| Product Code: ETC12599659 | Publication Date: Apr 2025 | Updated Date: Nov 2025 | Product Type: Market Research Report | |
| Publisher: 6Wresearch | Author: Sachin Kumar Rai | No. of Pages: 65 | No. of Figures: 34 | No. of Tables: 19 |
Sweden`s machine learning chip import market saw a significant shift in supplier concentration from 2023 to 2024, with a notable increase in the Herfindahl-Hirschman Index (HHI). Top exporting countries like Germany, Czechia, and Malaysia maintained strong positions, while the USA and Denmark also made significant contributions. The compound annual growth rate (CAGR) from 2020 to 2024 was an impressive 17.6%, with a notable growth spurt of 9.75% from 2023 to 2024. This data indicates a dynamic and expanding market for machine learning chips in Sweden, driven by diverse international suppliers.
1 Executive Summary |
2 Introduction |
2.1 Key Highlights of the Report |
2.2 Report Description |
2.3 Market Scope & Segmentation |
2.4 Research Methodology |
2.5 Assumptions |
3 Sweden Machine Learning Chip Market Overview |
3.1 Sweden Country Macro Economic Indicators |
3.2 Sweden Machine Learning Chip Market Revenues & Volume, 2021 & 2031F |
3.3 Sweden Machine Learning Chip Market - Industry Life Cycle |
3.4 Sweden Machine Learning Chip Market - Porter's Five Forces |
3.5 Sweden Machine Learning Chip Market Revenues & Volume Share, By Chip Type, 2021 & 2031F |
3.6 Sweden Machine Learning Chip Market Revenues & Volume Share, By Technology, 2021 & 2031F |
3.7 Sweden Machine Learning Chip Market Revenues & Volume Share, By Application, 2021 & 2031F |
3.8 Sweden Machine Learning Chip Market Revenues & Volume Share, By End User, 2021 & 2031F |
4 Sweden Machine Learning Chip Market Dynamics |
4.1 Impact Analysis |
4.2 Market Drivers |
4.2.1 Growing demand for machine learning applications across various industries in Sweden |
4.2.2 Increasing investments in artificial intelligence and machine learning technologies by Swedish companies |
4.2.3 Government initiatives and support for the development and adoption of machine learning technologies in Sweden |
4.3 Market Restraints |
4.3.1 High initial investment required for developing and implementing machine learning chip technologies |
4.3.2 Lack of skilled professionals in the field of machine learning and artificial intelligence in Sweden |
4.3.3 Data privacy and security concerns impacting the adoption of machine learning technologies in Sweden |
5 Sweden Machine Learning Chip Market Trends |
6 Sweden Machine Learning Chip Market, By Types |
6.1 Sweden Machine Learning Chip Market, By Chip Type |
6.1.1 Overview and Analysis |
6.1.2 Sweden Machine Learning Chip Market Revenues & Volume, By Chip Type, 2021 - 2031F |
6.1.3 Sweden Machine Learning Chip Market Revenues & Volume, By GPU, 2021 - 2031F |
6.1.4 Sweden Machine Learning Chip Market Revenues & Volume, By ASIC, 2021 - 2031F |
6.1.5 Sweden Machine Learning Chip Market Revenues & Volume, By FPGA, 2021 - 2031F |
6.1.6 Sweden Machine Learning Chip Market Revenues & Volume, By CPU, 2021 - 2031F |
6.2 Sweden Machine Learning Chip Market, By Technology |
6.2.1 Overview and Analysis |
6.2.2 Sweden Machine Learning Chip Market Revenues & Volume, By Edge AI, 2021 - 2031F |
6.2.3 Sweden Machine Learning Chip Market Revenues & Volume, By Cloud AI, 2021 - 2031F |
6.2.4 Sweden Machine Learning Chip Market Revenues & Volume, By Embedded AI, 2021 - 2031F |
6.3 Sweden Machine Learning Chip Market, By Application |
6.3.1 Overview and Analysis |
6.3.2 Sweden Machine Learning Chip Market Revenues & Volume, By Image Processing, 2021 - 2031F |
6.3.3 Sweden Machine Learning Chip Market Revenues & Volume, By Autonomous Driving, 2021 - 2031F |
6.3.4 Sweden Machine Learning Chip Market Revenues & Volume, By Robotics, 2021 - 2031F |
6.3.5 Sweden Machine Learning Chip Market Revenues & Volume, By Smart Assistants, 2021 - 2031F |
6.4 Sweden Machine Learning Chip Market, By End User |
6.4.1 Overview and Analysis |
6.4.2 Sweden Machine Learning Chip Market Revenues & Volume, By IT & Telecom, 2021 - 2031F |
6.4.3 Sweden Machine Learning Chip Market Revenues & Volume, By Automotive, 2021 - 2031F |
6.4.4 Sweden Machine Learning Chip Market Revenues & Volume, By Industrial, 2021 - 2031F |
6.4.5 Sweden Machine Learning Chip Market Revenues & Volume, By Consumer Electronics, 2021 - 2031F |
7 Sweden Machine Learning Chip Market Import-Export Trade Statistics |
7.1 Sweden Machine Learning Chip Market Export to Major Countries |
7.2 Sweden Machine Learning Chip Market Imports from Major Countries |
8 Sweden Machine Learning Chip Market Key Performance Indicators |
8.1 Adoption rate of machine learning chips in key industries in Sweden |
8.2 Rate of investment in machine learning chip research and development by Swedish companies |
8.3 Number of patents filed for machine learning chip technologies in Sweden |
9 Sweden Machine Learning Chip Market - Opportunity Assessment |
9.1 Sweden Machine Learning Chip Market Opportunity Assessment, By Chip Type, 2021 & 2031F |
9.2 Sweden Machine Learning Chip Market Opportunity Assessment, By Technology, 2021 & 2031F |
9.3 Sweden Machine Learning Chip Market Opportunity Assessment, By Application, 2021 & 2031F |
9.4 Sweden Machine Learning Chip Market Opportunity Assessment, By End User, 2021 & 2031F |
10 Sweden Machine Learning Chip Market - Competitive Landscape |
10.1 Sweden Machine Learning Chip Market Revenue Share, By Companies, 2024 |
10.2 Sweden Machine Learning Chip Market Competitive Benchmarking, By Operating and Technical Parameters |
11 Company Profiles |
12 Recommendations |
13 Disclaimer |
Export potential enables firms to identify high-growth global markets with greater confidence by combining advanced trade intelligence with a structured quantitative methodology. The framework analyzes emerging demand trends and country-level import patterns while integrating macroeconomic and trade datasets such as GDP and population forecasts, bilateral import–export flows, tariff structures, elasticity differentials between developed and developing economies, geographic distance, and import demand projections. Using weighted trade values from 2020–2024 as the base period to project country-to-country export potential for 2030, these inputs are operationalized through calculated drivers such as gravity model parameters, tariff impact factors, and projected GDP per-capita growth. Through an analysis of hidden potentials, demand hotspots, and market conditions that are most favorable to success, this method enables firms to focus on target countries, maximize returns, and global expansion with data, backed by accuracy.
By factoring in the projected importer demand gap that is currently unmet and could be potential opportunity, it identifies the potential for the Exporter (Country) among 190 countries, against the general trade analysis, which identifies the biggest importer or exporter.
To discover high-growth global markets and optimize your business strategy:
Click Here