1. Study Design
This study employed a quantitative, cross-sectional secondary-data research design to examine the relationships among artificial intelligence adoption, digital infrastructure, and business productivity across selected developed and emerging economies.
The study used a comparative country-level approach and examined selected indicators of AI adoption, technological readiness, digital infrastructure, AI investment, industry data intensity, and business productivity.
2. Countries Examined
The analysis covered five selected economies:
- United States
- United Kingdom
- China
- India
- Philippines
The countries were selected to provide comparative perspectives across different levels of technological development, digital infrastructure, economic structure, and AI readiness.
3. Data Sources
The study used secondary data obtained from internationally recognized sources, including the OECD AI Policy Observatory, Stanford AI Index, World Bank World Development Indicators, and McKinsey & Company.
The analysis used harmonized country-level indicators covering the 2018 to 2025 reference period, based on the availability and comparability of the relevant data.
The analysis used harmonized country-level indicators covering the 2018 to 2025 reference period, based on the availability and comparability of the relevant data.
4. Key Variables
The study examined the following principal variables:
Artificial Intelligence Adoption
Measured using the percentage of firms reporting AI utilization in at least one business function.
Measured using the percentage of firms reporting AI utilization in at least one business function.
Digital Infrastructure
Represented through indicators relating to internet connectivity, cloud computing readiness, and digital technological infrastructure.
Represented through indicators relating to internet connectivity, cloud computing readiness, and digital technological infrastructure.
Business Productivity
Measured using GDP per worker in constant 2015 US dollars.
Measured using GDP per worker in constant 2015 US dollars.
AI Investment
Used as an additional indicator of national investment and development in artificial intelligence technologies.
Used as an additional indicator of national investment and development in artificial intelligence technologies.
Industry Data Intensity
Examined as a contextual factor associated with differences in AI adoption across industries.
Examined as a contextual factor associated with differences in AI adoption across industries.
5. Statistical Analysis
The study employed descriptive statistics, Pearson correlation analysis, and multiple regression analysis using ordinary least squares (OLS).
The regression models examined the relationships between AI adoption, digital infrastructure, and business productivity. An interaction between AI adoption and digital infrastructure was also included to examine whether digital infrastructure influenced the relationship between AI adoption and productivity.
6. Authors and Affiliations
The study was authored by the following researchers:
Mhel Cedric D. Bendo
Role: First Author and Corresponding Author
Affiliation: College of Business Administration, Polytechnic University of the Philippines, Maragondon Campus, Cavite, Philippines
Role: First Author and Corresponding Author
Affiliation: College of Business Administration, Polytechnic University of the Philippines, Maragondon Campus, Cavite, Philippines
Assoc. Prof. Domar C. Alviar, DevCom
Role: Co-Author
Affiliation: Arts and Languages Department, College of Education, Arts, and Sciences, National University, Manila, Philippines
Role: Co-Author
Affiliation: Arts and Languages Department, College of Education, Arts, and Sciences, National University, Manila, Philippines
Prof. Maria Victoria Ulgado-Rosas, PhD, DBE, CMC, LPT, RBE, FriEcon
Role: Co-Author
Affiliation: Graduate School of Business, Colegio de San Juan de Letran, Manila, Philippines
Role: Co-Author
Affiliation: Graduate School of Business, Colegio de San Juan de Letran, Manila, Philippines
Asst. Prof. Avillardo V. Clarin, MBA, MM
Role: Co-Author
Affiliation: College of Business and Accountancy, National University, Manila, Philippines
Role: Co-Author
Affiliation: College of Business and Accountancy, National University, Manila, Philippines
Dr. Lucky S. Carpio
Role: Co-Author
Affiliation: Florentino Cayco Memorial School of Graduate Studies, Arellano University, Manila, Philippines
Role: Co-Author
Affiliation: Florentino Cayco Memorial School of Graduate Studies, Arellano University, Manila, Philippines
Dr. Ariel M. Gomez
Role: Co-Author
Affiliation: Architectural Engineering Department, United Arab Emirates University, Maqam Campus, Al Ain, United Arab Emirates
Role: Co-Author
Affiliation: Architectural Engineering Department, United Arab Emirates University, Maqam Campus, Al Ain, United Arab Emirates
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