Artificial Intelligence in Entrepreneurship
How is Entrepreneurial Discovery shaping up in
era of progressive AI development?
Principles of Entrepreneurship & Innovation (Course A) (140.030, 23W)
MARTINA KESINOVIC, 01644260
INTRODUCTION
INTRODUCTION ............................................................................................................................ 1
DEFINITION AI .............................................................................................................................. 2
AREAS OF APPLICATION OF AI IN ENTREPRENEURSHIP .................................................................. 2
THEORETICAL FRAMEWORK.......................................................................................................... 3
KIRZNER’S THEORY ............................................................................................................................ 3
SCHUMPETER’S THEORY ..................................................................................................................... 3
KIRZNER’S DISEQUILIBRIUM ENTREPRENEURSHIP IN THE AI ERA ................................................... 4
SCHUMPETER’S DISEQUILIBRIUM ENTREPRENEURSHIP IN THE AI ERA............................................ 4
ENTREPRENEURIAL DISCOVERY IN AI PROJECTS ............................................................................. 5
OPPORTUNITIES AND CHALLENGES ............................................................................................... 6
CASE STUDY “ALEXA” ................................................................................................................... 7
IMPACT ON INNOVATION AND ECONOMIC DEVELOPMENT ........................................................... 7
SUMMARY ................................................................................................................................... 8
I
Introduction
In the rapidly evolving landscape of entrepreneurship, the integration of artificial
intelligence (AI) has proven to be a transformative force, reshaping traditional
paradigms and opening up new opportunities. This article begins with a definition of
AI and explains its many applications in the field of entrepreneurship. From improving
decision-making processes to revolutionizing product development and customer
engagement, the impact of AI extends to various facets of entrepreneurial activity.
To provide a theoretical foundation for our analysis, the seminal works of two
eminent scholars, Israel Kirzner and Joseph Schumpeter, are examined. Kirzner's
theory of entrepreneurial discovery, which emphasizes the role of the entrepreneur in
identifying and exploiting market opportunities, and Schumpeter's theory, which
emphasizes the disruptive role of innovation as a driver of economic progress, are
drawn upon. Drawing on Kirzner's and Schumpeter's framework, it explores how AI is
amplifying entrepreneurial activity in the context of disequilibrium and ushering in a
new era of entrepreneurial discovery. Using case studies and empirical evidence, the
intricacies of AI-driven entrepreneurial ventures are explored, examining the
dynamics of opportunity recognition, resource allocation and value creation. But with
opportunities come challenges. A careful analysis of the potential pitfalls and
obstacles associated with integrating AI into business ventures is undertaken.
As an example, the development of Amazon's 'Alexa' is analyzed, showing how AI is
revolutionizing the way consumers interact with technology.
Finally, the wider impact of AI-driven entrepreneurship on innovation and economic
development will be explored. Through the intricate interplay between AI and
entrepreneurial activities, opportunities to foster innovation ecosystems and spur
economic growth in the digital age will be uncovered.
Through this comprehensive analysis, it aims to highlight the transformative potential
of AI for entrepreneurship and entrepreneurial thinking and action, while navigating
the nuanced landscape of opportunities and challenges it presents.
1
Definition AI
Artificial intelligence (AI) refers to the ability of machines to perform complex tasks
that would normally require human intelligence. This includes interpreting external
data, learning from this data and adapting flexibly to changing requirements in order
to achieve specific goals (adapted from Haenlein and Kaplan, 2019; He et al., 2019).
The basis of AI is learning, which in turn is based on algorithms. Algorithms are
methods for calculating information that are at the heart of every AI application.
These algorithms enable machines to recognize patterns in the data, draw
conclusions and make decisions in a way that is similar to human intelligence, but
often with much greater speed and accuracy. In this respect, AI marks a significant
step forward in human-machine interaction and promises to revolutionize many
aspects of our daily lives. (Chalmers et al., 2021)
Areas of application of AI in entrepreneurship
The new innovations are changing technological entrepreneurship, especially with
regard to the processes of founding new companies (Elia et al., 2020). AI has a
particularly critical impact on how entrepreneurs develop, shape and scale their
businesses as part of the entrepreneurial process (Chalmers et al., 2021). Like any
radical innovation, AI can empower entrepreneurs and enable the creation of new
opportunities by introducing new products or services in an entrepreneurial way
(Audretsch, 2019).
Moreover, AI techniques can improve the decision-making systems adopted by
entrepreneurs by increasing the quality of decisions made in terms of their
effectiveness and efficiency, thus improving operational performance (Kraus et al.,
2020).
Furthermore, AI can not only improve the performance of AI-driven organizations, but
also encourage more traditional companies to develop their business models using
AI-based solutions. The advent of the AI era has therefore created the greatest
entrepreneurial opportunity in the history of civilization (Shepherd and Majchrzak,
2022; Iansiti and Lakhani, 2020)
In the field of automation, entrepreneurs can use AI to automate repetitive tasks and
increase the efficiency of their operations. By developing AI-based products and
services, innovative solutions to existing problems can be developed, enabling
companies to stand out from the competition and tap into new market opportunities.
In addition, personalized recommendation systems and chatbots can be used to
improve customer interaction and personalize the customer experience, leading to
higher customer satisfaction and loyalty. (Giuggioli and Pellegrini 2022; Daugherty
and Wilson, 2018).
Overall, the application areas of AI in entrepreneurship offer a wide range of
opportunities that enable companies to optimize their business practices, develop
innovative products and services and position themselves successfully on the
market. (Giuggioli and Pellegrini 2022; Darwish et al., 2020)
2
Theoretical Framework
The theories of Israel Kirzner and Joseph Schumpeter regarding the recognition of
opportunities and imbalances in the market are used as a theoretical framework for
the groundwork of the topic. Kirzner's theory emphasizes the role of the entrepreneur
as a discoverer of unexploited resources, while Schumpeter emphasizes the
importance of disruption and creative destruction. These approaches provide a
framework for analyzing the interactions between artificial intelligence (AI) and
entrepreneurship.
Kirzner’s theory
Entrepreneurial discovery, as conceptualized by Kirzner, refers to the ongoing
process by which entrepreneurs identify previously undiscovered opportunities for
profit and value creation. At the heart of Kirzner's concept is the notion of the
entrepreneur as a discoverer of market imbalances and potential profit opportunities.
These discoveries can be made both on the basis of information about existing gaps
in the market and through the creation of new markets and the introduction of
innovative products or services. Kirzner emphasizes the role of uncertainty and
imbalance in the market and argues that successful entrepreneurs not only generate
profits through their ability to engage in entrepreneurial discovery, but also contribute
to improving market efficiency by offsetting these imbalances. (Kirzner, 1973)
Entrepreneurial discovery requires an active and creative entrepreneurial mindset, as
entrepreneurs continuously seek out new opportunities and are willing to take risks to
exploit them. Kirzner's concept emphasizes the importance of the entrepreneurial
spirit and highlights the role of the entrepreneur as a driving force for economic
innovation and progress. (Kirzner, 1973)
Schumpeter’s theory
Entrepreneurial Discovery, in Schumpeter's sense, refers to the ongoing process by
which entrepreneurs recognize and exploit new business opportunities to drive
economic change and innovation. Schumpeter coined the term "creative destruction"
to describe how entrepreneurs challenge and change existing market structures and
conventions by introducing new products, technologies or business models. For
Schumpeter, the entrepreneur is an agent of change who stimulates competition and
creates new growth impulses for the economy through his innovative strength and
willingness to take risks. Entrepreneurial discovery according to Schumpeter is
closely linked to the concept of economic change, which is characterized by the
continuous introduction of innovations and the transformation of industries.
(Schumpeter, 1942).
Entrepreneurial Discovery requires an entrepreneurial mindset that is willing to
challenge traditional ways of thinking and break new ground. Schumpeter's concept
emphasizes the importance of the entrepreneurial spirit in creating wealth and growth
in a dynamic economy. By continuously creating and introducing innovations,
entrepreneurs not only drive economic growth, but also ensure a constant
reorientation and improvement of the economic system (Schumpeter, 1942).
3
Kirzner’s disequilibrium entrepreneurship in the AI era
The concept of disequilibrium entrepreneurship, as developed by Israel Kirzner in his
1973 work "Competition and Entrepreneurship", emphasizes the role of the
entrepreneur as a person who perceives and compensates for imbalances in the
market in order to make profits. This perspective emphasizes the active role of the
entrepreneur in identifying gaps in the market and untapped resources. Especially in
the era of artificial intelligence (AI), imbalance entrepreneurship is gaining importance
as the rapid development of AI technologies creates new opportunities and
challenges for entrepreneurs.
A key characteristic of disequilibrium entrepreneurship in the AI era is the ability of
the entrepreneur to recognize and leverage the potential of AI technologies to
develop innovative business models and gain competitive advantage. As
emphasized by Kirzner, the core of imbalance entrepreneurship lies in the perception
of imbalances in the market and the exploitation of these imbalances to create value.
This perspective provides a framework for analyzing entrepreneurial discovery in AI
projects, as it emphasizes the importance of actively seeking new opportunities and
exploiting untapped resources. By integrating Kirzner's concept of disequilibrium
entrepreneurship into the discussion of entrepreneurship in the AI era, we can
provide a broader perspective on the role of the entrepreneur in a rapidly changing
and highly technological environment. (Kirzner, 1973)
Schumpeter’s disequilibrium entrepreneurship in the AI era
The concept of disequilibrium entrepreneurship, as developed by Joseph
Schumpeter in his 1911 work "The Theory of Economic Development", emphasizes
the role of the entrepreneur as a driver of economic change. Schumpeter described
the entrepreneur as a person who innovates by introducing new combinations of
production factors, thus reshaping the market. In the era of artificial intelligence (AI),
disequilibrium entrepreneurship is gaining importance as the rapid development of AI
technologies creates new opportunities and challenges for entrepreneurs.
A key characteristic of disequilibrium entrepreneurship in the AI era is the
entrepreneur's ability to recognize and leverage the potential of AI technologies to
develop innovative business models and gain competitive advantage. As
emphasized by Schumpeter, the core of entrepreneurship lies in the creation of
"creative destruction" by replacing old business models and technologies with new
and innovative ideas.
This perspective provides a framework for analyzing entrepreneurial discovery in AI
projects, as it emphasizes the importance of actively seeking new opportunities and
exploiting untapped resources. By integrating Schumpeter's concept of
entrepreneurship into the discussion of entrepreneurship in the AI era, we can
provide a broader perspective on the role of the entrepreneur in a rapidly changing
and highly technological environment. (Schumpeter, 1911)
4
In summary, both Kirzner's concept of disequilibrium entrepreneurship and
Schumpeter's theory of entrepreneurship can be applied to the era of artificial
intelligence (AI). Both approaches emphasize the active role of the entrepreneur in
identifying and exploiting market opportunities and introducing innovations. While
Kirzner focuses on the perception of imbalances in the market and emphasizes the
role of the entrepreneur as an adaptor and balancer, Schumpeter highlights the
importance of the entrepreneur as an innovator and creator who transforms the
market by introducing new ideas and technologies. In the era of Artificial Intelligence,
both approaches can be applied as entrepreneurs can identify new opportunities and
develop innovative business models through the use of AI technologies. By
integrating Kirzner's and Schumpeter's concepts, we can thus offer a comprehensive
perspective on the role of the entrepreneur in a high-tech and rapidly changing
environment.
Entrepreneurial discovery in AI projects
It is important to observe how AI can affect individual decisions, particularly in
relation to participation in entrepreneurship and the factors that influence the
likelihood and type of business creation. For this purpose, the article "Artificial
Intelligence and Entrepreneurship: Implications for Venture Creation in the Fourth
Industrial Revolution" by Chalmers, McKenzie and Carter was used, which refers to
many works by other scientists. Among other things, it draws on Vogel's framework
for understanding the causes of business start-ups, in which he describes triggers
and idea generation as early phases of this process. These activities can be
influenced by both individual and external systemic factors, suggesting that the
implementation of AI, whether selective or ubiquitous, can influence both an
individual's decision to start a business and the type of business founded (Vogel,
2017; McMullen & Shepherd, 2006).
At the external level, various factors such as spatial, temporal, regulatory and
technological changes play a role in the implementation of start-up ideas. In the
context of AI, scholars have identified significant potential changes to the external
environment, including proposed new economic and social policy responses to
automatization, changes in competitive forces and broader shifts in market
operations (Davidsson et al., 2018; Pulkka, 2017; Agrawal et al., 2018; Furman &
Seamans, 2019). For example, the introduction of a universal basic income (UBI) or
similar fiscal transfers to compensate for job losses due to automation could create a
social safety net for people without work to start new businesses, changing the
antecedents for business start-ups related to risk-taking and creativity (D'Mello, 2019;
Levine, 2019). However, there is also the possibility that AI-driven technology
platforms will dominate economic life even more, which could lead to a decline in
entrepreneurial activity due to market consolidation by large technology companies
(Shapiro, 2019; Zhu & Liu, 2018); (Chalmers, et. al. 2021)
Specifically, several factors influence entrepreneurs' decision to start new
businesses, including the desirability and feasibility of opportunities. AI offers
numerous opportunities for start-up activities, which are moderated by aspects of
feasibility, especially in terms of entrepreneurial self-efficacy. Despite the
attractiveness of AI-based entrepreneurial opportunities, there remains a significant
5
skills gap and labor shortage in key technical positions required to implement
complex AI systems (Marr, 2018; Cheng, 2018).
Furthermore, there is a growing recognition of the need to consider the societal
impacts of AI-driven entrepreneurship, such as the potential displacement of jobs and
the need to retrain and upskill workers to adapt to the changing technological
landscape. In addition, the ethical considerations surrounding the use of AI in
entrepreneurship, including issues of bias, privacy and transparency, must be
carefully considered to ensure responsible and equitable innovation in AI-driven
ventures. Overall, the tension between macroeconomic factors influencing venture
creation in the age of AI and individual factors influencing entrepreneurial decisionmaking is demonstrated. This highlights the need for further research into the impact
of global trends in AI development on entrepreneurship and the economy, as well as
the role of AI in the search for and development of new business ideas. (Chalmers,
et. al. 2021)
Opportunities and challenges
The development and integration of artificial intelligence (AI) comes with many
opportunities and challenges. In order not to go beyond the scope of the paper, the
focus will only be on a few, but quite significant, opportunities and challenges.
Opportunities for entrepreneurs:
In today's era of artificial intelligence (AI), entrepreneurs are presented with a
multitude of new opportunities, but also challenges. The integration of AI
technologies into entrepreneurial activities opens up exciting prospects that need to
be exploited. On the one hand, the automation of processes through AI technologies
enables a more efficient use of resources and allows entrepreneurs to focus on
strategic decisions. On the other hand, AI-supported analysis tools support datadriven decision-making and thus improve companies' chances of success. In
addition, AI systems help to identify new business opportunities by recognizing
trends and patterns in large amounts of data, thus enabling innovative products or
services. (Shepherd and Majchrzak, 2022)
Despite these promising opportunities, entrepreneurs also face a number of
challenges. Data protection and ethical concerns are particularly relevant, as the use
of AI often goes hand in hand with the processing of sensitive data. Entrepreneurs
must ensure that they respect the privacy of their customers and adhere to ethical
standards. (Shepherd and Majchrzak, 2022)
Overall, the integration of AI technologies offers both opportunities and challenges for
entrepreneurs. By being aware of these and preparing for them, entrepreneurs can
exploit the potential of AI while minimizing possible risks. (Shepherd and Majchrzak,
2022)
6
Case Study “Alexa”
In the following, a case study is presented that focuses on a prominent example from
the corporate world: the product "Alexa" from Amazon:
Since its launch in 2014, Amazon Alexa has become an integral part of many
households. The AI-powered voice assistant has revolutionized the way people
interact with technology in their own homes. Despite its successes, Amazon strives
to continuously improve Alexa's capabilities to enable more natural and intelligent
interaction.
Despite Alexa's successes, there is still room for improvement, especially in terms of
the naturalness and intelligence of the interaction. Amazon is looking for ways to
improve Alexa's conversational ability while maximizing its usefulness and value to
users.
The introduction of generative AI into Alexa's functionality is a crucial step in
achieving these goals. By developing a new large language model (LLM) specifically
for voice interactions, Alexa can now have more natural and intelligent conversations.
This technology offers improved conversational skills, real-time information, efficient
control of smart home devices and an optimized home entertainment experience.
Also the introduction of generative AI in Alexa has enabled promising progress in the
development of a more natural and intelligent interaction. Although the new features
are still in the development phase, testing so far indicates that Alexa is able to
respond more intelligently and contextually aware to user requests.
Overall, the introduction of generative AI in Amazon Alexa marks an important
milestone on the way to an even more intuitive and intelligent user experience.
Amazon is leading the way in delivering a voice-powered assistant that has the
potential to further transform the way people interact with technology. (Amazon,
2023)
Impact on innovation and economic development
In this section, the potential impact of entrepreneurial discovery in the AI era on
innovation and economic development is discussed.
Incredible potential is offered by entrepreneurial discovery in the AI era to drive
innovation and foster economic development. The integration of AI technologies into
entrepreneurial activities enables new business opportunities to be identified,
innovative products and services to be developed, and existing business models to
be transformed. Through the utilization of AI, data can be analyzed more efficiently,
trends and patterns can be identified, and informed decisions can be made,
potentially leading to an accelerated rate of innovation. (Shepherd and Majchrzak,
2022)
Moreover, the competitive landscape can be altered by entrepreneurial discovery in
the AI era, assisting companies in gaining a competitive advantage and
differentiating themselves from competitors. Companies that integrate AI into their
7
business models early and successfully can tap into new markets, gain market share,
and strengthen their position in the industry, potentially resulting in increased
competition and a more dynamic economy. However, alongside the opportunities,
challenges are also present in the integration of AI in entrepreneurship. These
challenges encompass concerns regarding data protection, ethical issues, skills
shortages, and technological dependency. Proactive measures need to be taken by
companies to address these challenges and develop suitable strategies to fully
exploit the potential of AI while minimizing potential risks. (Shepherd and Majchrzak,
2022)
Overall, this research indicates that entrepreneurial discovery in the AI era can
significantly impact innovation and economic development. Companies that
effectively integrate AI into their business models can benefit from accelerated
innovation processes, enhanced competitiveness, and long-term growth.
Nonetheless, it is imperative to acknowledge the challenges and formulate
appropriate strategies to harness the full potential of AI. (Shepherd and Majchrzak,
2022)
Summary
In summary, the paper reflects on the diverse potentials and challenges arising from
the integration of artificial intelligence (AI) into entrepreneurial activities. Various
theoretical approaches were examined, including Kirzner's and Schumpeter's
theories of opportunity recognition and market disequilibrium.
The analysis shows that AI is a transformative force in entrepreneurship and can
drive innovation in various industries. By applying AI, new business opportunities can
be identified, innovative products can be developed and existing business models
can be transformed. This offers opportunities for growth and competitive advantage,
but also poses risks such as privacy concerns and the potential displacement of
individual players through the overuse of AI.
I agree with researchers that a balanced use of AI is crucial to maintain the diversity
and dynamism of entrepreneurship. A conscious examination of the potentials and
risks of AI and measures to promote broad participation in entrepreneurship are
therefore of great importance. In my opinion, it is important to conduct further
research to better understand the long-term impact of AI on innovation and economic
development.
8
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