Across the full population, 15% use AI tools daily. In comparison, 35% use AI at least weekly, and 10% say they have tried AI but do not use it regularly. This shows broad adoption, but daily habit formation is still uneven.
How should we read this pattern?
This result adds detail to our previous story, where we saw that 61% of people in Estonia had already tried AI tools. The next question is how many have moved from first-time use to regular use.
Put together, the two measurements form a clear funnel: many people have tried AI, but a smaller share uses it daily. So the key divide is no longer between users and non-users, but between occasional and regular use.
The sizeable group that has tried AI but does not use it regularly suggests that the next stage is practical: helping people use AI for specific tasks, safely and consistently.
AI usage funnel (% of full population)
Chart type: chart | Label | Share (%) | | --- | --- | | Has tried AI at least once | 61 | | Uses AI at least monthly | 46 | | Uses AI at least weekly | 35 | | Uses AI daily | 15 |
Where do the biggest differences appear?
The broad pattern is clear: one group already uses AI regularly, while another has tried it but has not integrated it into routine use. The strongest contrast in this dataset appears by age.
Does usage rhythm differ by age?
Yes, clearly. The gap is not only about whether people have ever tried AI, but about how often AI actually becomes part of daily routines.
In the 25-34 age group, daily use is 30%, while in the 75+ group it is 1%. This suggests that what drops with age is mostly regularity of use.
At the same time, the share of people who have tried AI but do not use it regularly is higher in older groups. In practical terms, the key challenge is not first exposure, but turning trial into confident routine use.
Internationally, the same direction appears in Pew Research Center’s global study, where younger groups report more frequent contact with AI than older groups.
Daily use vs non-regular use by age (%)
Chart type: chart | Label | Uses AI daily | Tried, but does not use regularly | | --- | --- | --- | | 15-24 | 20 | 2 | | 25-34 | 30 | 6 | | 35-49 | 23 | 11 | | 50-64 | 11 | 12 | | 65-74 | 3 | 9 | | 75+ | 1 | 15 |
This is a fast-moving picture
AI usage is changing quickly. Today’s result (Opinion Estonia 2026/01) is a strong baseline, but daily usage is likely to rise further in the coming months. That is why this needs repeated measurement and trend tracking, not a one-off snapshot.
How does Estonia compare internationally?
Fully comparable country-level “daily use” data is still limited because methods differ. Still, available measurements are useful for orientation: in the UK, a Verian survey (12-15 Dec 2025) reported 21% daily AI use. In the US, a Gallup workplace study (Q4 2025) reported 12% daily AI use at work. In our Estonia 2026/01 measurement, daily use is 15% of the full population.
On broader AI reach, Eurostat’s release (16 Dec 2025) places Estonia among Europe’s leaders. That fits our local pattern: trial is already widespread, and the next growth comes from usage frequency.
What marketers should track right now
International practice suggests AI is already changing search and buying paths. Bain’s 2025 measurement indicates that AI summaries reduce clicks to traditional websites. This means marketing teams cannot rely on old traffic logic alone.
At this stage, four metrics matter most: share of the audience using AI daily, quality of search traffic, share of zero-click behavior, and whether conversions shift from owned channels into AI-mediated journeys. In short, teams should track not only visibility, but where decisions are actually formed.
Question: “Kui sageli kasutate tehisintellekti (AI) tööriistu?” In this article, shares are presented as part of the full target group: daily 15% (n=155), several times a week 20% (n=199), several times a month 11% (n=114), less than monthly 5% (n=46), tried but not regular 10% (n=100), do not know <1% (n=3). We also use the prior result that 61% have tried AI at least once. Very small subgroup results should be interpreted with caution.