In our latest State of Generative AI in the Nordics Q4 report, we investigated how the Nordics fare against global peers in scaling and implementing generative AI (GenAI). What particularly characterized the Nordics was a cautious, but perhaps measured, approach to GenAI implementation.

With almost half (43 %) of the respondents from our Q4 dataset residing in the US, we wanted to understand how the Nordics compared to closer-to-home countries in Europe, who operate in similar regulatory and cultural environments. Therefore, in this article, we are zooming in on what the Nordics can learn from regional peers in Germany, the Netherlands, and the UK.  

How do the Nordics compare with regional peers?

Nordic patience and lack of top management interest stands out – even when comparing to regional peers

The cautious approach to GenAI adoption and implementation that was identified in our State of GenAI Q4 report appears to remain a distinguishing characteristic of the Nordics when compared to our local neighbors in Germany, the Netherlands and the UK.

In particular, the tendency of much lower top management interest in GenAI persists when contrasting the Nordics to regional peers (figure 1a). This may indicate that the transformational potential of GenAI is not fully acknowledged from an executive and strategic perspective in the Nordics. At the same time, Nordic technical leaders show high enthusiasm regarding GenAI, which is on par with European counterparts (89 % versus 85-88 %). This could indicate that Nordic organizations have a strong grassroots foundation at the technical level but lack senior support to scale to the next level.

Figure 1: What sets the Nordics apart from regional peers? 

State of Generative in the Enterprise Q4 survey, N (Nordic) = 170, N (Germany) = 150, N (Netherlands) = 50, N (UK) = 200.

Building on this, 29 % of Nordic respondents report difficulties choosing the right technology as a key barrier to adoption, which is more than double of regional peers (figure 1b). Another central barrier in the Nordics is implementation challenges, reported by 35 % of respondents versus by about a quarter of regional peers (figure 1c). Scaling GenAI needs more than just technology; it requires robust governance, integrated risk management, executive buy-in, and a viable business case¹.

Together these barriers suggest that the Nordics are still too focused on the technical aspects of the technology and are not working sufficiently on identifying specific use cases for their organization from a more strategic perspective.

Another noticeable difference between the Nordics and our regional peers that mirror the findings in our recent report is that the Nordics display higher levels of patience in allowing GenAI initiatives to mature, with 71 % willing to wait more than 18 months before reducing investments, even if value targets are not being met (figure 1d). The higher levels of patience may also be reflected in the expectations towards scaling, where the Nordics are expecting fewer of their GenAI experiments and proof-of-concepts to scale fully within half a year than regional peers (figure 1e).

Collectively, these tendencies of higher patience, lower scaling expectations and larger struggle to choose the right technology suggest a fast-follower rather than early-adopter approach to GenAI in the Nordics. This may explain why neighboring regions are already investing more in autonomous agents, potentially putting the Nordics at a competitive disadvantage given the significant potential of agentic AI (figure 1f).

What can the Nordics learn from the United Kingdom?

The UK stands out for its high levels of excitement and fascination with GenAI, with 57 % and 54 % of respondents respectively expressing these sentiments – both notably higher than in the Nordics (figure 2a and 2b).

Research and development (R&D) is especially distinct when examining implementation across various functional areas, with 41 % of respondents from the UK indicating limited or at-scale implementation, in contrast to 29 % in the Nordics (figure 2c). This higher degree of R&D implementation could be linked to strong university and government support in R&D in the UK, creating a culture of innovation and experimentation. This no doubt also supports a strong talent pool, and high level of AI fluency and awareness – factors which are critical for scaling GenAI across an organization.

The UK also experiences fewer implementation challenges, with only 26 % reporting difficulties versus 35 % in the Nordics (figure 1c). This might be attributed to the UK’s higher degree of maturity in this field. For example, Model Risk Management (MRM) regulations, especially within the financial sector, have been high on the agenda for many years. Additionally, the UK exhibits more of a principles-based approach to approaching new regulations rather than a strict rules mindset, which could also explain this higher level of confidence in navigating AI implementation. Development of responsible AI is also high on the political agenda, with the UK government announcing of a new AI assurance platform in November 2024.

Nordic organizations are unlikely to be able to significantly influence the political or regulatory agendas to mirror the UK, at least in the short term. However, embracing a more proactive and risk-based approach, such as applying principles in risk management rather than waiting for rules could help to accelerate progress. Combining this with Nordic pragmatism could help ensure responsible and trustworthy AI implementations without falling behind competing countries.

For more insights into GenAI adoption and trust in the UK visit The impact of Generative AI on UK businesses: a deep dive

Figure 2: Nordics vs. the UK

State of Generative in the Enterprise Q4 survey, N (Nordic) = 170, N (UK) = 200.

What can the Nordics learn from Germany?

The disparity in GenAI interest among top management when comparing the Nordics to their peers, is particularly striking when contrasted with German executives, who show the highest levels of interest (figure 1a). Such strong top-down commitment likely fuels Germany’s robust experimentation culture, with Germany reporting the highest volume of GenAI experiments (figure 3a) as well as the highest expectations towards scaling these experiments within the next six months (figure 1e). In combination with the heightened concern among German respondents about the risk of not achieving expected value, it suggests that the Germans adopt a value-driven, fail-fast approach. This means that experimentation and scaling are prioritized, but also closely monitored to ensure the realization of expected value.

This fail-fast approach may explain why the Germans are less fearful of mistakes leading to real-world consequences than the Nordics (23 % versus 45 %) (figure 3b) Similarly, they are less concerned about complying with regulations (32 % versus 46 %). This lack of concern suggests a greater willingness to take calculated risks or a clearer approach to tackle common implementation barriers.

Moreover, the German respondents consider a lack of technical talent a more significant barrier to GenAI implementation than the Nordics (figure 3c). Potentially, the high levels of experimentation in Germany have resulted in a better understanding of the competencies needed for successful scaling, while the Nordics may pay less attention to this barrier because they do not yet fully grasp the skills required to advance their GenAI activities to the next level.

Combined, Nordic organizations can learn from Germany's robust leadership involvement and proactive experimentation to accelerate GenAI adoption and implementation effectively.

For more insights into Germany’s advancements and strategic approaches in scaling GenAI visit AI Study: Accelerating AI Transformation.

Figure 3: Nordics vs. Germany

State of Generative in the Enterprise Q4 survey, N (Nordic) = 170, N (Germany) = 150.

What can the Nordics learn from the Netherlands?

Like the UK, the Netherlands show strong GenAI implementation within R&D, with 42 % of respondents reporting limited or at-scale adoption. Dutch organizations also report the highest levels of trust in GenAI, with 54% expressing high or very high trust compared to 40 % in the Nordics (figure 4a).

While the Netherlands reports fewer concerns about regulatory compliance and perceives it as less of a barrier to adoption than the Nordics (figure 4b), they identify significant challenges in risk management – half of respondents cite this as a barrier (figure 4c). This suggests a focused approach to managing risks without letting regulatory requirements impede progress.

Dutch respondents also highlight the positive impact of GenAI on software quality, data standards, and model accuracy to a much greater extent than the Nordics. In relation to this, the Netherlands have more concerns about the misuse of client or customer data and availability of enough high-quality data. Together, these observations suggest a more mature integration of AI technologies as well as a more mature understanding of AI requirements, including risk management and compliance focus areas.

For the Nordics, the Dutch experience emphasizes the importance of building trust, investing in R&D, and developing robust risk management frameworks to unlock GenAI’s full potential.

For more insights into GenAI adoption and trust in the Netherlands visit Trust in Generative AI: A European and Dutch Perspective.

Figure 4: Nordics vs. the Netherlands

State of Generative in the Enterprise Q4 survey, N (Nordic) = 170, N (Netherlands) = 50.

Conclusion

When comparing the Nordics to global peers, it is evident that global advancements in GenAI are often driven by differing barriers, regulations, and cultural values. Our analysis highlights that even when compared to neighboring European countries with similar barriers and regulatory environments, the Nordics remain more cautious in GenAI adoption and implementation. This contrasts sharply with the more enthusiastic and rapid uptake seen in neighboring countries.

This caution suggests that the Nordics are lagging behind even where barriers are comparable. Such hesitancy could negatively impact Nordic competitiveness in key export markets, given the potential of GenAI to create competitive advantages. As a result, this may hinder the Nordics’ ability to keep pace with advancements and innovations in GenAI. From a Nordic perspective, this is a significant concern and highlights the urgent need for strategic changes to enhance the adoption and implementation of GenAI.

Recommendations for Nordic organizations

• Cultivate executive support: Educate top management on GenAI's strategic importance and transformational potential.
• Focus on strategy: Shift focus from merely understanding the technology to identifying strategic use cases that align with business objectives. This involves integrating GenAI into broader organizational strategies.
• Implement AI governance and risk management frameworks: Establish robust governance and risk management frameworks that support scaling of responsible and trustworthy AI implementations.
• Encourage an experimentation culture: Adopt a value-driven fail-fast approach to accelerate GenAI adoption while closely monitoring value realization. AI fluency is a critical enabler for this to be possible.
  

Endnotes

1. Scaling Generative AI: 13 elements for sustainable growth and value