Milijarda podatkov v podatkovni bazi SiStat

Number of enterprises with 10 or more employees and self-employed by purpose of usage of artificial intelligence technologies, cohesion regions, Slovenia, multiannually
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Contact and information

Information

Latest update
10/5/2023
Contact
Statistical Office of the Republic of Slovenia, T: +386 1 241 64 04, E: gp.surs@gov.si
Unit
number
Source
Statistical Office of the Republic of Slovenia
Footnotes

Footnotes

Linked content:
- Methodological explanations
COHESION REGION
Data are territorially classsified according to The Classification of Territorial Units for Statistics – NUTS, (description and explanations), level NUTS 2.Data on changes of individual cohesion regions are available at the link.
PURPOSE OF USAGE OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES
1.1 For marketing or sales
To provide customer support, to profile customers, to dynamically adjust prices, for providing tailor-made offers, for market analysis based on machine learning, use of a chatbot operating on the basis of natural language processing, for forecast customer response to the offers, to predict customer purchases.
1.2 For production processes
E.g. tools that classify products or find deficiencies in products based on computer vision, predictive maintenance based on machine learning, planning production, inventory optimization or business process based on machine learning, use of video analytics, autonomous drones to control production, to ensure safety or performing inspection, autonomous robots to perform assembly, assembly work.
1.3 For organisation of business administration processes
E.g. use of a business virtual assistant based on machine learning and/or on generating natural language, solutions that capture speech and sound and convert them into text and prepare a draft document, automated planning or planning based on machine learning, machine translation.
1.4 For management of enterprises
For data analysis and assistance in making investment decisions or in making other decisions, for sales or business forecasts or risk assessment based on machine learning, the use of predictive analytics to predict business events / sales / impact of marketing campaigns / customer response.
1.5 For human resource management or recruiting
E.g. pre-selection of candidates applying for the vacancy on the basis of the text mining, employee profiling (e.g. to provide individualized education) or to analyse their performance based on machine learning, the use of a conversational robot (chatbot) operating on the basis of machine learning in employment or as assistance in human resource management.
1.6 For organisation of business administration processes or management
E.g. use of a business virtual assistant based on machine learning and/or on generating natural language, solutions that capture speech and sound and convert them into text and prepare a draft document, automated planning or planning based on machine learning, machine translation, data analysis and assistance in making investment decisions or in making other decisions, for sales or business forecasts or risk assessment based on machine learning, the use of predictive analytics to predict business events / sales / impact of marketing campaigns / customer response, employee profiling (e.g. to offer personalized training) or analysis of their performance based on machine learning, employee profiling (e.g. to offer personalized training) or analysis of their performance based on machine learning.
1.7 For logistics
E.g. path optimization based on machine learning, stock forecasting, use of autonomous robots in warehouses for pick-and-pack tasks, use autonomous robots for sorting, sending, distributing packages, using autonomous drones for package delivery.
1.8 For ICT security
E.g. use of biometric methods for user authentication based on computer vision (e.g. to unlock a mobile phone based on a fingerprint, face), use of machine learning to detect and prevent cyber-attacks, use of spam filters in e-mail.
1.9 For accounting, controlling or finance management
E.g. use of machine learning to analyse data that helps to make financial decisions, invoice processing based on machine learning, use of machine learning or natural language processing for bookkeeping documents.
1.10 For research and development (R&D) or innovation activity
E.g. use of machine learning for analysis of data for conducting research, solving research problems, developing a new or significantly improved product/service.