Nordic industrial companies are showing an increased commitment to Artificial Intelligence (AI). While the overall adoption of AI technologies continues to increase, Nordic companies are also increasing their investments into AI development. Despite the significant acceleration in AI-related activities, there remains a large number of areas that require further progress, such as industrial large-scale adoption of AI, talent acquisition and investments into AI infrastructure.
Silo AI, Europe’s largest private AI lab, publishes today its third annual Nordic State of AI report, surveying several of the Nordic region’s largest companies in various industries, such as manufacturing and construction. The median age of the participating companies is 87 years, with many of them being over a century old. Among the respondents are companies like SKF, UPM, Höganäs and Assa Abloy.
“The Nordic State of AI report paints a picture of a region that stands out for its advanced technological abilities and openness to embrace new technologies. While Nordic companies are on the forefront of innovation, it's clear that there is still much work to be done. Fierce competition in a global technology landscape requires companies to not only embrace AI but also address key challenges in value creation. These include the challenges with large-scale integration into business processes, navigating the complexities of AI talent acquisition, and building a strong AI infrastructure”
says Peter Sarlin, Silo AI CEO and co-founder.
Large-scale integration of AI continues to be a challenge
While AI is being adopted, most companies are only taking initial steps. Almost 80% of respondents have started experimenting with ChatGPT-type products, and ¾ say they use AI as part of their product or service. However, a majority of those report intentions of investing above €0.5 million into AI in 2024, and only 20% of respondents expect to invest more than €10 million. AI development is still largely experimental and fragmented across companies. This shows a growing commitment to AI, while there is still work to be done in order to integrate AI at a larger scale.
For all companies, how and where AI is deployed influences the return on investment significantly. The best opportunities for generating good returns are in deploying AI at the core of a company’s products or services or in business-critical processes. As AI is a long-term investment, leadership is crucial for harnessing its potential to strengthen competitive advantage
Devising ambition for significant business results and maintaining that ambition with a disciplined focus on a common direction is essential for success, as with any long-term initiative.
Talent is a growing bottleneck to scaling the adoption of AI
The recruitment of AI talent is becoming increasingly critical as companies strive to scale their AI capabilities. A majority of firms have identified a pressing shortage of skilled professionals, with 51.4% citing a lack of talent as a primary challenge, up from 35.3% in the previous year. This talent gap is most acute in high-demand roles such as data scientists, data engineers, and machine learning engineers.
Demand is also increasing for a collaborative dynamic that combines technical AI skills with domain-specific expertise, ensuring a holistic approach to AI integration. Additionally, a baseline level of AI literacy among non-technical staff is essential to foster effective collaboration and maximize AI's potential within the company. More companies are investing in competence development than in recruiting new talent. In previous years, it has been the other way around.
While the hiring of new AI talent is on the rise, there's a clear acknowledgment within the industry that not all expertise needs to reside internally; external experts are increasingly seen as valuable assets to bridge these capability gaps and drive AI adoption forward.
Prioritizing investment in AI infrastructure is key
For forward-thinking companies, prioritizing investment in AI infrastructure is key, ensuring strategic readiness to harness AI's full potential. On a strategic level, it starts from realizing that AI infrastructure is more than just data and compute.
This endeavor will require buy-in from executives on various levels. Businesses will have to invest significantly not only in computational resources but also in data quality and management and the development and deployment of AI models, making the development process more reliable and productive. From a European perspective, infrastructure also includes foundation models, especially large language models, that are tailored to European languages, values, and culture, ensuring they are aligned with regional use cases and can be augmented and fine-tuned effectively.
“AI infrastructure is essential for scaling AI, facilitating knowledge sharing among stakeholders, and ensuring operational readiness. It underpins the creation of AI-enhanced products and services that resonate with European needs, embodying a strategic approach that goes beyond computing power to encompass the cultural and linguistic nuances vital for AI's success in the region.”
says Silo AI CEO and co-founder Peter Sarlin.
Europe lags behind in the software-centric technology sector
In 2021 three Nordic countries, Finland, Sweden and Denmark, ranked in the top 10 of Oxford Insights’ Government AI Readiness Index. In 2023 only Finland remains in the top 10. Europe and the Nordics are lagging behind in one out of the three pillars of the index, the Technology sector.
It is important to champion the development of AI technologies that reflect local values, languages and cultures, and that are compliant with local regulations such as the GDPR and the EU AI Act. This will enable Europe to actively shape its trajectory and foster technological progress that aligns with European strengths and market needs.
To succeed, Europe needs to face both sides of a dual imperative: firstly, the cultivation of more software companies is crucial to ensure the potential of AI is harnessed. These firms are pivotal for scaling AI technologies and filling a critical gap in Europe's tech sector. Secondly, there is an urgent need for traditional companies to evolve towards becoming more software-centric. This allows traditional businesses to integrate AI more effectively, creating significant value and maintaining competitiveness.
For more insights, we welcome you to download the full Nordic State of AI report.
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