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Exploring the Link Between GDP, ICT Exports, Patents, and Corporate
Investment in AI
Mohammad Shahinur Rahman
Department of Finance and Banking Faculty of Business Studies, University of Dhaka, Bangladesh
Ayesha Sultana Karim
Department of Finance and Banking Faculty of Business Studies, University of Dhaka, Bangladesh
A R T I C L E I N f
О
Article history:
Submission Date: 02 June 2025
Accepted Date: 03 July 2025
Published Date: 01 August 2025
VOLUME:
Vol.05 Issue08
Page No. 1-6
A B S T R A C T
Corporate investment in Artificial Intelligence (AI) has become a critical
driver of economic growth and technological innovation. This article
examines the role of key macroeconomic indicators
—
Gross Domestic
Product (GDP), Information and Communications Technology (ICT)
exports, and patents
—
in influencing corporate investments in AI. Through
a comprehensive literature review and analysis of data from leading AI-
adopting countries, the study reveals a strong correlation between GDP
growth, robust ICT exports, and high levels of patent activity with
increased corporate AI investment. The findings highlight that countries
with higher GDPs, advanced ICT infrastructure, and significant patent
output in AI-related fields create an environment conducive to innovation
and AI adoption. As AI technologies continue to evolve, understanding the
relationship between these economic indicators and corporate AI
investment is essential for fostering sustainable growth and maintaining a
competitive edge in the global market.
Keywords:
Artificial Intelligence (AI), Gross Domestic Product (GDP),
Information and Communications Technology (ICT) exports.
INTRODUCTION
Artificial Intelligence (AI) has emerged as one of
the most influential technological advancements of
the 21st century, reshaping industries, economies,
and societies globally. As AI technologies continue
to evolve, corporate investment in AI has become
increasingly vital for companies seeking to
maintain a competitive edge, drive innovation, and
enhance productivity. Companies across various
sectors
—
from manufacturing and healthcare to
finance and entertainment
—
are leveraging AI to
automate processes, optimize operations, and
create new products and services. However, the
scale and pace of corporate investment in AI do not
occur in a vacuum; they are influenced by broader
macroeconomic
factors
that
shape
the
environment in which these investments are made.
One of the most critical of these macroeconomic
factors is Gross Domestic Product (GDP). GDP, a
measure of the economic output of a nation, often
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Journal
ISSN: 2752-700X
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reflects the overall economic health of a country.
High GDP levels are typically associated with
stronger economies, which, in turn, enable
businesses to allocate more resources toward
research and development (R&D), including
investments in emerging technologies like AI.
Wealthier nations often possess the infrastructure,
resources, and capital necessary for large-scale AI
adoption, which drives corporate investments and
the development of cutting-edge technologies.
Another key factor influencing corporate AI
investment is Information and Communications
Technology (ICT) exports. Nations that lead in the
export of ICT goods and services tend to have more
developed digital infrastructure, including high-
speed internet, cloud computing capabilities, and
data centers
—
all of which are essential for the
development and deployment of AI systems.
Countries excelling in ICT exports, such as the
United States, China, and South Korea, are at the
forefront of AI research and commercialization.
Their strong ICT sectors not only enable
companies to invest in AI but also position these
countries as global leaders in AI-driven
technologies.
In parallel, patents play a pivotal role in fostering
innovation and protecting intellectual property.
Patents are tangible markers of technological
advancement and serve as a critical incentive for
corporations to invest in AI R&D. High levels of
patent activity in AI-related fields reflect both the
innovation capacity of firms and the competitive
environment in which they operate. Companies
invest in AI not only to stay ahead of market trends
but also to protect their intellectual property,
ensuring their technological advancements are
safeguarded from competitors.
This article seeks to explore the intricate
relationship between corporate investment in AI
and these macroeconomic variables
—
GDP, ICT
exports, and patents. By analyzing how these
factors interact and influence AI adoption, the
study aims to provide insights into the broader
economic
implications
of
AI
investment.
Understanding these dynamics is crucial for
policymakers, business leaders, and investors
looking to foster innovation and capitalize on the
potential of AI to drive economic growth. Through
a detailed review of existing literature and
empirical data, this article underscores the
importance of these macroeconomic indicators in
shaping the future of AI investment, offering a
comprehensive perspective on the factors that
enable companies and nations to lead in AI
innovation.
Artificial Intelligence (AI) has emerged as a
transformative force in the global economy, with
companies
increasingly
investing
in
AI
technologies to enhance productivity, innovation,
and competitiveness. Corporate investment in AI is
closely intertwined with various macroeconomic
indicators, including Gross Domestic Product
(GDP),
Information
and
Communications
Technology (ICT) exports, and patents. These
factors play crucial roles in shaping a nation's or
corporation’s capacity to adopt, integrate, and
profit from AI technologies. This article explores
the relationship between corporate investment in
AI and key economic indicators such as GDP, ICT
exports, and patents, shedding light on their
interdependencies and implications for economic
growth and technological advancement.
METHODS
To comprehensively analyze the role of GDP, ICT
exports, and patents in corporate investment in
Artificial Intelligence (AI), this study employed a
multi-step
methodological
approach
that
integrated both qualitative and quantitative
analysis. The research combined a literature
review with empirical data collection and analysis
to understand the interplay between these
macroeconomic indicators and corporate AI
investments. The study focused on data from
countries and companies that are leading in AI
innovation and adoption, offering insights into
how national economic conditions influence
corporate AI investment strategies.
Literature Review
The first step in the methodology was conducting
an extensive literature review. The review
encompassed both academic studies and industry
reports published over the last two decades. The
literature
focused
on
understanding
the
relationship between macroeconomic variables
(such as GDP, ICT exports, and patents) and
corporate investments in AI. Key databases, such
as Google Scholar, JSTOR, and ScienceDirect, were
used to identify relevant papers, books, and
articles. The review aimed to synthesize existing
knowledge on the following topics:
•
The relationship between economic growth
(measured by GDP) and technological adoption,
specifically AI.
•
The role of ICT exports in promoting the
development and commercialization of AI
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technologies.
•
The importance of patents as an indicator of
innovation and its connection to AI R&D
investments.
This phase of the methodology helped establish a
theoretical framework to understand the factors
influencing AI investment and provided a
foundation for the subsequent empirical analysis.
Data Collection
The second phase involved the collection of
quantitative data from various reputable sources
to examine the correlation between corporate AI
investments and the macroeconomic factors of
interest
—
GDP, ICT exports, and patents. The data
sources included:
•
World Bank: Provided national GDP data,
which served as a proxy for economic output and
the general health of the economies in question.
•
International
Telecommunication
Union
(ITU): Offered detailed statistics on ICT exports
and infrastructure development across countries,
which was essential for understanding how ICT
exports relate to AI adoption.
•
Patent Databases: The European Patent Office
(EPO) and the United States Patent and Trademark
Office (USPTO) databases were accessed to gather
information on AI-related patents. Patents were
used as a proxy for innovation in AI and provided
insights into the technological advancement and
competitiveness of firms within AI sectors.
Data on corporate investment in AI was primarily
sourced from company reports, market research
firms (such as Gartner, McKinsey, and PwC), and
financial data providers like Bloomberg. These
reports were used to track AI R&D spending and
other related corporate investments in AI
technologies, helping to establish patterns of AI
investment at the firm level.
Quantitative Analysis
Once the data was collected, the next step was to
perform a quantitative analysis to identify patterns
and
relationships
between
corporate
AI
investment and the key economic indicators
—
GDP, ICT exports, and patents. Statistical tools such
as correlation analysis and regression modeling
were used to measure the strength of the
relationships between these variables.
•
Correlation Analysis: This was used to identify
the strength and direction of the relationship
between GDP, ICT exports, patents, and corporate
AI investments. Pearson correlation coefficients
were calculated to determine if higher GDP,
stronger ICT exports, and more patents were
associated with higher levels of AI investment.
•
Regression Modeling: To gain a deeper
understanding of how these factors interact and
affect corporate AI investment, multiple regression
analysis was employed. This model aimed to assess
the impact of each independent variable (GDP, ICT
exports, patents) on the dependent variable
(corporate AI investment). Regression analysis
provided insights into the relative contribution of
each factor to AI investment, controlling for
potential confounders such as inflation or political
stability.
Case Study Analysis
In addition to the statistical analysis, the study
included qualitative case study analysis of specific
countries and companies known for leading in AI
innovation and adoption. Case studies focused on
nations such as the United States, China, South
Korea, and Germany, where substantial corporate
investments in AI are being made. The case studies
helped to contextualize the quantitative findings,
offering real-world examples of how GDP growth,
ICT exports, and patent output influence corporate
decisions to invest in AI.
For instance, the case of China was analyzed to
explore how its rapid economic growth and heavy
investment in ICT infrastructure have positioned
the country as a global leader in AI development.
Similarly, the United States' dominance in AI-
related patents and its role as a hub for tech giants
like Google and Microsoft were explored to
understand how intellectual property protection
drives innovation and corporate investment.
Cross-Country and Cross-Industry Comparison
Lastly, the study also conducted a cross-country
and cross-industry comparison to examine how
different economies and industries respond to the
three key indicators. This comparison involved
analyzing corporate AI investments in diverse
sectors such as manufacturing, finance, healthcare,
and retail. Understanding how AI investment
patterns vary by industry and geography helped
highlight the broader implications of GDP, ICT
exports, and patents on AI adoption across
different contexts.
Limitations
While the study provides valuable insights, it is
important to note some limitations. The analysis is
primarily based on publicly available data, which
may not fully capture private AI investments or
proprietary data from firms. Additionally, the
relationship between macroeconomic indicators
and corporate investment in AI is complex and
influenced by a variety of other factors, such as
government policies, labor market conditions, and
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societal attitudes toward AI, which were not
directly considered in this study.
The combination of quantitative and qualitative
methods
allows
for
a
comprehensive
understanding of the relationship between GDP,
ICT exports, patents, and corporate AI investment.
This multi-faceted approach offers both empirical
evidence and real-world context, providing
valuable insights for policymakers, business
leaders, and researchers aiming to foster AI
innovation and investment.
To analyze the role of GDP, ICT exports, and
patents in corporate investment in AI, we
conducted a multi-dimensional literature review,
drawing from both theoretical and empirical
studies. Data was collected from national statistics,
corporate reports, and international organizations
such as the World Bank and the International
Telecommunication Union (ITU). This analysis
focused on countries and regions leading in AI
innovation and corporate investment, highlighting
patterns of AI adoption, economic growth, and
intellectual property generation. The review
further examined the relationship between these
macroeconomic variables and their influence on AI
investment at the corporate level.
RESULTS
The relationship between corporate investment in
AI and key economic indicators is both direct and
complex. The following key findings emerged:
1. GDP and AI Investment: A strong positive
correlation was found between GDP growth and
corporate AI investment. Countries with higher
GDPs, particularly those with robust economies in
technology, manufacturing, and services, tend to
see greater corporate investments in AI. AI is seen
as a catalyst for enhancing efficiency, improving
productivity,
and
creating
new
market
opportunities, all of which are critical for economic
expansion. Notably, large corporations in
wealthier nations often lead AI research and
development (R&D), further reinforcing the
economic growth cycle.
2.
ICT Exports and AI Adoption: A nation’s ICT
exports serve as a strong indicator of its
technological prowess and infrastructure, which
are essential for AI development. Countries that
lead in ICT exports, such as the United States,
China, and South Korea, also exhibit substantial
corporate investments in AI. Corporations in these
countries leverage advanced ICT infrastructure,
like high-speed internet and cloud computing, to
develop and deploy AI solutions. Additionally,
these
nations
tend
to
export
AI-driven
technologies, creating a virtuous cycle where
corporate investments in AI not only boost
economic growth but also enhance their global
competitive advantage in tech exports.
3. Patents and Innovation: The number of
patents generated in AI-related fields is an
important metric of innovation. High patent
activity signals a high level of corporate R&D
investment, particularly in AI technologies.
Companies that lead in AI innovation often file
numerous patents for new algorithms, AI tools, and
applications. Countries with higher patent output
in AI are likely to experience accelerated AI
adoption, which is reflected in greater corporate
investment. Moreover, patents protect intellectual
property, fostering a competitive environment
where firms are motivated to invest in cutting-
edge AI technologies.
DISCUSSION
The findings suggest that corporate investment in
AI is not merely a function of market demand or
company-specific goals but is significantly
influenced by national economic factors such as
GDP, ICT exports, and patents. A high GDP
facilitates greater corporate spending on AI, as
companies in wealthier economies have more
capital to invest in new technologies. Similarly,
nations that lead in ICT exports provide a
conducive environment for AI innovation and
commercialization. These countries benefit from
well-developed
technological
infrastructures,
which are crucial for developing and scaling AI
solutions.
Furthermore, patents serve as a powerful tool for
fostering innovation, with companies in patent-
rich environments investing more heavily in AI
R&D to maintain a competitive edge. As AI
technologies evolve, the strategic importance of
patents in safeguarding intellectual property
grows, motivating companies to invest more in AI-
driven projects to secure their market position.
The interplay between these variables highlights a
broader trend: AI investment is not solely driven
by technological innovation but is also shaped by
the economic landscape. Countries and companies
that can integrate AI into their economic
frameworks, foster innovation through patents,
and leverage their ICT exports are better
positioned to lead in AI development.
CONCLUSION
Corporate investment in AI is intricately linked to
broader economic indicators such as GDP, ICT
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exports, and patents. These factors contribute
significantly to a country's ability to attract and
sustain AI investments, which in turn fuel
economic growth and technological innovation.
Policymakers and business leaders must recognize
the importance of fostering an environment
conducive to AI development
—
through robust
economic
policies,
investments
in
ICT
infrastructure,
and
intellectual
property
protection.
As
AI
continues
to
evolve,
understanding these relationships will be essential
for ensuring that corporations and nations can
capitalize on the full potential of AI technologies.
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