Expert insight: How to successfully implement AI

What patterns do you see in how the most forward-thinking organisations adopt AI?

Emmanuel Vivier: Leading companies aren’t just testing artificial intelligence (AI) – they’re integrating it into core operations. AI is being deployed to streamline internal processes, enhance customer experiences and enable faster, more informed decision-making. However, to make this transformation possible, businesses heavily invest in strong data infrastructure and governance. After all, AI systems are only as effective as the quality of the data they rely on.

Building AI readiness among employees is another top priority. AI-focused companies invest in continuous training programmes and create a culture that values data literacy and comfort with new technologies. The goal isn’t to replace employees, but to empower them with AI tools that enhance their capabilities and make their jobs easier. 

Forward-thinking firms form strategic partnerships, recognising that innovation rarely happens in isolation.
Emmanuel Vivier, HUB Institute

They are also establishing clear policies to ensure transparency and accountability, especially around sensitive data. As AI adoption grows, so do the cybersecurity risks associated with it. Businesses respond by investing in stronger cybersecurity systems and educating their teams on how to remain secure in an increasingly digital environment.

Many companies use a "test & learn" approach to move from experimentation to scaling AI. This agile method helps identify valuable applications and extend them across teams. Forward-thinking firms also form strategic partnerships, recognising that innovation rarely happens in isolation. They carefully weigh the benefits of building AI solutions in-house versus sourcing them externally.

What are the most critical skills employees and leaders will need to thrive in a hybrid human-AI workplace?

Understanding how AI works is no longer optional; it is essential. Employees must grasp prompt engineering, be able to use dashboards and data-driven insights and understand automation workflows. Adaptability – learning, unlearning and relearning – is key. Both staff and management must be open to acquiring new skills, rapidly mastering new AI tools and feeling comfortable navigating ambiguity and experimentation. 

Data protection and trust are strategic imperatives in AI-driven workplaces. Organisations need to ensure that all collaborators can recognise AI-enabled phishing, fraud or hallucinations and understand how shared models may leak sensitive prompts or data.

Both staff and management must be open to acquiring new skills, rapidly mastering new AI tools and feeling comfortable navigating ambiguity and experimentation. 
Emmanuel Vivier, HUB Institute

I also believe that human traits such as emotional intelligence and empathy will become more valuable as routine tasks are automated. Skills like active listening and empathetic leadership will shape staff wellbeing and customer experience. 

What are the most common pitfalls organisations face when implementing AI?

Many companies encounter the same challenges that hinder them from achieving meaningful outcomes. Issues relating to the following areas often derail AI transformation efforts:

• AI needs strong leadership and real budgets – not just verbal support. Too often, companies hesitate to commit significant resources, leaving teams underfunded and isolated.
• AI success requires specialised talent – relying solely on existing teams limits scale. Recruiting or upskilling the right individuals is crucial to developing sustainable AI capabilities.
• Without training and change management, adoption stalls. Employees require targeted training to comprehend the impact of AI on their work and to utilise new systems effectively. Change management should be embedded to overcome resistance and ensure adoption across the company.
• AI must involve all departments – not just IT – to align with business needs. Shared ownership across functions also supports responsible governance and the ethical implementation of policies.
• AI projects must be appropriately scoped. Some organisations start too small with minor tools that don’t unlock deeper value. Others launch massive programmes with high costs before validating needs and readiness. A balanced strategy begins with focused pilots and scales based on results and lessons learned.

Avoiding these pitfalls requires a strategic and realistic approach to AI. This includes leadership commitment, adequate resources, the right skills and a collaborative culture. With the proper foundations, AI can become a powerful driver of innovation and long-term business performance.

How do you perceive Luxembourg’s potential as a strategic European hub for companies looking to accelerate their data and AI-driven operations?

Luxembourg’s unique blend of digital maturity, financial expertise, legal robustness and global openness makes it a strategic launchpad for AI in Europe. Having lived in Luxembourg for over eight years, I am convinced that its future goes far beyond finance – while still building on that strength. For foreign companies seeking to establish trustworthy, scalable and regulation-ready AI operations, the country offers an unmatched combination of strengths. 

Its central EU location and multicultural, highly skilled workforce make Luxembourg an ideal base for serving diverse Western European markets. The linguistic and cultural versatility supports AI model training, localisation and deployment. The country also facilitates compliance with EU regulations, such as GDPR and the upcoming AI Act, due to its proximity to European institutions. 

Luxembourg’s unique blend of digital maturity, financial expertise, legal robustness and global openness makes it a strategic launchpad for AI in Europe.
Emmanuel Vivier, HUB Institute

Trust is central to data-driven strategies, and Luxembourg delivers with political stability, pro-business policies and a transparent regulatory framework. The country is recognised for its strong commitment to data privacy and cybersecurity, which makes it ideal for companies handling sensitive or proprietary data. Luxembourg’s advanced digital infrastructure – including secure data centres and high broadband coverage – underpins real-time AI and edge computing.

As a global financial hub, Luxembourg fosters AI innovation through regulatory sandboxes and public-private partnerships. Institutions such as the Luxembourg Institute of Science and Technology (LIST) and the Interdisciplinary Centre for Security, Reliability and Trust (SnT) drive cutting-edge research in AI, cybersecurity and autonomous systems. The government also promotes AI adoption, supporting startups and corporates in prototyping and deploying AI technologies.

Luxembourg may not be Silicon Valley, but it serves as a strategic crossroad within the EU: neutral, multilingual and driven by innovation. Its unique ecosystem positions Luxembourg as a future safe haven for ethical, high-performance AI in Europe.