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Executive Search for AI-Specialists in Switzerland and Europe

Summary

Artificial intelligence is transforming the industrial landscape – from automated quality control to the development of new business models. While the potential is significant, implementation remains challenging: companies face complex technological, organizational, and regulatory hurdles. At the same time, there is a shortage of experienced specialists who can think strategically, execute technically, and embed AI across functions – competition for talent is intense.

 

Wirz & Partners supports organizations in filling critical AI roles – at C-level, on supervisory boards, or in specialized expert positions. Our mission: to identify individuals who not only understand AI but can translate it into tangible, long-term business value.

 

Why Clients Choose Wirz & Partners 


We follow a tailored search approach that combines technological understanding, industry insight, and cultural fit. We go beyond traditional role profiles to identify people who drive transformation and enable innovation. Our client base spans from publicly listed industrial enterprises to high-growth, PE- and VC-backed tech companies.

 

 

Artificial intelligence is transforming the industrial landscape. Whether in automated quality control, predictive maintenance, or the development of new business models – the use of AI offers enormous potential. To ensure this potential does not go untapped, companies and consulting firms alike depend on experienced AI specialists. And this is where the challenge begins: The market for AI experts is highly competitive, the required expertise is complex and constantly evolving. A shortage of skilled professionals, lack of in-house knowledge, and regulatory uncertainties are slowing down implementation.

 

Current Challenges in the Application of Artificial Intelligence in Industry

 

The integration of artificial intelligence into industrial processes can drive significant change: It improves production, reduces energy consumption, and creates space for new business models. However, implementation quickly reveals that the path to successfully leveraging AI is complex – especially in Switzerland and across Europe. Technological, organizational, and regulatory hurdles make adoption challenging and require targeted expertise.

The demand for qualified AI and IT specialists far exceeds the available supply. In particular, medium-sized companies struggle to find suitable experts with industry-specific experience.

The EU AI Act and national regulations create planning uncertainty and delay investment decisions. This is especially problematic in safety-critical industries such as pharmaceuticals or mechanical engineering, where compliance is a major concern.

Strict data protection laws and high security requirements make it difficult to implement data-driven systems – especially when sensitive production or customer data is involved.

The rapid advancement in AI technologies – such as large language models or edge computing – makes it challenging to select suitable solutions and integrate them into existing processes.

Many companies lack the in-house expertise or time capacity to systematically plan and implement AI projects. Without clear responsibilities and strategic integration, many initiatives remain stuck in the pilot phase.

Despite all the challenges, many companies recognize the potential of artificial intelligence. Already, 42% of industrial companies in Europe are using AI-based applications – and around another third are planning to get started. Interest is also growing in Switzerland: AI is increasingly being used in areas such as automation, robotics, and predictive maintenance, where it complements existing technologies in meaningful ways.

 

Requirements for Successful AI Implementation

 

For artificial intelligence to truly take hold in industrial applications, technical, organizational, and process-related conditions must come together.

 

Technological foundation

 

The foundation of every successful AI project is a reliable IT and data infrastructure. This includes clean, well-structured data, powerful cloud systems, and IT solutions that can be integrated with AI models. The choice of algorithms – such as Convolutional Neural Networks (CNNs) for image processing or Large Language Models (LLMs) for text – always depends on the specific use case.

 

Organizational requirements

 

For AI projects to move beyond the pilot phase, clear responsibilities, interdisciplinary teams, and flexible processes are essential. Key success factors include:

  • Support from top management to strategically anchor AI within the organization

  • Training programs to close knowledge gaps across the company

  • Agile methods to enable rapid learning and continuous development

  • Clear ethical guidelines – especially with regard to the EU AI Act and industry-specific regulations

Only when technology, organization, and processes work hand in hand can AI projects be implemented successfully – and translated into real, lasting value.

 

AI Applications in Industry: Successful Case Studies from the DACH Region

  • Predictive Maintenance (Liebherr, CH)
    Liebherr uses AI-powered sensors and machine learning to detect equipment failures early and optimize maintenance processes. This reduces costs and increases availability.1
  • Quality Control (BMW, DE)
    BMW employs AI-based image processing to detect defects in real time. This lowers waste and improves production efficiency.2
  • Drug Discovery (Roche & Novartis, CH)
    Pharmaceutical companies use AI to analyze chemical structures and accelerate the development of new medications – with higher success rates and shorter development cycles.3

 

1  https://www.liebherr.com/

2 https://www.press.bmwgroup.com/

3  https://www.handelsblatt.com/

 

New Leadership Demands in the Age of Artificial Intelligence

 

With the rise of AI technologies, it's not only business models that are evolving – expectations for leaders and decision-makers are also undergoing fundamental change. Today’s successful companies need strategic leadership at the executive level, as well as knowledgeable board members, advisory council members, or supervisory board representatives who understand technological developments, can critically assess them, and actively help shape their direction.

 

Whether at the executive level or in advisory bodies – what’s required are new skill sets, a shared vision for the future, and the ability to confidently navigate both the opportunities and risks of emerging technologies.

Executive Level

  • Strategically manage AI initiatives and embed them into the company’s overall development

  • Drive AI projects to operational success – with an agile mindset, iterative processes, and a clear focus on impact

  • Build data-driven organizations where teams possess the necessary expertise and the right mindset

  • Bridge technology and business to turn innovation into market-ready solutions

  • Foster a culture of openness and collaboration across functions and departments

  • Leverage AI & analytics to improve products, optimize processes, and rethink customer experiences

Non-Executive / Board Roles

  • Understanding the strategic relevance of AI and its impact on business models, market positioning, and company value

  • Competence in assessing technological opportunities and risks, especially in the context of investments, partnerships, or M&A

  • Awareness of regulatory developments such as the EU AI Act, data protection, and ethical considerations

  • Ability to ask critical questions – for example, regarding data quality, model transparency, or security

  • Experience in guiding innovation processes, whether from other industries, start-ups, or board engagements

  • An independent perspective to reflect on technology decisions in support of sustainable corporate governance

Conclusion

Artificial intelligence not only introduces new technologies but also reshapes the requirements for leadership and collaboration. Successfully navigating this transformation calls for individuals who combine technological expertise with strategic thinking and a willingness to drive change.

 

Wirz & Partners helps companies find exactly these kinds of people – whether at the C-level, on the board of directors, or in specialized roles focused on AI, data science, and machine learning. Our goal is not just to identify technically qualified candidates, but to find personalities who will actively shape your AI initiatives for the long term. In an era of data-driven business models, having the right people in place is often the decisive step toward implementing innovation and achieving sustainable growth.