2022 Survey Report

AI adoption in Europe: How
high performers generate value

AI adoption in Europe: How high performers generate value

The state of AI in Europe 2022
There's been a severe lack of data available on the state of AI in Europe. We at StageZero decided to remedy this and contribute to the AI community by making available to everyone the data we have gathered from surveying companies in Europe.

In 2022, we asked companies throughout Europe how they generate value through developing and using AI. Here are a few of our key takeaways.
There's been a severe lack of data available on the state of AI in Europe. We at StageZero decided to remedy this and contribute to the AI community by making available to everyone the data we have gathered from surveying companies in Europe.

In 2022, we asked companies throughout Europe how they generate value through developing and using AI. Here are a few of our key takeaways.
"We have identified several correlations between
company practices and how well they perform
when adopting AI.

I was positively surprised to find that most companies seem to be realizing value out of their implementations.”
"We have identified several correlations between
company practices and how well they perform
when adopting AI.

I was positively surprised to find that most companies seem to be realizing value out of their implementations.”
Dr. Thomas Forss, CEO
StageZero Technologies

Key takeaway - 92% say access to data is an issue

“Managers and technologists recognize a lack of data as the most
significant barrier to providing value through machine learning.”
“Managers and technologists recognize a lack of data as the most significant barrier to providing value through machine learning.”
Companies already developing their own AI or ML solutions ranked access to training data and high quality data as the most significat issues.

Key takeaway - Partnering boosts success

56% vs 19%
“High performers are more willing to turn to external data
providers for help and solve problems with training data.”
“High performers are more willing to turn to external data providers for help.”
56% of high performers generate value from partnering with external data
providers, while only 19% of the others do.
56% of high performers generate value from partnering with external data providers, while only 19% of the others do.
“I was surprised to see that the overwhelming
majority of companies considers regulatory
compliance an issue in AI adoption.”
“I was surprised to see that the overwhelming majority of companies considers regulatory compliance an issue in AI adoption.”
Dr. Magnus Westerlund
Arcada University of Applied Sciences

Key takeaway - High performers generate value by using MLOps

“All high performers monitor their models, with 56% monitoring
some deployed models and the rest monitoring all.”
“All high performers monitor their models, with 56% monitoring some deployed models and the rest monitoring all.”
MLOps are practices for maintaining and retraining machine learning models once they are deployed and taken into use.
MLOps are practices for maintaining and retraining machine learning models once they are deployed and taken into use.

Download the full report to see the rest of the results!


Share
Page Link
https://stagezero.ai/2022-survey-report/
Copy
©2022 StageZero Technologies
linkedin facebook pinterest youtube rss twitter instagram facebook-blank rss-blank linkedin-blank pinterest youtube twitter instagram