Gen AI adoption in the Nordics: Balancing ambition with caution

Visit our Generative AI webpage

\r\nNordic businesses are keeping pace with global generative AI investment trends, with average projected spending reaching $49.7 million per company this year, according to our recent research, slightly above the global average of $47 million.

\r\n

These investments are taking place amid a sense of urgency to realize the potential of this powerful technology, with 65% of businesses expressing a desire to accelerate their generative AI strategies. At the same time, about two-thirds (62%) of Nordic businesses express at least moderate worry about the existential impact of generative AI on their operations.

\r\n

This measured perspective is perhaps characteristic of a region known for its thoughtful approach to pursuing technological advancement within the context of its potential societal and ethical implications, as seen in its early investment into sustainability.

\r\n

To better understand what generative AI adoption will look like globally, we conducted a study of 2,200 business leaders in 23 countries and 15 industries, including 110 in the Nordics. The study assessed a wide range of generative AI adoption trends, including investment levels, use cases, how critical gen AI strategies are to business success, and organizational readiness to adopt the technology.

\r\n

We also analyzed 18 regional and internal business factors that will either inhibit or accelerate business adoption of gen AI (see the end of the report for the full list of factors). Respondents evaluated each factor's potential impact on their generative AI strategy, rating it as either positive or negative on a scale of high to low impact.

\r\n

From the results, we calculated a "momentum score" for each country or region. The momentum score represents the level of confidence business leaders have about being able to roll out their generative AI strategy based on internal business factors and the prevailing local conditions of their country or region.

\r\n

For all the regions covered, inhibitors to adoption outranked accelerators, meaning that all momentum scores skewed negative. In effect, businesses globally feel constrained by their operating environment.

\r\n

But to understand how different regions varied relative to each other, we averaged the ratings to establish a baseline global momentum score. This approach enabled us to identify regions that are more optimistic about their ability to adopt the technology compared with a global average.

\r\n

While there is clear investment in generative AI across the Nordic region, the overall momentum score of -14% indicates a more cautious approach compared with the global average. Several factors contribute to this measured pace, notably concerns surrounding consumer perceptions, the adaptability of existing business models, and the cost and availability of skilled talent. Additionally, challenges related to current technology infrastructure and the perceived maturity of generative AI technologies are contributing factors.

\r\n

However, Nordic businesses display a more optimistic outlook in key areas. They express greater confidence in their operating models' flexibility, market demand, the quality of generative AI outputs, data readiness and the availability of compute power. This suggests that companies will be able to leverage internal strengths to address specific challenges and accelerate their adoption of generative AI.

\r\n

Nordics gen AI scorecard

\r\n"}}" id="text-6d135cb50b" class="cmp-text">

Nordic businesses are keeping pace with global generative AI investment trends, with average projected spending reaching $49.7 million per company this year, according to our recent research, slightly above the global average of $47 million.

These investments are taking place amid a sense of urgency to realize the potential of this powerful technology, with 65% of businesses expressing a desire to accelerate their generative AI strategies. At the same time, about two-thirds (62%) of Nordic businesses express at least moderate worry about the existential impact of generative AI on their operations.

This measured perspective is perhaps characteristic of a region known for its thoughtful approach to pursuing technological advancement within the context of its potential societal and ethical implications, as seen in its early investment into sustainability.

To better understand what generative AI adoption will look like globally, we conducted a study of 2,200 business leaders in 23 countries and 15 industries, including 110 in the Nordics. The study assessed a wide range of generative AI adoption trends, including investment levels, use cases, how critical gen AI strategies are to business success, and organizational readiness to adopt the technology.

We also analyzed 18 regional and internal business factors that will either inhibit or accelerate business adoption of gen AI (see the end of the report for the full list of factors). Respondents evaluated each factor's potential impact on their generative AI strategy, rating it as either positive or negative on a scale of high to low impact.

From the results, we calculated a "momentum score" for each country or region. The momentum score represents the level of confidence business leaders have about being able to roll out their generative AI strategy based on internal business factors and the prevailing local conditions of their country or region.

For all the regions covered, inhibitors to adoption outranked accelerators, meaning that all momentum scores skewed negative. In effect, businesses globally feel constrained by their operating environment.

But to understand how different regions varied relative to each other, we averaged the ratings to establish a baseline global momentum score. This approach enabled us to identify regions that are more optimistic about their ability to adopt the technology compared with a global average.

While there is clear investment in generative AI across the Nordic region, the overall momentum score of -14% indicates a more cautious approach compared with the global average. Several factors contribute to this measured pace, notably concerns surrounding consumer perceptions, the adaptability of existing business models, and the cost and availability of skilled talent. Additionally, challenges related to current technology infrastructure and the perceived maturity of generative AI technologies are contributing factors.

However, Nordic businesses display a more optimistic outlook in key areas. They express greater confidence in their operating models' flexibility, market demand, the quality of generative AI outputs, data readiness and the availability of compute power. This suggests that companies will be able to leverage internal strengths to address specific challenges and accelerate their adoption of generative AI.

Nordics gen AI scorecard

Base: 110 senior business leaders in the Nordics
\r\nSource: Cognizant and Oxford Economics
\r\nFigure 1

\r\n

As for where businesses' generative AI investments will be aimed in the near term, we looked at two distinct uses of the technology: productivity, such as helping people work more quickly and get more done, and disruptive innovation, which involves more sweeping change to business and operating models. Overall, businesses in the Nordics mirror the global trend: Over the next two years, more respondents expect to use generative AI to boost productivity than drive disruptive change (see Figure 2).

\r\n

However, our study also reveals a change in what productivity means when pursued with generative AI. The end goal is not efficiency and cost-cutting as has been the case with previous automation endeavors. This new dynamic requires fresh thinking around understanding business use cases of generative AI, which we'll address later in this report.

\r\n

Notably, Nordic businesses are more likely than their global peers to embed generative AI into their products and services in the next two years (31% vs. the global average of 26%). This suggests a pervasive belief that generative AI will become an integral part of the Nordic business landscape and citizens' digital lives.

\r\n

Greater focus on productivity than innovation

\r\n

Q: Which of the following best describes the role generative AI will play in your organization's business strategy in the next two years? (Percent of respondents naming each as a top-3 choice)

\r\n"}}" id="text-80d25d4267" class="cmp-text">

Base: 110 senior business leaders in the Nordics
Source: Cognizant and Oxford Economics
Figure 1

As for where businesses' generative AI investments will be aimed in the near term, we looked at two distinct uses of the technology: productivity, such as helping people work more quickly and get more done, and disruptive innovation, which involves more sweeping change to business and operating models. Overall, businesses in the Nordics mirror the global trend: Over the next two years, more respondents expect to use generative AI to boost productivity than drive disruptive change (see Figure 2).

However, our study also reveals a change in what productivity means when pursued with generative AI. The end goal is not efficiency and cost-cutting as has been the case with previous automation endeavors. This new dynamic requires fresh thinking around understanding business use cases of generative AI, which we'll address later in this report.

Notably, Nordic businesses are more likely than their global peers to embed generative AI into their products and services in the next two years (31% vs. the global average of 26%). This suggests a pervasive belief that generative AI will become an integral part of the Nordic business landscape and citizens' digital lives.

Greater focus on productivity than innovation

Q: Which of the following best describes the role generative AI will play in your organization's business strategy in the next two years? (Percent of respondents naming each as a top-3 choice)

\r\nInhibitors and accelerators: The forces driving AI momentum

\r\n

To dig deeper into these mechanics, rather than comparing to a global average, we'll now examine how business leaders rate inhibitors and accelerators within their region. By doing so, our study provides a detailed temperature check on what respondents view as the main inhibitors and accelerators to generative AI in their region.

\r\n

With this assessment, leaders can take advantage of what's working well in their local environment, while strategizing on overcoming challenges.

\r\n

A look at Nordic gen AI accelerators

\r\n"}}" id="text-935ef5c97a" class="cmp-text">

Inhibitors and accelerators: The forces driving AI momentum

To dig deeper into these mechanics, rather than comparing to a global average, we'll now examine how business leaders rate inhibitors and accelerators within their region. By doing so, our study provides a detailed temperature check on what respondents view as the main inhibitors and accelerators to generative AI in their region.

With this assessment, leaders can take advantage of what's working well in their local environment, while strategizing on overcoming challenges.

A look at Nordic gen AI accelerators

Respondents were asked which factors inhibit or accelerate their organization's adoption of generative AI. Score represents a percentage point difference to the country's momentum score compared to the global baseline.
\r\n
\r\nBase: 110 senior business leaders in the Nordics
\r\nSource: Cognizant and Oxford Economics
\r\nFigure 3

\r\n

The flexibility of operating models in Nordic companies serves as a strong foundation for generative AI adoption. Companies like Danish shipping and logistics giant Maersk, for example, have successfully integrated AI into their operations to track shipments, anticipate disruptions and proactively identify alternatives.

\r\n

Complementing this adaptability is a growing market demand for generative AI. AI tool usage is widespread in the Nordic region, with nearly half the population using these tools to some extent in 2024. This underscores the need to invest in and enhance the region's infrastructure to match changing behaviors and enhance safe and effective use.

\r\n

Data readiness further bolsters the region's prospects. In many ways, the Nordic region is leading the charge on data issues, especially as it relates to privacy. For example, Finland's "MyData" initiative, which enables people to own and control the use of their personal data, exemplifies the Nordics' commitment to data management, privacy and security, and provides a strong foundation for safer development and deployment of generative AI applications.

\r\n

At the same time, a significant portion (48%) of businesses believe their data security practices are not robust enough to support generative AI initiatives. This highlights the need for investment in modernizing infrastructure and strengthening security measures to ensure the responsible and safe deployment of AI technologies.

\r\n

Finally, the availability of compute power also plays a significant role. The presence of major data centers from global cloud providers and initiatives like the LUMI petascale supercomputer in Finland ensures that Nordic businesses have access to the computational resources necessary for generative AI development.

\r\n

Understanding Nordic gen AI inhibitors

\r\n"}}" id="text-49434c1e6d" class="cmp-text">

Respondents were asked which factors inhibit or accelerate their organization's adoption of generative AI. Score represents a percentage point difference to the country's momentum score compared to the global baseline.

Base: 110 senior business leaders in the Nordics
Source: Cognizant and Oxford Economics
Figure 3

The flexibility of operating models in Nordic companies serves as a strong foundation for generative AI adoption. Companies like Danish shipping and logistics giant Maersk, for example, have successfully integrated AI into their operations to track shipments, anticipate disruptions and proactively identify alternatives.

Complementing this adaptability is a growing market demand for generative AI. AI tool usage is widespread in the Nordic region, with nearly half the population using these tools to some extent in 2024. This underscores the need to invest in and enhance the region's infrastructure to match changing behaviors and enhance safe and effective use.

Data readiness further bolsters the region's prospects. In many ways, the Nordic region is leading the charge on data issues, especially as it relates to privacy. For example, Finland's "MyData" initiative, which enables people to own and control the use of their personal data, exemplifies the Nordics' commitment to data management, privacy and security, and provides a strong foundation for safer development and deployment of generative AI applications.

At the same time, a significant portion (48%) of businesses believe their data security practices are not robust enough to support generative AI initiatives. This highlights the need for investment in modernizing infrastructure and strengthening security measures to ensure the responsible and safe deployment of AI technologies.

Finally, the availability of compute power also plays a significant role. The presence of major data centers from global cloud providers and initiatives like the LUMI petascale supercomputer in Finland ensures that Nordic businesses have access to the computational resources necessary for generative AI development.

Understanding Nordic gen AI inhibitors

\r\nSector spotlight: Stark differences in industries' gen AI adoption priorities

\r\n

Of course, there are many use cases and strategies for using generative AI. As we've said, Nordic businesses are primarily focused on realizing productivity gains with generative AI, at least in the next two years. However, a look at what's driving their business cases sheds a new light on productivity from how it's been seen historically.

\r\n

Traditionally, businesses have equated automation productivity gains with cost-cutting: driving down the cost of output by reducing the number of people needed to get work done.

\r\n

While generative AI-driven automation will likely lower headcount to some degree, that is no longer the end goal. Instead, as seen through the metrics respondents will use to drive business cases, we see a shift toward redirecting productivity gains into funding endeavors that increase revenues or lead to entirely new revenue streams.

\r\n

The metrics Nordic businesses say will be most important for justifying generative AI expenditures include increasing revenues, discovering new revenue sources and improved product and service quality, all of which were named by at least 44% of respondents (see Figure 5). Conversely, metrics like cost savings, time-to-market and productivity were cited by less than 30% of respondents. In other words, the concept of productivity no longer stops at cost-cutting-businesses appear to be redirecting productivity gains into initiatives aimed at growth.

\r\n

This emphasis on growth-oriented metrics also reflects the unique socioeconomic landscape of the Nordics, which discourages workforce reductions. Further, strong labor unions can make such measures costly, particularly for larger enterprises. Consequently, these businesses tend to favor strategies that empower them to achieve "more with the same" rather than pursuing the traditional "same with less" approach.

\r\n

Revenue is a top metric for justifying gen AI use cases

\r\n

Q: Which of the following metrics are most important in terms of justifying your organization's generative AI business cases? (Percent of respondents naming each as a top-three choice)

\r\n"}}" id="text-ddcf983a3c" class="cmp-text">

Sector spotlight: Stark differences in industries' gen AI adoption priorities

Of course, there are many use cases and strategies for using generative AI. As we've said, Nordic businesses are primarily focused on realizing productivity gains with generative AI, at least in the next two years. However, a look at what's driving their business cases sheds a new light on productivity from how it's been seen historically.

Traditionally, businesses have equated automation productivity gains with cost-cutting: driving down the cost of output by reducing the number of people needed to get work done.

While generative AI-driven automation will likely lower headcount to some degree, that is no longer the end goal. Instead, as seen through the metrics respondents will use to drive business cases, we see a shift toward redirecting productivity gains into funding endeavors that increase revenues or lead to entirely new revenue streams.

The metrics Nordic businesses say will be most important for justifying generative AI expenditures include increasing revenues, discovering new revenue sources and improved product and service quality, all of which were named by at least 44% of respondents (see Figure 5). Conversely, metrics like cost savings, time-to-market and productivity were cited by less than 30% of respondents. In other words, the concept of productivity no longer stops at cost-cutting-businesses appear to be redirecting productivity gains into initiatives aimed at growth.

This emphasis on growth-oriented metrics also reflects the unique socioeconomic landscape of the Nordics, which discourages workforce reductions. Further, strong labor unions can make such measures costly, particularly for larger enterprises. Consequently, these businesses tend to favor strategies that empower them to achieve "more with the same" rather than pursuing the traditional "same with less" approach.

Revenue is a top metric for justifying gen AI use cases

Q: Which of the following metrics are most important in terms of justifying your organization's generative AI business cases? (Percent of respondents naming each as a top-three choice)

Base: 110 senior business leaders in the Nordics
\r\nSource: Cognizant and Oxford Economics
\r\nFigure 5

\r\n

Using this more granular view of productivity goals and business drivers, we analyzed the differences in how industries intend to use the technology.

\r\n

Rather than focusing on the distinction between productivity vs. innovation, we grouped the metrics into two high-level categories of business use cases:

\r\n

• \r\n
• Enhancing current business performance (revenue, cost savings, time-to-market, productivity)
• \r\n
• Building something new (new revenue sources, new or improved products, innovation)
• \r\n

\r\n

We then assigned each of the metrics a score to see the relative gap between a number-one-ranking metric and a number-three-ranking metric. By calculating the average score across industries, we could clearly see how each industry's responses deviated from the baseline.

\r\n

Our analysis reveals stark differences among Nordic industries in terms of the business use cases they'll likely prioritize (see Figure 6).

\r\n

Industries diverge on business cases

\r\n"}}" id="text-91b6cfb488" class="cmp-text">

Base: 110 senior business leaders in the Nordics
Source: Cognizant and Oxford Economics
Figure 5

Using this more granular view of productivity goals and business drivers, we analyzed the differences in how industries intend to use the technology.

Rather than focusing on the distinction between productivity vs. innovation, we grouped the metrics into two high-level categories of business use cases:

• Enhancing current business performance (revenue, cost savings, time-to-market, productivity)
• Building something new (new revenue sources, new or improved products, innovation)

We then assigned each of the metrics a score to see the relative gap between a number-one-ranking metric and a number-three-ranking metric. By calculating the average score across industries, we could clearly see how each industry's responses deviated from the baseline.

Our analysis reveals stark differences among Nordic industries in terms of the business use cases they'll likely prioritize (see Figure 6).

Industries diverge on business cases