates, he was careful to stress that each region has its own strengths. “There are differences in approach. The US model is often described as more flexible, while the EU places greater emphasis on safety, transparency and ethical standards,” he said. “The ideal scenario may lie in finding a balance between innovation and governance.”
Czilik also addressed growing concerns around the quality and security of data used to train AI systems. As artificial intelligence becomes increasingly embedded in decision-making processes—whether in energy trading, logistics, or public administration—the integrity of the data it consumes is vital.
Asked whether there is a risk that malicious actors could feed false data into these systems, Czilik confirmed that the possibility exists. However, he was quick to draw historical parallels. “Providing misleading information is not new—it’s something we’ve seen in markets for decades. What’s important is how we detect, verify, and respond to such input.”
Tools such as generative AI rely heavily on the quality of their training data. Misinformation, including so-called “deep fakes”, presents challenges not only for end users but also for the developers building AI models. “If people are not aware that the data being processed is flawed, they may be misled,” Czilik noted. The solution, he suggested, lies in digital literacy, robust validation processes, and continued refinement of AI systems.
The discussion also touched on the differences between various AI platforms, particularly in terms of their access to live versus historical datasets. “Some tools work with up-to-date information, while others are based on static datasets. Knowing which model suits which task is essential,” he said.
Intellectual property is another area under scrutiny, with ongoing legal cases examining whether certain public or proprietary content has been used to train AI without consent. Czilik highlighted the importance for organisations to consider training their own AI tools using internal data. This not only strengthens relevance but also avoids potential legal uncertainty.
Cartwright, reflecting on his own use of tools such as ChatGPT and Grok, remarked on their usefulness for research and analysis. “It’s the most effective research aid I’ve encountered in years of journalism,” he said. Czilik agreed, describing AI as a powerful enabler across virtually every sector. “It’s augmenting human performance at an extraordinary pace. The potential is vast.”
Although AI’s evolution remains in its early stages, Czilik observed that recent advances have already surpassed many expectations. “Where we are today is far beyond what many anticipated just five years ago. But the journey is still ongoing.”
As the EU moves forward with its AI Act, Czilik’s remarks underscore the importance of dialogue between policymakers, developers, and end users. While regulatory clarity remains essential, it must be aligned with the need for innovation and practical application. Europe, he suggested, is well-positioned to shape the next phase of AI development—drawing on its strengths in governance, data privacy, and cross-sector collaboration.
“The technology is here,” he concluded. “Now it’s about how we use it—responsibly, effectively, and strategically.”
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