Digital transformation will remain a key driver for organisations worldwide in 2025. In an era characterised by global crises, economic uncertainty and rapid technological change, the issue of resilience is becoming increasingly important. But what really makes organisations resilient? Alongside agile structures and robust strategies, one key technology is coming increasingly into focus: artificial intelligence (AI). AI can not only help to identify risks at an early stage and optimise processes, but also support the development of proactive solutions. It is therefore no surprise that AI is set to be one of the key themes of 2025. The latest CxO AI Survey by analysts at PAC (Pierre Audoin Consultants) has identified key IT trends that will shape businesses in 2025. Here, too, the focus is particularly on artificial intelligence (AI), but also on data sovereignty, AI governance and the growing need for IT investment.
1. Sharp rise in IT investment
Companies are planning to invest significantly more in their IT over the next two years. Around 35 per cent of respondents state that they wish to increase their spending by between 26 per cent and 50 per cent. This growth reflects the mounting pressure to invest in forward-looking technologies that enable innovation and competitive advantages – particularly in AI, data analytics and cloud solutions. These figures illustrate that IT is no longer merely a supporting function, but is increasingly playing a central role in companies’ strategic direction.
2. Artificial Intelligence as a Strategic Priority
AI is at the heart of digital transformation and will continue to grow in importance by 2025. 39 per cent of respondents state that AI is a high priority and is supported at C-level. 29 per cent even regard AI as the top priority, firmly embedded in their company’s core strategy. These figures demonstrate that companies are increasingly recognising how crucial AI is to their future competitiveness. From optimising internal processes to developing new business models and improving the customer experience – AI will play a key role in the coming years.
3. Challenges in AI adoption
Despite the high willingness to invest, the study shows that the use of AI technologies is associated with numerous challenges: around 28 per cent of respondents cite a lack of understanding of AI use cases as the biggest problem in a business context. Many companies find it difficult to identify the potential of AI in a targeted manner and apply it to their individual requirements. Furthermore, employees and managers often harbour reservations about AI, whether due to fears of job losses, scepticism about the technology or a lack of knowledge. This can hinder acceptance and adoption. Security concerns, such as the fear of data manipulation, also often play a role.
4. Focus on data sovereignty and governance
Many companies lack a clear strategy for how to collect, store, analyse and utilise data. Data quality is often inadequate, which can severely impair the performance of AI models. In addition to operational implementation, companies are grappling with regulatory and ethical requirements. Regulations, particularly regarding data protection (e.g. the GDPR in Europe), and ethical concerns can complicate the introduction of AI. Companies must ensure that their AI systems are transparent, fair and secure.
- Data sovereignty: They must ensure that data sovereignty and data protection requirements are complied with.
- AI governance: Clear rules and processes must be established for the use of AI.
- Data quality: High-quality, consistent data is required as the basis for valid AI models.
These requirements make it clear that the introduction of AI goes beyond purely technical issues and requires comprehensive governance structures.
5. Shortage of skilled IT staff
Around 33 per cent of companies regard the AI skills of their IT teams as a key challenge. The shortage of experts in AI, data science and machine learning is one of the biggest hurdles. This affects both the development of models and their integration into existing systems. Companies must invest more heavily in the training and recruitment of AI specialists in order to keep pace with technological developments. Building a competent team that not only understands the technical aspects of AI but can also assess its strategic implications is becoming essential.
Conclusion
The IT trends for 2025 paint a clear picture: companies are prepared to invest heavily in their IT infrastructures and, in particular, in AI. However, despite this determination, successful implementation remains a challenge involving technological, organisational and regulatory hurdles. Those companies that invest early in talent development, data quality and governance structures will have the best chance of harnessing AI as a driver of innovation and growth. However, alongside increased investment in technology, organisational adjustments, talent development and the implementation of governance structures are necessary to fully realise the potential of AI and data-driven approaches by 2025.
