NAVIGATING ENTREPRENEURIAL CHALLENGES WITH THE
HELP OF AI: AWARENESS, BENEFITS, AND BARRIERS IN AI
TOOLS UTILIZATION BY KNOWLEDGE INTENSIVE ENTERPRISES
GM1361 Master Degree Project in Knowledge-based Entrepreneurship
Graduate School Spring 2024
Author: Marios Kyriakis
Supervisor: Rögnvaldur Saemundsson
Acknowledgements
The true story is that I never thought I would pursue a master degree. This changed due to
this degree being connected heavily with opportunities that will impact my life and they are
not restricted to the academic era. A significant factor was not only me who realized these
opportunities but also my dear parents, Ilias and Kyrano, and brother, Alexander, who could
show me the way of this path. My dear family has gone through so many difficulties and I am
really grateful for them. Apart from them, my grandfather who unfortunately passed away in
2017, had significantly impacted my life with his sayings that I will always remember.
Before coming to this university for the program of knowledge-based entrepreneurship, I
faced a significant challenge while trying to find a place to stay leading me to getting
scammed. Nevertheless, I was lucky since I was able to find a place to stay for the first
months through facebook, thanks to Grigoris and Sonja, who follow the teachings of Jesus
Christ.
During this program, I met some great people from different backgrounds and nationalities,
Afroditi, Helia, Maria, Chie, Sarah, Rima, Bahareh, Agis, Victor, Vitor, Jonathan, Shikhar,
Savvas, Manish, Christina, Jenny and I hope they make the right decisions in their lives. I
would love to write something about each of them, but they already know.
The writing of this thesis was a challenge since it was something new to me and because life
is complicated by nature. Why I choose this topic results from me having realized that there
are entrepreneurs who use AI tools and they overcome some challenges with these AI tools.
Yet, these entrepreneurs did not come from knowledge-intensive enterprises and this sparked
my interest. It was great to be challenged, and the university, the survey respondents, and
interviewees, deserve a thank you for their contribution as well.
1
Abstract
This thesis aimed to find a connection between the utilization of AI tools and the challenges
faced by knowledge-intensive enterprises (KIEs). Therefore, the purpose was to showcase
that entrepreneurs and professionals are aware that they can use AI for overcoming the
challenges that they face within their enterprises and do not use them just for the sake of it.
The focus was also to the challenges that they faced during the utilization of the tools that
they used, and recommendations they had. For reaching the goals, a mixed method was used,
including quantitative data from survey responses and qualitative data from interviews. The
findings showcased that the level of awareness was low since only one survey respondent and
one interviewee used AI tools for overcoming challenges they faced. The challenges that they
faced were: lack of reputation, and business model development. Regarding the challenges
associated with AI tools utilization, these were mainly: the usage of an appropriate prompt,
and initial costs.
2
Table of Contents
1. Introduction........................................................................................................................................ 5
1.1 Background and purpose..........................................................................................................5
1.2 Research Question....................................................................................................................6
1.3 Significance of the Study......................................................................................................... 6
1.4 Thesis Structure........................................................................................................................6
2. Literature Review...............................................................................................................................7
2.1 The Entrepreneurial Process.................................................................................................... 7
2.1.1 Decision-making Models................................................................................................. 8
2.2 Challenges Faced in The Entrepreneurial Process................................................................... 8
2.2.1 The Case of Zappos..........................................................................................................9
2.4 Knowledge Intensive Entrepreneurship................................................................................... 9
2.4.1 How KIEs Operate......................................................................................................... 11
2.5 Artificial Intelligence............................................................................................................. 12
2.6 Benefits of AI.........................................................................................................................13
2.7 Challenges Utilizing AI..........................................................................................................14
3. Research Method..............................................................................................................................15
3.1 Research Strategy...................................................................................................................15
3.2 Survey.................................................................................................................................... 15
3.2.1 Survey Preparation.........................................................................................................15
3.2.2 Survey Structure and Content........................................................................................ 17
3.2.3 Survey Sample and Limitations..................................................................................... 17
3.4 Interviews...............................................................................................................................19
3.4.1 Interview Design............................................................................................................ 19
3.4.2 Interview Structure and Content.................................................................................... 19
3.4.3 Interview Sample and Limitations................................................................................. 19
3.5 Summary of Research Method...............................................................................................20
4. Results............................................................................................................................................... 22
4.1 Survey.................................................................................................................................... 22
4.1.1 CO-founder and COO, Company A...............................................................................22
4.1.2 CEO, Company B.......................................................................................................... 22
4.1.3 Lead Developer, Company C......................................................................................... 23
4.1.4 CEO, Company D.......................................................................................................... 23
4.1.5 CEO, Company E...........................................................................................................23
4.1.6 CEO, Company G.......................................................................................................... 24
4.1.7 CEO, Company I............................................................................................................24
4.1.8 Application Developer, Company S...............................................................................24
4.2 Summary of Survey Results...................................................................................................24
4.3 Interviews...............................................................................................................................27
4.3.1 Product Manager, Company L....................................................................................... 28
4.3.2 CEO, Company M..........................................................................................................28
4.3.3 CEO, Company N.......................................................................................................... 29
4.4 Summary of Interview Results...............................................................................................30
5. Analysis............................................................................................................................................. 32
3
5.1 Analysis of Survey................................................................................................................. 32
5.1.1 AI tools used.................................................................................................................. 32
5.1.2 Benefits from using AI tools..........................................................................................32
5.1.3 Challenges Utilizing AI..................................................................................................33
5.2 Analysis of Interviews............................................................................................................34
5.2.1 AI tools used.................................................................................................................. 34
5.2.2 Benefits from using AI tools..........................................................................................34
5.2.3 Challenges Utilizing AI..................................................................................................35
6. Discussion..........................................................................................................................................36
7. Conclusion.........................................................................................................................................39
7.1 Recommendations for future research................................................................................... 39
7.2 Recommendations for new entrepreneurs..............................................................................40
8. References......................................................................................................................................... 41
8.1 From Articles......................................................................................................................... 44
8.2 From Websites........................................................................................................................44
9. Appendix........................................................................................................................................... 44
9.1 Invitation to survey participation 1........................................................................................ 44
9.2 Invitation to survey participation 2........................................................................................ 44
9.3 Survey Reminder 1.................................................................................................................45
9.4 Survey Reminder 2.................................................................................................................45
9.5 Interview guide.......................................................................................................................46
4
1. Introduction
1.1 Background and purpose
The concept of knowledge-intensive entrepreneurship (KIE) is significantly influenced by
technological advancements, as highlighted by Radosevic and Yoruk (2013). On the other
hand, Kloch and Stachlecker (2006) argue that KIE firms, with their strong foundations, serve
as drivers for technological progress and play a vital role in its advancement. In both
scenarios, technological progress plays a pivotal role in this form of entrepreneurship.
This progress can catalyze the emergence of new industries, as well as the transformation or
decline of existing ones, as proposed by Cooper and Schendel (1976). This phenomenon is
commonly referred to as creative destruction, where new companies strive to innovate and
secure a dominant position in the market, while established firms strive to protect their
market share against these new entrants, as highlighted by Greenstein (2004). As an outcome,
the global landscape is in a state of constant change, with economies shifting, new
knowledge-intensive businesses emerging in the service sector, and technologies advancing
(Antonelli & Fassio, 2014).
By harnessing AI capabilities, knowledge-intensive firms can interpret the collected data,
facilitate ideation sessions, aiding teams in generating innovative solutions to complex
problems (Sarker, 2022).
As a result, this study aimed to comprehend how AI tools can assist the entrepreneurial
process of knowledge-intensive enterprises. Meaning if the AI tools are utilized to overcome
challenges that the enterprises face. Despite the wealth of knowledge available, there are
certain unknowns that entrepreneurs may encounter. For instance, entrepreneurs may struggle
to sift through vast amounts of information to identify key insights crucial for transforming
their ideas into successful ventures (Vidgen et al., 2017). Therefore, the AI transformation
improves the digital entrepreneurial capability (Runping et al., 2021).
The entrepreneur is the primary stakeholder in this research paper, as they are the individual
who conceived the idea and strategizes on how to progress. Presently, AI tools are being
integrated into decision systems, which have a significant influence on various applications
and augment intelligent decision-making processes (Phillips-Wren, 2012).
5
Consequently, the purpose was to understand the entrepreneurial challenges and how AI tools
are currently being used by knowledge-intensive businesses. This includes not only the
benefits that these AI tools can have after their utilization but also the challenges that are
associated with their usage.
1.2 Research Question
The research question of this thesis was the following:
What are the opportunities and challenges in utilizing AI tools to address challenges in
knowledge-intensive enterprises (KIE)?
It was narrowed down to knowledge-intensive enterprises, including independent start-ups,
university spin-offs. The research investigated the challenges that they experience as new
firms, their awareness of AI tools, and the benefits/challenges that they experience with the
usage of AI tools.
1.3 Significance of the Study
This study seeked to enhance the comprehension of the convergence of AI and the
entrepreneurial journey, specifically in the realm of knowledge-intensive enterprises. The
outcomes of this research could make a valuable addition to the current body of knowledge
on entrepreneurship and technology, providing valuable insights that can guide KIE firms and
equip them with AI tools that can prove advantageous in the entrepreneurial ecosystem.
1.4 Thesis Structure
This thesis is organized into eight primary chapters. Chapter 2 presents a review of the
relevant literature on the entrepreneurial process, the challenges faced, the
knowledge-intensive entrepreneurship, the historical development of AI, and the challenges
associated with the utilization of AI. Chapter 3 outlines the research methodology, including
the survey design, data analysis, limitations, and interviews. Chapter 4 presents the results of
the survey and the interviews, while Chapter 5 provides an analysis of the findings. The
discussion of the findings both from the surveys and the interviews can be found in Chapter
6. Finally, Chapter 7 concludes the thesis by summarizing the key insights,, and suggesting
avenues for future research. Chapters 8 and 9 include the references and appendix;
respectively.
6
2. Literature Review
2.1 The Entrepreneurial Process
The opportunity marks the beginning of the venture, which then continues with
understanding who the customer is. From there, meticulous management takes place for the
customer creation and the building of the company.
The opportunity of a venture can be recognized, discovered, or created. An opportunity can
be recognized if the entrepreneur is able to exploit unrecognized market opportunities by
using market alertness and knowledge from social networks (Singh et al., 1999). Opportunity
discovery involves the entrepreneurs information and society’s information (Shane, 2000).
This means that the entrepreneur either knows the supply and looks for the demand, or vice
versa. Opportunity creation means that the entrepreneur is the creative force of supply and
demand, and exploits endogenous opportunities (Saxton et al., 2012). This initial phase is
often referred to as customer discovery, which involves comprehending the potential
customer base. Overall, entrepreneurs look for opportunities to deliver value to their
customers (Pryor et al., 2016). Moreover, it can be argued that the entrepreneurial process
shares similarities with the customer development process.
Subsequently, the viability of the customer segment must be assessed, leading to either
feasibility exploration or customer validation. Customer validation represents a deeper
understanding that there is indeed a market for the proposed idea (Blank & Dorf, 2012).
Moving forward, the company formulates its business blueprint, effectively establishing its
existence. The business blueprint can be interpreted as the customer journey map which
showcases the points of interaction and is considered the visual representation of a service
(Stickdorn & Schneider, 2011). Following this, the focus shifts to company building,
encompassing the execution and expansion of the organization.
These stages are characterized by intense efforts, such as identifying market gaps ripe for
innovation, distilling a viable company concept, articulating this vision into a solid strategy,
and eventually catapulting the venture into reality. The figure below illustrates the stages as
indicated from the earlier discussion.
7
Figure 2.1.2 The Process (Adopted from Blank & Dorf, 2012)
Therefore, the entrepreneurial process is characterized by its dynamic nature, as it progresses
through iterative loops that are nonlinear (Greene, 2020). This iterative approach is enriched
by feedback, which necessitates a continuous spectrum of evaluation and refinement. At the
heart of this journey lies not only the comprehension but also the embodiment of
entrepreneurial traits and competencies. These include the ability to recognize opportunities
that may be concealed in plain sight, as well as the skillful utilization of resources to convert
potential into tangible achievements (Treffinger, 1995). By embracing these qualities,
entrepreneurs can navigate the difficult path of entrepreneurship and steer their venture
towards success. Still, this process is not a uniform model, as entrepreneurs may employ
different cognitive strategies when making decisions.
2.1.1 Decision-making Models
Effectuation and causation are two distinct entrepreneurial decision-making models that
represent varying cognitive approaches (Sarasvathy, 2001). The causation approach involves
entrepreneurs setting a specific goal and then working towards achieving it by identifying the
necessary means. Those who follow a causal thinking pattern believe in the idea that they can
control the future if they can accurately predict it (Sarasvathy, 2001).
On the other hand, effectuation deviates from the causal logic by focusing on the available
means rather than a predetermined goal, then shaping these means into one or more goals that
were not necessarily predefined (Sarasvathy, 2001). Effectuation challenges conventional
business planning methods and encourages a different mindset. By integrating effectuation
and causation models through an offloading process, it becomes possible to elucidate the
connection between an entrepreneur's cognitive foundations and their subsequent actions.
2.2 Challenges Faced in The Entrepreneurial Process
During the entrepreneurial process, entrepreneurs must contend with the liabilities associated
with their newness and smallness. Both are risks for new businesses, which might limit their
ability to innovate and produce new ideas. The liability of newness relates to inherent
disadvantages new firms have when compared to incumbent organizations, such as having no
8
reputation, being vulnerable to capital, having costs and inefficiencies in production, and
being restricted by the lack of the needed resources (Stinchcombe, 1965). The disadvantage
of being small is having fewer resources than larger companies. To get beyond these
limitations, businesses can, nonetheless, build partnerships with a range of partners to go past
these liabilities. To increase productivity and profitability, for instance, owners of more
established small enterprises appear to concentrate on internal procedures. Furthermore, when
businesses mature, they accumulate much more resources, which might enhance business
performance when creatively merged. Furthermore, it has been demonstrated that a firm’s age
plays a significant role in defining its level of legitimacy, which improves the success of new
ventures.
2.2.1 The Case of Zappos
The online merchant Zappos, specializing in footwear and other merchandise, stands as a
brilliant example of a startup that has achieved both reputation and expansion. Founded in
1999 by Nick Swinmurn and Jerry Maguire, Zappos set out to create a hassle-free shopping
experience and foster a culture centered around the needs of its customers. Over time, Zappos
has solidified its reputation by delivering top-tier products, providing exceptional customer
service, and nurturing an extraordinary workplace environment (Frei et al., 2009). As a result
of its sterling credibility, Zappos has not only expanded its product offerings and
geographical reach but also forged significant partnerships with notable entities like Amazon
(Wikipedia contributors, 2024). Through the leveraging of its well-established
trustworthiness, Zappos has established itself as a stable and significant player in the internet
retail space.
2.3 Knowledge Intensive Entrepreneurship
Knowledge-intensive entrepreneurship is a specific type of entrepreneurship that thrives on
being innovative. It is characterized by a collaborative interaction between individuals who
possess knowledge. The success of these ventures is contingent upon their mission, meaning
the direction of the company, and the ability to adapt to the ever-changing external
environment. Knowledge-intensive entrepreneurship is not limited to specific industries but
rather can be found in a wide range of them, going beyond the boundaries of low-tech or
high-tech industries (McKelvey & Lassen, 2013).
Knowledge-intensive enterprises are composed of experienced individuals who possess the
capability to generate novel knowledge (Boland & Tenkasi, 1995). Consequently, knowledge
9
serves as their most crucial intangible asset, enabling them to thrive in information-driven
economies and achieve profitability (Demarest, 1997). However, this pursuit of success
presents a significant challenge, as these specialized individuals must possess diverse
knowledge in order to effectively compete and foster innovation (Tenkasi & Boland, 1996).
Furthermore, it is imperative for these firms to engage in continuous learning and ensure their
knowledge remains up to date.
Additionally, as mentioned by McKelvey and Lassen (2013), KIE firms ought to be nascent
blooms in time's vast garden, not more than eight years old. These firms must constantly push
the boundaries of knowledge, using it to create breakthrough products and services. Each
piece of wisdom should serve as a driving force, propelling these enterprises into uncharted
territories and enabling them to seize new opportunities (McKelvey & Lassen, 2013).
The categories of KIE firms, as outlined by McKelvey and Lassen (2013) include:
Corporate spin-offs:
In this type of spin-off, employees leave a large established company and they start their own
venture. This happens as there might be a business opportunity outside the scope of the large
established company, and the employees with the knowledge gained, leave and start a new
company. Many large companies created policies about this and some examples of them are
SAAB AB, Telia, and Siemens.
University spin-offs:
University spin-offs are established through the transfer of knowledge generated from
research activities within the academic institution. This knowledge, which encompasses
scientific and technical expertise, serves as the foundation for the development of new
enterprises. By leveraging the intellectual capital produced within the university setting,
spin-offs can capitalize on opportunities arising from technological advancements and
research findings.
Researchers and students within the university environment have the potential to initiate
knowledge-intensive enterprises (KIE. The university serves as a crucial hub for the
commercialization of cutting-edge technical and scientific knowledge, providing a fertile
ground for the creation of spin-off companies.
10
Independent start-ups:
In this scenario, the founder has gained experience and knowledge by working in a low-tech
or traditional industry, enabling them to turn an initial idea into a company.
2.3.1 How KIEs Operate
From Section 2.3 it can be realized that knowledge intensive enterprises have the input of
knowledge as the fundamental point for their creation and operation. In spite of that, they are
created and operate in a more complicated manner.
Figure 2.3.1 KIE Model (Adopted from McKelvey & Lassen, 2013)
The above figure highlights the complicated operation of the KIEs and presents the three
phases that take place during this process. These three phases have interacting variables and
all affect one another (McKelvey & Lassen, 2013).
Input:
This first phase is about how access is gained to resources and ideas. This phase is
challenging because it is difficult to get access to resources and these resources will influence
the development of the firm later on. It is basically the creation of the venture and four
aspects are related to it. These variables are: sources of knowledge inputs, characteristics and
traits of founders, financing, societal influences and public policy.
As mentioned earlier, the sources of knowledge inputs are the ones who impact the
development and the success of the venture. The other variable showcases that the knowledge
intensive entrepreneur differs in traits from the regular type of entrepreneur. Financing is
challenging and has effects on the venture. Societal influences also impact the venture as they
stimulate the development of knowledge intensive enterprises (McKelvey & Lassen, 2013).
Development:
11
The second phase relates to how these KIEs are managed and developed. The variables
within the second phase require interaction with internal and external processes as they result
in opportunities and are realized through business models. The four variables found here are
human resources, growth, network, and internationalization.
Human resources reflect those hired from the KIE, their knowledge, experience, and the
different challenges associated with their roles. The network reflects the social capital and
literature has shown that they are important for understanding how they impact the
performance of KIEs and the entrepreneurial process. The growth variable is challenging
because there needs to be a balance both on the research and development, and activities with
the market. The internationalization means that KIEs are not restricted since knowledge can
be created somewhere and applied in another geographical location (McKelvey & Lassen,
2013).
Output:
The final phase relates to the evaluation of the performance and the outputs. Once again,
there are four variables and those are new firm formation, growth performance, patents, and
knowledge creation.
New firms can be created as an outcome of development and the actual performance of the
KIE is growth. Growth can positively affect the creation of new jobs and improve
performance. Nevertheless, data collection about performance is difficult to obtain due to a
lack of accessibility and historical information. The third way of evaluation is the patents and
patents can be used as firm strategy for innovation and performance. The final variable here
is knowledge creation (McKelvey & Lassen, 2013).
2.4 Artificial Intelligence
The historical evolution of AI may be split into four major periods: AI's birth, golden era,
winter, and spring. AI was founded in the 1950s and 1960s by scholars such as Alan Turing,
John McCarthy, Marvin Minsky, and Claude Shannon, who developed the first AI systems
such as logic solvers, and natural language processors (Winston et al., 2012). The golden age
of AI occurred between the late 1960s and the late 1970s, when AI achieved extraordinary
breakthroughs like proving mathematical theorems, and playing expert-level games
(MCShane & Nirenburg, 2021). The AI winter occurred in the 1980s and 1990s, when AI
12
faced several obstacles, and a lack of common sense, but researchers began to lay the
intellectual and social foundation of AI in South Korea (Shin, 2022). Afterwards, the AI
spring began with major players such as the US, China, and the EU28 (Righi et al., 2022).
The AI spring continues to this day, as it is experiencing a resurgence due to the availability
of large amounts of data, and the development of new technologies.
Each phase of the evolution has influenced the entrepreneurial process differently, depending
on the availability and advancement of AI technologies and techniques. In this paper, the
focus is on the AI spring. It is argued that the AI spring has a significant impact on the
entrepreneurial process in knowledge-intensive firms, which are firms that rely heavily on the
creation, acquisition, and use of knowledge as a source of competitive advantage. AI enables
entrepreneurs to identify and exploit opportunities, make better decisions, improve
performance, and foster innovation (Mikalef & Gupta, 2021).
The emergence of AI technologies in business contexts has followed a similar path to the
overall evolution of AI, with significant exceptions. Businesses can adopt AI for a variety of
applications, but challenges are associated with its future impact (Dwivedi et al., 2019).
2.5 Benefits of AI
The use of artificial intelligence (AI) is influencing how businesses function today, having an
effect on internal operations and customer satisfaction. AI is a useful tool for businesses,
supporting both customer behavior analysis and competition analysis. In the words of
Taherdoost & Madanchian (2023), businesses are able to evaluate consumer feedback's
thoughts to learn more about market trends and preferences through the use of AI-powered
sentiment analysis. Nevertheless, companies need to evaluate the area where technological
adoption is needed while understanding both the advantages and disadvantages (Gupta &
Yang, 2024). For AI tools to be effectively used, they need human participation during the
process (Davenport & Euchner, 2022).
Campbell et al. (2020) provide an example of how AI uses data-driven precisely to enhance
marketing strategies and improve customer relationships. Apart from contributing to
increasing operational effectiveness, this strategic use of AI enables companies to deliver
engaging, individualized experiences to customers (Mondal et al., 2023).
13
Pokhrel & Banjade (2023) point out that AI turns into a proficient writer in the field of
content generation. Recurrent neural networks and Open AI language models have been
utilized with AI technologies to create engaging written material for consumers on a broad
spectrum of platforms.
Apart from that, AI tools can assist entrepreneurs in idea generation and business model
creation (Gupta & Yang, 2024). Meaning that, by leveraging AI tools, entrepreneurs can
come up with new and innovative ideas (Mondal et al., 2023). By AI tools such as Generative
AI, they can be assisted in understanding their processes since they are provided with a
description about the different stages (Feuerriegel et al., 2023).
The effect of AI is also being embraced by the educational sector. According to Chen et al.
(2022), students are beginning to gravitate toward AI-assisted presenting platforms, which
demonstrate the mutually beneficial link between AI and human intelligence while having the
potential to redefine learning experiences. This illustration is selected due to the potential for
students to transition into entrepreneurs through university and academic spin-offs.
2.6 Challenges Utilizing AI
There are several challenges that must be considered prior to its utilization. Firstly, the
adoption of AI involves significant costs, making it a financially demanding endeavor
(Keicher et al., 2022). This poses a barrier for new companies, particularly those that rely
heavily on knowledge-intensive operations, as they may struggle to allocate the necessary
resources for AI utilization. Secondly, the introduction of AI can potentially result in job
displacement, as certain tasks previously performed by humans may be automated (Nigmatov
& Pradeep, 2023). This raises concerns about the impact on employment and the need for
retraining or re-skilling of the workforce. Lastly, the field of AI in business is still relatively
new, necessitating the availability of experienced personnel who possess the skills to
effectively utilize AI technologies (Badhurrunisa & Dass, 2022).
14
3. Research Method
3.1 Research Strategy
In this research, the first chosen approach for investigating the impact that AI tools can have
in the entrepreneurial process was the quantitative approach.
The quantitative research strategy is the type of strategy which involves the collection of
numbers rather than words and exhibits the relationship between theory and research (Bell et
al., 2019). Useful data was collected through this type of approach and it presented the
challenges that are faced in the entrepreneurial process, the benefits that AI tools provide, and
the challenges that are associated with their utilization.
This type of research strategy was not linear since the development of the survey was based
on the literature and the literature was a dynamic body which constantly changed after
supervision feedback. Bell et al. (2019) have outlined the process of the quantitative approach
which makes it easier to understand that this research strategy is not linear.
3.2 Survey
3.2.1 Survey Preparation
For the survey it was crucial to discover a variety of AI tools and according to their usage to
be classified in categories. Thus, in this Section it will be presented which AI tools could
assist businesses in idea generation, customer experience improvement, and marketing
management; among others.
To begin with, Feedly AI is a tool that can be used to help companies gather resources, and
identify industry trends. It is a tool that understands a vast amount of market intelligence
concepts. Companies need to create an AI feed with a relevant AI model such as “product
launches” in order to track competitor strategies. This tool has assisted in filtering out the
noise for and capturing the important knowledge (Feedly, 2024).
Moving forward, Salesforce Einstein uses predictive and generative AI to increase
productivity. According to their website, Salesforce Einstein improves customers' experience,
and some of the companies that currently use this tool are Uber Eats, and Gucci (Salesforce,
2024).
15
Reaching ChatGPT, a widely known generative AI tool. It is developed by OpenAI and
trained to have a “conversation” with the person who is using it, and create content based on
users request. In this era of writing solutions lies also Anyword. Anyword uses data analytics
to predict the potential success of marketing content (Anyword, 2024).
Continuing with DALL-E 2 which is also developed by OpenAI. The difference with
ChatGPT is that DALL-E 2 creates realistic images from a written description. Another
similar tool is Midjourney. Midjourney has its own platform while DALL-E 2 is implemented
in ChatGPT. Both DALL-E 2 and Midjourney, can help in generating images and the
selection depends on user preferences. Apart from image generation, businesses can use
Synthesia for video creation. Synthesia takes away the need for equipment that is important
in creating videos and other time consuming activities, such as scripting, and training of
actors (Zapier, 2024).
Going on with Article Forge. Article Forge uses advanced AI and deep learning to write new
articles automatically. These articles are written in a way that the algorithms of Google can
easily evaluate, and rank them. A similar tool is INK. INK has helped the Founding Partner
and President of Ascend Hospitality Group to have better keywords from their competitors.
Also, it has helped grow traffic by 140% in a quarter for Quotapath (INK, 2024). Another
similar tool is GrowthBar which is powered by ChatGPT. GrowthBar is used as a marketing
advisor from companies such as DELLE, AllTrails, and Codeless (GrowthBar, 2024).
Nevertheless, creating content for blog posts and updating among different social media
platforms can take time. For that reason, there are AI tools which assist in managing and
scheduling the social media marketing. These tools are Social bee, Flick, and Feedhive.
Based on what was previously mentioned, AI tools can be used for:
● competitor analysis and consumer behavior
● productivity and customer experience
● written content generation
● image generation
● video generation
● presentations
● automate business processes
16
● search engine optimization
● marketing management
Now regarding the entrepreneurial process, and the challenges associated with it, the AI tools
could help overcome the challenges of:
● coming up with new ideas
● lack of reputation
In summary, the survey developed as part of this research aimed to test the potential of these
AI tools in empowering entrepreneurs throughout the entrepreneurial lifecycle.
3.2.2 Survey Structure and Content
The survey was divided into several sections to gather comprehensive data from the
respondents. The initial section requested respondents to provide information about their
firm, including the company name, the respondent's position, the industry in which the firm
operated, the number of years the firm had been in operation, and the current number of
employees.
The second section of the survey focused on the entrepreneurial challenges encountered by
the KIE firms. It also inquired about the respondents' familiarity with AI tools, the tools
utilized during their entrepreneurial journey, and the tools currently being used.
The third section aimed to determine which of these tools specifically aided in idea
generation, feasibility exploration, business blueprint development, execution, and expansion.
Lastly, the survey investigated the benefits of employing AI tools, and the challenges
associated with their utilization, such as potential job displacement, and presented
recommendations from the respondents for those interested in utilizing AI.
3.2.3 Survey Sample and Limitations
The survey instrument was developed, drawing on insights from the existing literature and
input from subject matter experts. Once the survey was finalized, it was distributed to a
targeted sample of KIEs on a daily basis over a period of 4 weeks.
The targeted sample consisted of two types of knowledge-intensive enterprises. The first
sample was university spin-offs found from both GU and Chalmers ventures. From both
17
ventures, 92 were sent an email for participating in the survey. The second sample was
independent start-ups found from the website called the European AI Startup Landscape.
From that website, all the companies that had contact details on their website and matched the
criteria from McKelvey and Lassen (2013) were sent an email. From the second sample, 158
companies were reached out. The survey link, along with the accompanying emails, can be
found in Appendix 9.
Even though the survey was distributed to a total of 250 potential respondents, only 8
responses were collected, representing a response rate of 3,2 %.
The survey respondents will be presented in the table below. Due to confidentiality reasons,
the identity of the individual completing the survey and the company involved will not be
disclosed. Instead, the industry in which the company operates will be provided, the role of
the survey respondent, and the type of KIE.
Company Industry Role of respondent Type of KIE
A Chemistry Co-Founder and University spin-off
COO
B AI/Data CEO Independent start-up
C Marketing Analytics Lead Developer University spin-off
D Agricultural CEO Independent start-up
Technology
E Healthcare CEO Independent start-up
G Electric Power CEO Independent start-up
Generation
I Startup, Deeptech, CEO Independent start-up
Computer
Engineering
S Healthcare Application Independent start-up
Developer
18
While the survey responses provided valuable insights, the relatively low response rate may
limit the generalizability of the findings. Potential reasons for the limited response rate, such
as survey fatigue or lack of incentives, should be considered when interpreting the results.
The survey link, along with the accompanying emails, can be found in Appendix 9.
3.4 Interviews
Due to the lack of survey responses, a second method was selected, which was the qualitative
approach. This decision resulted in a combination of two distinct methods, namely qualitative
and quantitative. While the quantitative method focuses on numerical data and statistical
analysis, the qualitative approach emphasizes the importance of words and narratives
(Bryman & Bell, 2011). By utilizing both methods, a comprehensive dataset was gathered to
enhance the research findings.
3.4.1 Interview Design
The interviews were designed to be semi-structured, allowing for flexibility while ensuring
that key topics were addressed. An interview guide was prepared to assist in interpreting the
results, ensuring consistency and reliability in the collected data.
3.4.2 Interview Structure and Content
The interview guide consisted of three sections and can be found in Appendix 9.5. The first
section from questions one to three, aimed to digest the role of the interviewee, the role that
the interviewee had in the company, and if the interviewee was the entrepreneur to present
some challenges that were faced in the entrepreneurial journey.
The second section from questions four to seven aimed to identify how aware the interviewee
was with AI tools, what AI tools were used, what was the reason for using them, and what
benefits were experienced.
The final section which included two questions, question eight and nine, focused on the
negative outcomes of the utilization of AI tools, and recommendations that the interviewees
had future entrepreneurs or professionals.
3.4.3 Interview Sample and Limitations
The interviewees were primarily entrepreneurs or founders of knowledge-intensive
enterprises that focused on creating value and have been established for no longer than eight
19
years. The selection criteria did not consider factors such as internationalization and growth
performance, as some companies might be relatively new. It was assumed that interviewees
encountered unique obstacles within their enterprise and utilized a variety of AI tools.
While the primary emphasis was on entrepreneurs or founders, an exception arose in the form
of the product manager from Company L. This deviation occurred due to his close
relationship with the founder and his understanding of the challenges encountered in the
entrepreneurial journey, which contributed to the research.
During the interviews, participants had the opportunity to deviate from the primary subject
and introduce points they considered important to the conversation.
The interviews took place in a hub where entrepreneurs and aspiring business owners seek
guidance and support to navigate challenges. The interviews were also facilitated by the
University of Gothenburg's close relationship with this specific location, enabling a smooth
process of data collection and ensuring that the research objectives were effectively met.
During the final week of April and the initial week of May, a total of three interviews were
conducted. The table below showcases the three different interviewees, including the
company, the role, and the type of KIE.
Company Role of interviewee Type of KIE
L Product Manager Independent start-up
M CEO Independent start-up
N CEO Independent start-up
(soon to be founded)
It is worth noting that the interviews were conducted in the work environment of the
interviewees, which may have led to time limitations. However, valuable insights were
obtained despite this constraint.
3.5 Summary of Research Method
The research employed a mixed-methods approach, combining both quantitative and
qualitative methods to gather a comprehensive dataset and enhance the research findings.
20
Initially, a quantitative survey was designed and distributed to 250 knowledge-intensive
enterprises (KIEs), such as independent start-ups, university, and academic spin-offs, as
outlined by McKelvey and Lassen (2013). The survey aimed to examine the challenges faced
by KIEs, the benefits of using AI tools, and the challenges associated with their utilization.
However, the survey received a low response rate of 3.2%, with only 8 responses collected,
limiting the generalizability of the findings.
Due to the lack of responses from the survey, a qualitative approach was adopted through
semi-structured interviews. The interviews were conducted at a hub where entrepreneurs and
professionals seek guidance and support, facilitated by the University of Gothenburg's close
relationship with this location.
The interviewees were primarily entrepreneurs or founders of businesses that focus on
creating value and have been established for no longer than eight years. An exception was
made for the product manager from Company L due to their close relationship with the
founder and understanding of the entrepreneurial challenges. During the interviews,
participants had the opportunity to deviate from the primary subject and introduce points they
considered important.
In total, three interviews were conducted during the final week of April and the initial week
of May. The interviews were conducted in the work environment of the entrepreneurs.
21
4. Results
4.1 Survey
4.1.1 Co-Founder and COO, Company A
A significant issue regarding the reusability of colored fabrics was identified by a researcher
from Chalmers University in 2015, leading to the establishment of an academic spin-off
company in 2020. This company directly resulted from the problem identified, demonstrating
the practical application of academic research in addressing real-world challenges.
During the early stages of the company, the Co-Founder and COO highlighted several
challenges they faced, including the scarcity of resources in terms of human and financial
capital. Overcoming the limited availability of skilled personnel and necessary funds was
crucial to moving the company forward.
The Co-Founder and COO emphasized the use of a single AI tool, ChatGPT, for their
entrepreneurial endeavors. This tool played a key role in various aspects of their operations,
such as generating written content, conducting competitor analysis, and gaining insights into
consumer behavior. The Co-Founder and COO noted that one challenge of using this AI tool
was the difficulty in fact-checking the information it produced, underscoring the importance
of ensuring reliability in the outputs.
4.1.2 CEO, Company B
This company was founded in 2020 and the purpose of its creation was the transformation of
data to useful knowledge. The challenges that were encountered from this company were lack
of resources, lack of human capital, lack of financial capital, and lack of reputation.
The CEO used three AI tools for his entrepreneurial journey which continues to this day and
these were ChatGPT, DALL-E 2, and Synthesia. Additionally, the CEO leveraged the
capabilities of Canva to expand his audience and establish a reputable presence in the market.
The utilization of these AI tools brought forth numerous advantages, including productivity
and customer experience, written content generation, presentation creation, and marketing
management.
22
The recommendations that he had for new entrepreneurs that want to use AI in their ventures
was to “filter and use the ones that create real value for you and your customers”.
4.1.3 Lead Developer, Company C
Two studies were conducted to justify the establishment of this company. The primary
objective of these studies was to gain insights into the influence of marketing in the Swedish
academic landscape in 2015. The company sought to evaluate the effectiveness of advertising
through a collaborative effort with Stanford University in 2018. Over time, these studies
gradually evolved and resulted in the development of a marketing analytics platform tailored
for the Swedish market, which was launched in 2022.
One of the key challenges faced by the company was the scarcity of human resources as
selected by the lead developer. The lead developer utilized artificial intelligence tools,
specifically ChatGPT, DALL-E 2, and Midjourney. By leveraging these AI tools, the benefits
included idea generation, written content creation, productivity, and customer experience.
4.1.4 CEO, Company D
During an entrepreneurship course in a greenhouse, two engineers saw an opportunity to
apply their passion and solve greenhouse problems. One of them is now the CEO and when
asked about entrepreneurial challenges, he wrote that the challenge was the product market fit
and the rollercoaster of startup fundraising, with the second one being connected with the
lack of financial capital.
He used only one AI tool and this was ChatGPT which assisted him in idea generation,
presentation creation, productivity and customer experience. He mentioned that he imagines
that the opportunities of AI tools are endless. At the moment he used ChatGPT or Bard for
making contents in presentations, business plans or customer proposals more concise and
clear.
4.1.5 CEO, Company E
The establishment of this company aimed to enhance the well-being of individuals through
innovative solutions. Founded in 2020, it brought together a diverse group of experts
specializing in AI, the realm of breast cancer and beyond.
The entrepreneurial challenges as selected from the CEO were the lack of resources and the
lack of financial capital. The CEO used AI tools such as ChatGPT and currently does inhouse
23
machine learning development with PhD engineers. The benefits from ChatGPT utilization
are competitor analysis and consumer behavior, productivity and customer experience,
written content generation, and marketing management.
4.1.6 CEO, Company G
Founded in 2022, the company had the primary objective of minimizing the expenses
associated with electricity for its customers.
The CEO faced the challenge of financial capital during his entrepreneurial journey and used
ChatGPT for competitor analysis and consumer behavior, and the automation of business
processes. A challenge for AI tools utilization was claimed to be the need for specialized
skills, and his recommendations for new entrepreneurs were to avoid AI tools and stick to
traditional solutions.
4.1.7 CEO, Company I
Established in 2020, this organization's CEO encountered obstacles including a deficiency in
reputation, resources, human capital, and financial capital.
Utilizing ChatGPT for written content creation and image generation, the CEO acknowledged
the drawbacks of AI tools, citing concerns about the potential for low-quality results. He also
emphasized that AI should be viewed as a tool similarly to Google Search.
4.1.8 Application Developer, Company S
This company was founded in 2018 for creating devices that store medical information. The
company lacked human and financial capital during its journey.
The benefits from utilizing ChatGPT were the generation of written content, images, videos,
the creation of presentations and search engine optimization. Some of the negative aspects
utilizing AI tools were high initial costs, and need for specialized skills. She recommended
for new entrepreneurs to identify where the solution is needed as it can be used in multiple
stages including customer service enhancement. Also, she recommended to always update the
AI strategy for aligning with your business and that the AI tools are not a “one-size-fits-all”
solution.
4.2 Summary of Survey Results
The results obtained from the survey are summarized Tables 4.1 - 4.5.
24
Table 4.1 Challenges during the entrepreneurial process
The presented table below showcases the challenges encountered in the entrepreneurial
process as reported by various survey respondents. All respondents were given the chance to
highlight any additional challenges, which are denoted by an asterisk (*).
Challenges/ A B C D E G I S
Company
*Product X
market fit and
managing the
rollercoaster
of startup
fundraising
Lack of X X X X
resources
Lack of human X X X X X
capital
Lack of X X X X X X X
financial
capital
Lack of X X
reputation
Table 4.2 AI tools used
The table below presents the AI tools used among the survey respondents.
Company AI tools used
A ChatGPT
B ChatGPT, DALL-E 2, Synthesia, and Canva
C ChatGPT, DALL-E 2, and Midjourney
D ChatGPT & Bard
E ChatGPT
G ChatGPT
I ChatGPT
S ChatGPT
25
Table 4.3 Benefits from using AI tools
Below the benefits of using AI tools among different survey respondents are presented. Some
benefits can be seen on only one respondent and the majority of them apply more than once.
Benefits/ A B C D E G I S
Company
Competitor X X X X
analysis and
consumer
behavior
Written X X X X X X
content
generation
Productivity X X X X
and customer
experience
Presentations X X X
Marketing X X
management
Automate X
business
processes
Video X
generation
Search engine X
optimization
Image X X
generation
Grow X
audience
Table 4.4 Challenges Utilizing AI tools
This table highlights the difficulties encountered while utilizing AI tools among various
survey participants. All respondents were given the chance to express any additional
challenges they faced, which are denoted by an asterisk (*). Interestingly, half of the
respondents reported no challenges whatsoever.
Challenges/ A B C D E G I S
Company
26
*Difficult to X
fact check
*Low quality X
outcome
Need for X X
specialized
skills
High initial X
costs
Potential job
displacement
Table 4.5 Recommendations for new entrepreneurs
The below table showcases the recommendations that the survey respondents had for new
entrepreneurs who want to use AI in their ventures.
Company Recommendation
B “Filter and use the AI tools that create value
for you and your customers.”
D “It is too early to recommend something and
I can imagine the opportunities are endless.
We currently use ChatGPT or Bard to make
content of presentations, business plans or
customer proposals more concise and clear.
It is really good at summarizing and
structuring content.”
G “Avoid as much as possible, most problems
can be solved with traditional ways.”
I “AI is just a tool, in the same way as Google
Search is a tool.”
S “Identify where you want to use it as it can
be used in multiple stages of data analysis,
automation, and customer service
enhancement. You must update your AI
strategy continuously to align with your
business goals and capabilities since it is not
a “one-size-fits-all” solution.”
4.3 Interviews
27
4.3.1 Product Manager, Company L
The product manager of Company L works in a company that has a mission in creating a
positive impact to the environment with sustainable products and services. The company was
founded back in 2020 and wants to create a community for sharing knowledge, fostering
connections, and inspiring positive change.
Even though he is not the CEO of Company L, he knows the entrepreneurial challenges. One
challenge was related to hiring talented individuals who shared their vision. The company
tried to hire students due to lack of human capital, from the University of Gothenburg and the
tax was a boundary since it was significantly high. Also, operating across EU member states
presented hurdles. There is a lack of streamlined processes for hiring talents across borders
and the European Commision reaction in this area needs improvement.
In his professional endeavors, he relies on two AI tools, ChatGPT and DALL-E 2, which
prove to be invaluable in generating images for marketing activities. The utilization of these
tools can present a challenge in striking the right balance between fostering innovation and
ensuring financial viability.
As advice for entrepreneurs looking to incorporate AI tools in their ventures he mentioned to
not adopt AI just for the sake of it. There should be an identification where it truly adds
value, for example, driving insights. He also mentioned that the field evolves rapidly and
continuing learning is essential.
4.3.2 CEO, Company M
In 2021, the CEO of Company M established a non-profit organization dedicated to creating
websites alongside his team. During the winter of 2023 he desired to transition into a
profitable venture while continuing to build more websites. Despite the organization's
primary focus on knowledge-sharing for sustainability-related issues, the CEO recognized the
need to generate revenue and expand its reach. The existing website already gained a
substantial daily traffic of seven thousand views, indicating its potential for growth and
impact.
One of the significant challenges the CEO encountered in his entrepreneurial journey was
effectively reaching out to customers and driving sales. Fortunately, his prior credibility
28
within the industry mitigated concerns about his organization's reputation. Nonetheless, the
transition from a non-profit model to a profit-oriented approach posed a considerable hurdle.
When questioned about his utilization of AI tools, the CEO revealed that he initially
employed them for assistance in developing the business model. Presently, he selectively
employs AI tools during specific periods to explore uncharted territories. Among the AI tools
he utilizes are ChatGPT and Perplexity, which he regards as valuable sounding boards. The
rationale behind their usage lies in their ability to generate diverse responses when prompted,
allowing intelligent individuals to interpret and analyze the outcomes. The CEO found these
AI tools beneficial not only for business model development but also for organizing
information into categories. Furthermore, they can assist in generating text, facilitate
translation, and aid in the writing process.
The Chief Executive Officer of Company M faced two primary obstacles in utilizing AI
tools. One issue involved the AI tools occasionally generating nonsensical text, necessitating
additional time to clean up the text. The second challenge revolved around determining the
most effective way to interact with the tools, specifically identifying the appropriate prompt
to yield the desired outcome. As a result, the CEO recommended careful consideration of
how to effectively utilize and prompt these AI tools to achieve the desired results.
4.3.3 CEO, Company N
The Chief Executive Officer at Company N is a proficient communicator and also works as a
freelancer. Since she has not started her own company yet, she has been learning and gaining
experience from the CEO of Company M. As a result, her current entrepreneurial journey is
centered around generating ideas, and she is not currently encountering any entrepreneurial
obstacles.
In her entrepreneurial journey, she utilizes two artificial intelligence tools, namely ChatGPT
and Adobe AI. These tools play a crucial role by enabling her to transform text into visual
content and providing her with textual information. By leveraging these AI tools, she is able
to address various questions and concerns that she may have, a practice that she notes is
common among many individuals using these AI tools.
29
Despite her reliance on AI tools in her work, she experiences no notable challenges while
using them and finds the process enjoyable. Besides, she offers a valuable piece of advice to
those considering the use of AI tools, emphasizing that specialized knowledge is not a
prerequisite for their effective utilization. This insight suggests that individuals from diverse
backgrounds and expertise levels can benefit from incorporating AI tools into their
professional activities, underscoring the accessibility and user-friendly nature of such tools.
4.4 Summary of Interview Results
The results obtained from the interviews are summarized in Tables 4.6 - 4.10.
Table 4.6 Challenges during the entrepreneurial process
The presented table below showcases the challenges encountered in the entrepreneurial
process as reported by the interviewees.
Company Entrepreneurial Challenges
L Hiring talents across the borders/
lack of human capital
M Reaching out to customers and business
model development
N None
Table 4.7 AI tools used
The table below presents the AI tools used among the survey interviewees.
Company AI tools used
L ChatGPT & DALL-E 2
M ChatGPT & Perplexity
N ChatGPT & Adobe AI
Table 4.8 Benefits from using AI tools
Below the benefits of using AI tools among different interviewees are presented.
30
Company Benefits
L Marketing activities and image generation
M Business model creation and written content
generation
N Written content generation and image
generation
Table 4.9 Challenges Utilizing AI tools
This table highlights the difficulties encountered while utilizing AI tools among various
survey participants.
Company Challenges
L Balancing between innovation and financial
viability
M Cleaning up the nonsensical generated text
and finding the appropriate prompt
N None
Table 4.10 Recommendations for new entrepreneurs
The table below showcases the recommendations that the interviewees had for new
entrepreneurs who want to use AI in their ventures.
Company Recommendations
L Identify the area that it adds value
M Use the appropriate prompt for the desired
result
N Experience with AI tools
31
5. Analysis
5.1 Analysis of Survey
5.1.1 AI tools used
From Table 4.2 it can be realized that all of the survey respondents were using ChatGPT.
Only one company was using Bard apart from ChatGPT, and two companies, namely
Company C, and Company B, were using three and four AI tools.
5.1.2 Benefits from using AI tools
During the survey development, various tools were discovered and they were categorized that
they can be used for:
● competitor analysis and consumer behavior
● productivity and customer experience
● written content generation
● image generation
● video generation
● presentations
● automate business processes
● search engine optimization
● marketing management
Competitor analysis and consumer behavior
Taherdoost and Madanchian (2023) state that organizations can enhance their understanding
of customer feedback and predict future preferences, as emphasized by the survey
participants. Furthermore, Company A, D, E, and G recognized competitor analysis and
consumer behavior as significant advantages resulting from the use of AI tools.
Productivity and customer experience
As per Campbell et al. (2020), artificial intelligence has the potential to enhance a company's
marketing approach and bolster customer connections, leading to improved operational
effectiveness and tailored customer interactions. Companies B, C, and E all saw a boost in
productivity and enhanced customer experience as a consequence of using AI tools.
Company S recommended this as an area that could be improved by using AI tools.
Content generation
In the 2023 research conducted by Pokhrel and Banjade, the effectiveness of artificial
intelligence in generating content is emphasized. From the survey findings, respondents from
companies A, B, C, and E viewed the written content creation as advantageous. The survey
32
respondent from Company S viewed not only written content generation but also video and
image generation.
Presentations
Chen et al. (2022) revealed that the integration of AI technology in the educational field for
presentation development is on the rise. This phenomenon is not confined to education alone,
as up-and-coming entrepreneurs are also realizing the benefits of leveraging AI tools.
Notably, the CEOs of Company B and Company D, and the Application developer of
Company S have highlighted presentations as an outcome of utilizing AI tools.
Automate business processes
Only one respondent selected that a benefit experienced by using AI tools was the automation
of business processes. This respondent was the CEO of Company G.
Marketing management
The CEO of Company B, and the CEO of Company D experienced a more efficient
marketing management by using AI tools.
Grow audience
Company B encountered the challenge of lack of reputation during his entrepreneurial
journey. In order to overcome this challenge he utilized Canva and expanded his audience
while simultaneously establishing his company’s presence.
5.1.3 Challenges Utilizing AI
High initial costs
According to the research conducted by Keithcer et al. (2022), it was demonstrated that the
integration of AI into various processes requires a substantial financial investment. The
results obtained from the survey indicated that only company S perceived the adoption of AI
as an activity that entails considerable expenses.
Potential job displacement
The research conducted by Nigmatov and Pradeep (2023) suggested that the introduction of
AI could lead to the automation of specific human tasks, potentially resulting in job
displacement. Even so, the survey results indicated that none of the participants viewed this
as a barrier to the utilization of AI.
Need for specialized skills
33
The study by Badhurrunisa and Dass (2022) highlighted the importance of having skilled
personnel for the successful integration of AI technologies. Interestingly, only the CEO of
Company G and the Application developer of Company S, acknowledged this potential
challenge in effectively utilizing AI, among all the survey respondents.
Additional challenges
The opportunity was given to all survey participants to discuss a potential challenge they
believed could hinder the utilization of AI. The Co-founder and CEO of Company A, and the
CEO of Company I seized this chance and highlighted the challenge of fact checking, and
low quality outcome; respectively. Given that numerous AI tools are generative in nature, fact
checking may pose a complex task, and the quality can be questionable.
5.2 Analysis of Interviews
5.2.1 AI tools used
From Table 4.7 it can be observed that all of the companies were using two AI tools. The one
tool that was used by all the three companies was ChatGPT. The second tool varied from
each interviewee with that being DALL-E 2, Perplexity, and Adobe AI for Company L, M,
and N; respectively.
5.2.2 Benefits from using AI tools
The benefits for each interviewee were different.
The Product Manager at Company L effectively utilized two AI tools, ChatGPT and DALL-E
2, to generate images for marketing purposes. These tools proved to be invaluable in
enhancing the marketing activities of the company.
The CEO of Company M relied on AI tools, ChatGPT and Perplexity, to support various
aspects of business development. These tools served as valuable sounding boards for the
CEO, aiding in the refinement of the business model and organization of information. The
CEO recognized the importance of AI tools not only in generating text but also in facilitating
translation and enhancing the writing process.
The entrepreneur at Company N incorporated AI tools, ChatGPT and Adobe AI, into her
entrepreneurial journey to enhance her creative processes. These tools enabled her to
transform text into visual content and access textual information efficiently.
34
5.2.3 Challenges Utilizing AI
From the Product Manager of Company L, the utilization of the tools that he used could
present a challenge in striking the right balance between fostering innovation and ensuring
financial viability. This indicates that a challenge for utilizing it could be the involvement of
cost.
The CEO of Company M realized that AI tools such as ChatGPT can create nonsensical text
leading to additional time spent cleaning up the text. Apart from that, he presented the need
of identifying the appropriate prompt to have the desired outcome. This creates the need for
having some experience for effectively using AI tools.
On the contrary, the CEO of Company N did experience challenges when using AI tools and
she suggested experience with it while she believed that AI tools are accessible and can be
easily used.
35
6. Discussion
This section will address the research question by presenting the outcomes derived from two
different methodologies. The first method involved the survey data, while the second
encompassed the insights gained from the interviews.
From the survey results presented in Section 4.1 and summarized in Section 4.2, it was
evident that the majority of companies rely on a single AI tool, with a few exceptions such as
Company G, C, and B, which utilize two, three, and four AI tools, respectively. This
suggested that many companies are not fully leveraging the range of AI tools available.
Table 4.1 provided insights into entrepreneurial challenges, which were consistent with the
existing literature on the subject. Among the challenges listed, the least encountered was the
lack of reputation, as indicated by two companies, while the most prevalent challenge was
identified as the lack of financial capital.
Upon examination of Table 4.3, it became apparent that companies derive various benefits
from the utilization of AI tools. The most commonly reported benefit was written content
generation, while video generation appeared to be the least prevalent among the benefits
observed. Furthermore, the data in Table 4.3 highlighted that different companies have
experienced a range of anticipated benefits, including but not limited to video generation,
search engine optimization, image generation, automation of business processes, marketing
management, presentations, productivity, and consumer experience, content generation, as
well as competitor analysis and consumer behavior.
The challenges associated with the utilization of AI tools were examined in Table 4.4,
revealing varying experiences among different companies. While four companies reported no
challenges, Company G and Company S encountered common obstacles such as the
requirement for specialized skills. Furthermore, when asked to identify a significant
challenge, Company A highlighted the difficulty in fact checking, whereas Company I
pointed out the issue of low quality outcomes.
Table 4.5 presented the suggestions given by the survey participants to aspiring entrepreneurs
who wish to use AI tools in their ventures. While one recommendation advised against their
36
usage and advocated for sticking to traditional methods, the majority of the suggestions were
positive. These suggestions emphasized the importance of comprehending the specific area
where AI tools are required and highlighted their potential in areas such as business planning
and customer enhancement. The interviewees also expressed a favorable attitude towards
recommendations, suggesting the exploration of AI tools and emphasizing the importance of
selecting appropriate prompts to achieve the intended results.
The interview findings presented in Section 4.3 reaffirmed the notion that many companies
were not fully utilizing the range of AI tools. Most companies limited their usage to a
maximum of two tools.
The interviewees had different opinions when asked about the challenges faced by
entrepreneurs. One interviewee highlighted the hiring process in Sweden as a major obstacle
for entrepreneurs seeking talented individuals from renowned universities such as the
University of Gothenburg. On the other hand, the CEO of Company L identified reaching out
to customers as a significant entrepreneurial challenge that he encountered.
In terms of the advantages derived from utilizing AI tools, the interviewees expressed varying
perspectives. The product manager of Company L utilized AI to generate images that assisted
in marketing activities. Meanwhile, the CEO of Company M relied on AI for tasks such as
aiding the writing process, translation, and comprehending the business model, enabling him
to develop it according to his preferences. Additionally, the CEO of Company N employed
AI for written content and transforming text into visual representations.
The findings of the study indicated that new entrepreneurs derived a range of benefits from
utilizing AI tools, however, most of which did not contribute positively to the entrepreneurial
challenges. It is important to note that this study had a limitation in terms of survey
responses, which necessitated conducting interviews to complement the survey findings and
existing literature.
By combining the two methods, it can be realized that the four most experienced
entrepreneurial challenges were the lack of financial capital, human capital, resources, and
reputation. This was something that was expected as these challenges are faced when an
enterprise is new and small, as discussed by Stinchcombe (1965). The least experienced
37
challenges were product market fit, business model development, and customer reach out.
Based on these entrepreneurial challenges, financial capital was a hurdle for seven
companies, specifically A, B, D, E, G, I, and S. Similarly, human capital posed a challenge
for six companies: A, B, C, I, S, and L. The constraint of resources was encountered by four
companies: A, B, E, and I, while reputation issues were faced by two: B and I. Product
market fit was a unique challenge to company D. Company M alone experienced difficulties
with business model development and customer outreach.
In the discussion of benefits, written content generation proved to be advantageous for eight
companies: A, B, C, E, I, S, M, and N. Competitor analysis and consumer behavior analysis
were beneficial for four companies: A, D, E, and G. Productivity enhancement and improved
customer experience were key factors for four companies: B, C, E, and S. Three companies,
namely B, D, and S, made use of AI tools for presentations. AI tools were also utilized for
marketing management by three companies: B, E, and L. Companies I, S, and L employed AI
tools for image generation. Search engine optimization and video generation was achieved by
company S exclusively. Company G integrated automation into their business processes.
Company L utilized AI tools to address challenges in business model development, while
company B focused on expanding their audience through AI tools.
From the sections 5.1.3 and 5.2.3, different concerns and considerations can be observed.
Potential job displacement did not emerge as a barrier for the companies even though it was
raised by Nigmatov and Pradeep (2003). High initial costs were acknowledged only by
company S. From the perspective of Company L’s Product Manager, the challenge lies in
balancing innovation with financial viability, echoing the cost-related concerns. Meanwhile,
Company M’s CEO pointed out the difficulties in prompt identification and text refinement
when using AI tools like ChatGPT, indicating a need for experience in effective AI tool
usage. The need for specialized skills was highlighted by two companies: G and S. Additional
challenges such as fact-checking and quality outcomes were mentioned by two companies: A
and I. Contrastingly, the CEO of Company N found AI tools to be accessible and
user-friendly.
38
7. Conclusion
The literature addressed in this thesis highlighted the challenges in the entrepreneurial
process, the benefits of using AI tools, and the challenges for their utilization.
Lessons learned from the research revealed that these advantages apply to the business world.
On top of that, the study clarified the difficulties that arise while starting a business which
were aligned with Stinchcombe (1965). Apart from the challenges presented by
Stinchhcombe (1965), knowledge-intensive enterprises faced difficulties in reaching out to
customers and developing the business model. No significant connection was discovered
between the entrepreneurial challenges and the benefits of AI tools. This outcome
demonstrated a low level of awareness from entrepreneurs and professionals since the
majority used AI tools for benefits that do not help overcome the challenges that their
enterprise faced. Only one survey respondent and one interviewee used AI tools for
overcoming a challenge of their enterprise, and these were from Company B and Company
M.
Almost all survey respondents acknowledged written content generation as a major benefit
for utilizing AI tools. Added to that, the benefits mentioned by the survey participants aligned
with the information that was presented in the existing literature. The interviewees had
similar benefits with only one interviewee experiencing the benefit of business model
creation.
Undoubtedly, there were challenges associated with the utilization of AI tools. Nevertheless,
these challenges were slightly different from the expected ones, which were: high initial costs
(Keicher et al., 2022), potential job displacement (Nigmatov & Pradeep, 2023), and need for
specialized skills (Badhurrunisa & Dass, 2022). Only two enterprises from the eight that
responded to the survey, selected the need for specialized skills and high initial costs. The rest
of the survey respondents and the interviews, showcased that a struggle came when the
desired result was not reached or when nonsensical text was generated.
7.1 Recommendations for future research
The present research has demonstrated that the knowledge-intensive enterprises who were
represented by the survey respondents and the interviewees, were not fully utilizing the array
39
of artificial intelligence tools that could potentially enhance their processes, and assist them
in overcoming challenges. To expand on these findings, it would be advantageous to explore
the realm of corporate spin-offs in future investigations, as the current study solely focused
on independent start-ups and spin-offs originating from universities and academic
institutions.
Overall, the outcomes of this study emphasized the importance of comprehending the unique
hurdles and opportunities faced by independent start-ups and academic spin-offs.
Further research in this domain has the potential to provide valuable insights for
entrepreneurs and professionals aiming to navigate the intricate landscape of
knowledge-intensive entrepreneurship and capitalize on the opportunities.
7.2 Recommendations for new entrepreneurs
The survey results mainly included favorable suggestions, emphasizing the importance of
identifying the areas where AI tools can be most effectively used. Despite the
overwhelmingly positive feedback, there was one negative opinion urging against the use of
AI tools altogether.
All interviewees shared positive feedback as well, highlighting the importance of delving into
the possibilities of AI tools and identifying the right prompts to achieve desired outcomes.
This consensus underscores the value of trial and error when utilizing AI tools.
40
8. References
8.1 From Articles
Antonelli, C., & Fassio, C. (2014). The Economics Of The Light Economy. Globalization, Skill
Biased Technological Change And Slow Growth. Technological Forecasting and Social Change, 87,
89-107. https://doi.org/10.1016/J.TECHFORE.2013.11.006.
Badhurunnisa, M., & Dass, V. (2023). Challenges and Opportunities Involved in Implementing AI in
Workplace. International Journal For Multidisciplinary Research.
https://doi.org/10.36948/ijfmr.2023.v05i06.10001.
Bell, E., Bryman, A., & Harley, B. (2019). Business research methods (5th edition). Oxford
University Press.
Blank, S., & Dorf, B. (2012). The Startup Owner’s Manual: The Step-by-Step Guide for Building a
Great Company. K&S Ranch, Inc.
Boland, R., & Tenkasi, R. (1995). Perspective Making and Perspective Taking in Communities of
Knowing. Organization Science, 6, 350-372. https://doi.org/10.1287/ORSC.6.4.350.
Campbell, C., Sands, S., Ferraro, C., Tsao, H., & Mavrommatis, A. (2020). From data to action: How
marketers can leverage AI. Business Horizons. https://doi.org/10.1016/j.bushor.2019.12.002.
Chen, J., Lai, P., Chan, A., Man, V., & Chan, C. (2022). AI-Assisted Enhancement of Student
Presentation Skills: Challenges and Opportunities. Sustainability. https://doi.org/10.3390/su15010196.
Cooper, A., & Schendel, D. (1976). Strategic responses to technological threats. Business Horizons,
19, 61-69. https://doi.org/10.1016/0007-6813(76)90024-0.
Davenport, T., & Euchner, J. (2022). The Rise of Human-Machine Collaboration.
Research-Technology Management, 66, 11 - 15.
Demarest, M. (1997). Understanding knowledge management. Long Range Planning, 30, 374-384.
https://doi.org/10.1016/S0024-6301(97)00017-4.
Dwivedi, Y., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R.,
Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P., Janssen, M., Jones, P., Kar, A., Kizgin, H.,
Kronemann, B., Lal, B., Lucini, B., Medaglia, R., Meunier-FitzHugh, K., Meunier-FitzHugh, L.,
Misra, S., Mogaji, E., Sharma, S., Singh, J., Raghavan, V., Raman, R., Rana, N., Samothrakis, S.,
Spencer, J., Tamilmani, K., Tubadji, A., Walton, P., & Williams, M. (2019). Artificial Intelligence
(AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research,
practice and policy. International Journal of Information Management.
https://doi.org/10.1016/J.IJINFOMGT.2019.08.002.
Feuerriegel, S., Hartmann, J., Janiesch, C., & Zschech, P. (2023). Generative AI. Business &
Information Systems Engineering, 1-16.
Frei, F. X., Ely, R. J., & Winig, L. (2009). Zappos.com 2009: Clothing, customer service, and
company culture. Harvard Business School Case 610-015. (Revised June 2011). Harvard Business
School.
Greenstein, S. (2004). Creative Destruction and Deconstruction. IEEE Micro, 24, 83-85.
https://doi.org/10.1109/MM.2004.45.
41
Greene, F. J. (2020). Entrepreneurship theory and practice (1st ed.). Red Globe Press.
Gupta, V., & Yang, H. (2024). Study protocol for factors influencing the adoption of ChatGPT
technology by startups: Perceptions and attitudes of entrepreneurs. PLOS ONE, 19.
Jarrahi, M. H., Askay, D., Eshraghi, A., & Smith, P. (2022). Artificial intelligence and knowledge
management: A partnership between human and AI. Business Horizons, 66(1), 87-99.
https://doi.org/10.1016/j.bushor.2022.03.002
Keicher, L., Ardilio, A., & Nawroth, G. (2022). Boosting Innovation by Artificial Intelligence (AI):
Effects and Potentials of AI in the Process of Innovating. 2022 Portland International Conference on
Management of Engineering and Technology (PICMET), 1-11.
https://doi.org/10.23919/PICMET53225.2022.9882591.
Koch, A., & Stahlecker, T. (2006). Regional innovation systems and the foundation of knowledge
intensive business services. A comparative study in Bremen, Munich, and Stuttgart, Germany.
European Planning Studies, 14, 123 - 146. https://doi.org/10.1080/09654310500417830.
Mondal, S.R., Das, S., & Vrana, V.G. (2023). How to Bell the Cat? A Theoretical Review of
Generative Artificial Intelligence towards Digital Disruption in All Walks of Life. Technologies.
McKelvey, M. & Lassen, A. H. (2013) Managing Knowledge Intensive Entrepreneurship. Edward
Elgar Publishing. Cheltenham (UK), Northampton (USA)
McShane, M., & Nirenburg, S. (2021). Linguistics for the Age of AI. The MIT Press.
https://doi.org/10.7551/mitpress/13618.001.0001
Mikalef, P., & Gupta, M. (2021). Artificial intelligence capability: Conceptualization, measurement
calibration, and empirical study on its impact on organizational creativity and firm performance. Inf.
Manag., 58, 103434. https://doi.org/10.1016/j.im.2021.103434.
Nigmatov, A., & Pradeep, A. (2023). The Impact of AI on Business: Opportunities, Risks, and
Challenges. 2023 13th International Conference on Advanced Computer Information Technologies
(ACIT), 618-622. https://doi.org/10.1109/ACIT58437.2023.10275510.
Phillips-Wren, G. (2012). AI Tools in Decision Making Support Systems: a Review. Int. J. Artif.
Intell. Tools, 21. https://doi.org/10.1142/S0218213012400052.
Pokhrel, S., & Banjade, S. (2023). AI Content Generation Technology based on Open AI Language
Model. December 2023. https://doi.org/10.36548/jaicn.2023.4.006.
Pryor, C., Webb, J., Ireland, R., & Jr, D. (2016). Toward An Integration of the Behavioral and
Cognitive Influences on the Entrepreneurship Process. Strategic Entrepreneurship Journal, 10, 21-42.
https://doi.org/10.1002/SEJ.1204.
Radosevic, S., & Yoruk, E. (2013). Entrepreneurial propensity of innovation systems : Theory,
methodology and evidence. Research Policy, 42, 1015-1038.
https://doi.org/10.1016/J.RESPOL.2013.01.011.
Righi, R., Samoili, S., Cobo, M., Baillet, M., Cardona, M., & Prato, G. (2020). The AI
techno-economic complex System: Worldwide landscape, thematic subdomains and technological
collaborations. Telecommunications Policy, 44, 101943. https://doi.org/10.1016/j.telpol.2020.101943.
42
Runping, G., Mengyuan, H., Tingting, S., & Ziqing, F. (2021). Opportunity Development Mechanism
of Enterprises in Digital Transformation from an Ecosystem Perspective: Based on the Case Studies
of Haier and Suning. , 43, 43-67. https://doi.org/10.16538/J.CNKI.FEM.20210802.105.
Sarasvathy, S. D. (2001). Causation and Effectuation: Toward a Theoretical Shift from Economic
Inevitability to Entrepreneurial Contingency. The Academy of Management Review, 26(2), 243–263.
https://doi.org/10.2307/259121
Sarker, I.H. (2022). AI-Based Modeling: Techniques, Applications and Research Issues Towards
Automation, Intelligent and Smart Systems. SN COMPUT. SCI. 3, 158.
https://doi.org/10.1007/s42979-022-01043-x
Shane, S. (2000). Prior Knowledge and the Discovery of Entrepreneurial Opportunities. Organization
Science, 11, 448-469. https://doi.org/10.1287/ORSC.11.4.448.14602.
Shin, Y. (2019). The Spring of Artificial Intelligence in Its Global Winter. IEEE Annals of the History
of Computing, 41, 71-82. https://doi.org/10.1109/MAHC.2019.2922909.
Singh, R., Hills, G., Lumpkin, G., & Hybels, R. (1999). THE ENTREPRENEURIAL
OPPORTUNITY RECOGNITION PROCESS: EXAMINING THE ROLE OF SELF-PERCEIVED
ALERTNESS AND SOCIAL NETWORKS.. , 1999. https://doi.org/10.5465/APBPP.1999.27600505.
Stickdorn, M., & Schneider, J. (2011). This is Service Design Thinking. BIS Publishers. ISBN
978-90-6369-279-7
Stinchcombe. (1965). Social structure and organizations. In J.G. MARCH (ed.) Handbook of
organizations (pp. 142–193).
Taherdoost, H., & Madanchian, M. (2023). Artificial Intelligence and Sentiment Analysis: A Review
in Competitive Research. Comput., 12, 37. https://doi.org/10.3390/computers12020037.
Tenkasi, R., & Boland, R. (1996). Exploring knowledge diversity in knowledge intensive firms: a new
role for information systems. Journal of Organizational Change Management, 9, 79-91.
https://doi.org/10.1108/09534819610107330
Treffinger, D.J. Creative Problem Solving: Overview and educational implications. Educ Psychol Rev
7, 301–312 (1995). https://doi.org/10.1007/BF02213375
Vidgen, R., Shaw, S., & Grant, D. (2017). Management challenges in creating value from business
analytics. Eur. J. Oper. Res., 261, 626-639. https://doi.org/10.1016/J.EJOR.2017.02.023.
Winston, P. Marvin L. Minsky (1927–2016). Nature 530, 282 (2016).
https://doi-org.ezproxy.ub.gu.se/10.1038/530282a
8.2 From Websites
Anyword. (2024). Anyword AI Writing Platform Built for Marketing Results. Retrieved from
https://anyword.com/
Feedly. (2024, January 17). Meet Feedly AI for Market Intelligence. Retrieved from
https://feedly.com/new-features/posts/meet-feedly-ai-for-market-intelligence
GrowthBar. (2024). Make SEO Content That Google Loves With AI. Retrieved from
https://www.growthbarseo.com/
43
INK. (2024). Experience The Power Of Perfectly Optimized Content. Retrieved from
https://inkforall.com/
Salesforce. (2024). Salesforce Einstein AI Solutions. Retrieved from
https://www.salesforce.com/products/einstein-ai-solutions/
Wikipedia contributors. (2024, February 21). Zappos. In Wikipedia.
https://en.wikipedia.org/wiki/Zappos
Zapier. (2024, January 8). Synthesia AI: Using Synthesia to generate AI videos. Retrieved from
https://zapier.com/blog/synthesia-ai-video/
9. Appendix
9.1 Invitation to survey participation 1
Dear [Name],
I am Marios Kyriakis, and I am currently a Master's student at the University of Gothenburg, focusing
on my master's thesis which explores the impact of AI tools on the entrepreneurial process. This topic
is particularly relevant for businesses seeking innovation, such as yours. I came across your contact
information on [Website Name] and believe that your participation in the survey could be mutually
beneficial. By completing this survey
https://qualtricsxm7lw58gklx.qualtrics.com/jfe/form/SV_1AE8lo4ITSqXJEG , you will discover
various AI tools that may be new to you. Your insights are incredibly valuable, and the survey will
only take a few minutes of your time. Questions 1-3 are confidential, and your responses will be
anonymized in the results. For instance, you may be mentioned as 'Founder of Company A'. Your
collaboration and input are greatly appreciated.
Warm regards,
Marios Kyriakis
9.2 Invitation to survey participation 2
Dear Entrepreneurial Mindset,
I hope this email finds you well. I am Marios Kyriakis, and I am currently a Master's student at the
University of Gothenburg, focusing on my master's thesis which aims to explore the impact of AI
tools on the entrepreneurial process.
Therefore, don't miss out on this opportunity to enhance your entrepreneurial processes.
Complete this 3-minute survey to learn about AI tools that could assist your entrepreneurial processes.
You can participate through this link:
https://qualtricsxm7lw58gklx.qualtrics.com/jfe/form/SV_1AE8lo4ITSqXJEG
Your feedback will shape solutions to support new businesses.
It's a quick way to discover new AI tools for your company.
Let me know if you have any questions!
44
Thank you in advance for your participation.
Please ensure that this message reaches someone who possesses the necessary expertise in this matter,
in case you are not the intended recipient.
Best regards,
Marios Kyriakis
University of Gothenburg
9.3 Survey Reminder 1
Dear Professional,
I'm following up on the survey I sent earlier about the impact of AI tools on entrepreneurship. Several
of your peers have already completed the survey, and their insights have been valuable.
If you haven't participated yet, I'd like to remind you that the survey only takes about 3 minutes. Your
input is crucial for understanding how businesses like yours are using AI to drive innovation. You can
access the survey here: https://qualtricsxm7lw58gklx.qualtrics.com/jfe/form/SV_1AE8lo4ITSqXJEG
Questions 1-3 are confidential, and responses will be anonymized in the results.
Your collaboration is greatly appreciated. Let me know if you have any questions.
Best regards,
Marios Kyriakis
University of Gothenburg
9.4 Survey Reminder 2
Hello Entrepreneurial Mindset,
I trust this message finds you in good spirits. I am reaching out to kindly remind you about the AI
tools survey that was recently distributed.
Your input will not only aid in the completion of my thesis but also provide you with valuable insights
on AI tools that can optimize entrepreneurial procedures. You can participate by clicking on the
following link: https://qualtricsxm7lw58gklx.qualtrics.com/jfe/form/SV_1AE8lo4ITSqXJEG
Rest assured that questions 1-3 are confidential, and your responses will remain anonymous in the
final analysis. Should you have any inquiries or require assistance, please do not hesitate to contact
me.
Thank you immensely for dedicating your time and sharing your thoughts!
Warm regards,
Marios Kyriakis
University of Gothenburg
45
9.5 Interview guide
1. Interviewee introduction. What role does the interviewee have in that company?
2. What is the value proposition for your company and how did you come up with this idea?
When was it founded?
3. What challenges do you face in your entrepreneurial journey?
4. How familiar are you with AI tools?
5. How do you use AI tools in your entrepreneurial journey? (which areas)
6. Can you present what specific AI tools you use?
7. When did you start using them and what benefits do you experience?
8. Have you had any negative aspects while utilizing AI in your entrepreneurial process?
9. What are some recommendations that you would like to give to other entrepreneurs who want
to use AI in their ventures?
46