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Nordic AI survey 2026
Mind the gap: the mismatch between AI adoption and impact
Our survey explores how AI is being adopted across Finland, Sweden and Norway – and where the gaps remain. Discover how the use of AI has progressed compared to last year.
From experimentation to everyday use
AI adoption in the Nordics has taken a significant leap forward over the past year. Organizations have shifted from experimentation to broad operational use. AI has become part of everyday business, with employees actively using AI in their daily work.
AI adoption is accelerating
Compared to 2025, organization-wide AI use in production has increased from 7% to 31%. Despite this growth, only 4% of organizations say that AI is a critical part of their core infrastructure and business operations, suggesting that AI is still often applied in a limited or fragmented way.
At the employee level, AI has already become part of everyday work. Almost one third of employees (30%) use AI solutions to a large extent, while minimal use has declined from 17% to 10%. Notably, no respondents now report zero AI use.
Usage remains concentrated in specific functions. The highest levels of AI adoption are seen in IT operations (46%), customer service (35%) and software development (35%), largely unchanged from last year.
Key drivers for AI adoption
Efficiency
65%
Modernizing operations or digital transformation
35%
Cost optimization
32%
From adoption to impact
To unlock the full potential of AI, organizations need a clear strategic direction and cultural change. Those that succeed in aligning business goals with skills development can turn AI into a concrete competitive advantage.
Impact remains efficiency-led
Efficiency remains the main driver of AI adoption. Nearly two thirds of organizations (65%) cite efficiency as their primary motivation, followed by modernizing operations (35%), reducing costs (32%) and improving customer experience (27%). More strategic ambitions, such as innovation, resilience and long-term transformation, still play a secondary role.
There are, however, early signs of change. Interest in using AI for innovation and product development has increased since 2025, rising from 18% to 24%.
The next challenge is scaling AI from efficiency gains to measurable business impact. Today, impact is primarily assessed through short-term operational KPIs such as productivity (33%) and cost savings (31%). At the same time, 24% of organizations still lack formal KPIs for AI, making it harder to track value and steer investments.
Decision-making authority for AI initiatives sits mainly with IT or technology leadership (50%) and executive management (49%), while only 24% report ownership within business management. Only 21% have a central AI or data team.
The results suggest that closer alignment between AI initiatives and business needs, supported by clear ownership and collaboration across functions, will be essential to turn widespread AI use into sustained, business-driven impact.
Embedding responsibility into AI adoption
AI implementation needs to be accompanied by robust, responsible governance to mitigate risks and ensure ethical use. Organizations must also take a deliberate and forward-looking approach to AI, not only in how they operate today, but to support sustainable development over time.
Use of AI agents
AI agents are gaining traction, particularly in customer service (39%) and IT operations (38%). At the same time, confidence in their maturity remains mixed.
Concerns are most pronounced around risk and reliability. More than half of respondents (57%) are concerned about how autonomous agents handle data securely, and a majority (60%) express concern about the quality and reliability of their outputs.
Despite these concerns, experimentation continues. Alongside widespread use of tools such as Microsoft Copilot and ChatGPT, nearly one third of organizations (29%) report building or testing custom AI agents. This points to growing interest in tailored, organization-specific solutions.
Security is the biggest barrier
Security concerns (45%) remain the biggest barrier to AI adoption across all countries.
Skills and competence gaps are the second major obstacle. Almost four in ten organizations (39%) say skills gap is slowing AI adoption, highlighting the need for training and upskilling.
Many organizations also struggle with data quality (24%), regulatory uncertainty (22%) and model quality issues (21%).
Overall, the results point to the need for stronger security and governance practices, combined with ongoing skills development and clearer internal ownership, to enable more confident and responsible AI adoption.
Main barriers for AI adoption
Cybersecurity concerns
45%
Skills and competence gaps
39%
Data quality or data access
24%
From pilots to production
Everyone talks about AI, but only half are using it to any significant extent. The market is still stuck in the pilot trap. Scaling is held back by the organization, not the technology. The real value lies in safely integrating AI into core operations – with clear ownership, governance and objectives.
Responsible use of AI
A clear majority (78%) report having responsible AI policies in place or currently under development. However, only around one third (35%) have fully established policies and guidelines, indicating that governance maturity is still lagging behind the rapid pace of AI adoption.
While security, data privacy and the reliability of AI outputs continue to raise high levels of concern, ethical and environmental aspects are generally seen as less immediate risks. 26% say they are not concerned at all about AI’s environmental impact, and 16% report no concern about ethical issues.
Regulatory readiness remains a clear gap. Only a small minority of organizations (3%) feel fully prepared for the upcoming EU AI Act, while most are still at early or mid-level stages of preparedness.
About the survey
Tieto's Nordic AI survey 2026
In early 2026, we surveyed IT decision‑makers across Finland, Sweden and Norway to understand how AI is being used in Nordic organizations today and what’s holding it back.
The Nordic AI survey brings together insights from more than 600 respondents in medium‑ and large‑sized organizations across industries, all involved in AI decision‑making. Participants were recruited via an online panel by Norstat. The respondents represent more than 15 industries and come from different companies and organizational positions.
This is the second consecutive year we run the Nordic AI survey, allowing us to track how AI maturity is evolving across the region.
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