Entrepreneurial Success: The Missing Link Between Education, AI, and Startup Growth

DOI: https://doi.org/10.64010/SDUS3791

Abstract

In today’s competitive startup landscape, where nine out of ten ventures fail, identifying the missing link between formal education, artificial intelligence (AI), and entrepreneurial success is crucial. This reflection explores how the integration of formal education, experiential learning, and AI-driven strategies can equip entrepreneurs to overcome critical challenges such as market misalignment, leadership deficiencies, and resource constraints. By combining theoretical frameworks with qualitative insights from interviews with startup founders and reflective analyses, this article offers actionable recommendations for educational institutions, entrepreneurs, and policymakers. It highlights the importance of bridging skill gaps, fostering AI adoption, and developing resilient startups capable of navigating uncertainty and achieving sustainable growth.

I. Introduction

In the fast-paced and uncertain world of startups, success is rarely determined by innovation alone. While creativity fuels new ventures, long-term survival depends on the strategic integration of formal education, artificial intelligence (AI), and entrepreneurship. According to CB Insights (2024), nearly 90% of startups fail within their first five years, often due to market misalignment, leadership deficiencies, and resource constraints. However, emerging evidence suggests that startups leveraging AI technologies, strong business education, and experiential learning demonstrate higher resilience and growth potential. For instance, a 2021 KPMG report found that AI-driven startups in the healthcare sector experienced revenue growth 40% faster than their non-AI counterparts. This disparity raises a crucial question: What factors enable certain startups to thrive while others struggle to survive?

One key factor is startup resilience—a venture’s ability to adapt to market shifts, overcome financial and operational challenges, and sustain growth despite uncertainty. Resilient startups are those that effectively navigate volatility, refine their business models in response to real-world conditions, and leverage emerging technologies such as AI to drive efficiency and innovation. However, resilience does not develop in isolation; it is deeply tied to an entrepreneur’s ability to bridge skill gaps—deficiencies in essential areas such as strategic decision-making, financial management, leadership, and technology integration.

Consider the case of Carlos, a participant in BICTIA’s programs and a highly skilled software engineer. Opting for entrepreneurship over completing a traditional business degree, Carlos developed cutting-edge AI-powered financial algorithms that propelled his fintech startup forward. However, as the company expanded, his lack of expertise in business fundamentals—such as market positioning, cash flow management, and team leadership—hindered growth and scalability. His experience highlights a broader challenge in the startup ecosystem: while technical expertise is invaluable, entrepreneurs must also bridge critical skill gaps, integrate AI strategically, and develop startup resilience to sustain long-term success.

This paper explores the interplay between formal education, experiential learning, and AI adoption as key drivers of startup success. Through theoretical analysis, structured interviews with startup founders, and reflective insights from BICTIA’s ecosystem, this study identifies key aspects for entrepreneurs to develop the competencies needed to navigate market volatility, optimize AI-driven strategies, and overcome common business challenges. By elaborating on bridging skill gaps, fostering AI adoption, and promoting startup resilience, this paper provides recommendations for educators, entrepreneurs, and policymakers. The discussion also highlights the role of accrediting bodies such as the Accreditation Council for Business Schools and Programs (ACBSP) in aligning academic learning with entrepreneurial demands, ensuring that formal education evolves to meet the needs of modern founders.

Ultimately, this reflection aims to contribute to the development of a startup ecosystem that not only thrives on innovation but also sustains long-term growth and adaptability in an increasingly competitive business landscape.

III. Decoding Startup Survival: Education, AI, and the Road to Resilience

This section explores the critical factors behind startup failures, the transformative impact of education in fostering entrepreneurial success, and the catalytic role of AI in reshaping the startup ecosystem. By examining these elements, the discussion provides actionable insights to help entrepreneurs, educators, and policymakers mitigate failure and build resilient ventures.

Grounded in a structured analysis of market trends, founder interviews, and empirical data, this discussion identifies the root causes of startup failure and evaluates how a strategic blend of formal education, experiential learning, and AI integration can drive sustainable growth. As part of this reflective study, interviews were conducted and a structured questionnaire was distributed to entrepreneurs within BICTIA’s ecosystem, gathering insights from 38 respondents (see Appendix 1 and Appendix 2 for details). These findings provided an empirical foundation, which combined with the author’s expertise in systems thinking (Jackson, 2000) fostered the connection of theoretical frameworks with real-world challenges, offering a comprehensive perspective on the evolving startup landscape.

Startup Failure

According to CB Insights (2024), the primary cause of startup failure is the lack of market demand (42%), followed by financing problems (29%) and inadequate teams (23%). These factors closely align with local experiences from entrepreneurs in BICTIA´s ecosystem. Identifying the root causes of failure is essential to developing strategies that mitigate these risks. Based on prior research and insights from the interviews, four main categories of failure have been identified.

The first category encompasses market-related challenges. Many startups struggle due to insufficient market research, often misinterpreting consumer demand or failing to identify viable customer segments. This issue is particularly pronounced in the context of disruptive innovations, where traditional forecasting methods tend to fall short. Christensen (1997) highlights this challenge, noting that market researchers and business planners often fail to predict the growth potential of emerging markets. He argues that historical data from industries such as disk drives, motorcycles, and microprocessors show a consistent pattern: expert forecasts about the size of new markets are frequently inaccurate (p. 15).

The empirical findings reinforce this point. In our study, 33.3% of respondents reported stable sales with minimal fluctuations (-5% to +5%), while 12.1% experienced a decline of over 20%. These figures highlight the ongoing challenge of achieving a strong product-market fit, even with conventional market research. The difficulty is even more pronounced in sectors leveraging disruptive technologies, where consumer adoption patterns remain unpredictable and market validation requires continuous iteration.

The second major category of failure is team-related. Poor leadership—manifested in ineffective decision-making, lack of strategic vision, or weak execution—often undermines startup viability. Additionally, conflicts stemming from misaligned goals or interpersonal tensions can disrupt collaboration, eroding productivity and long-term sustainability (Morales, 2014).

Financial constraints represent the third key challenge, with implications beyond capital  availability. Startups often struggle not only with securing funding but also with managing resources effectively. Christensen (1997) sheds light on this dynamic, arguing that while managers may believe they control resource allocation, in reality, it is customers and investors who dictate spending priorities. He asserts that companies unable to align their investment patterns with the expectations of these stakeholders ultimately fail (p. 14).

Information gathered from the questionnaires supports this claim. Survey results indicate that 48.5% of startups failed to create additional jobs, underscoring growth limitations, while many founders described securing capital as “very difficult” or even “impossible.” This financial strain often leads to insolvency, even among startups with promising revenue potential. Perhaps most strikingly,is the fact that 47.0% of entrepreneurs relied primarily on self-financing, a constraint that significantly limits scalability and innovation.

The fourth category pertains to technological deficits. Startups that fail to keep pace with evolving industry standards and technological advancements risk obsolescence. AI presents a significant opportunity for growth and efficiency, yet many startups struggle with its adoption. Despite 48.5% of surveyed startups utilizing AI, common barriers persist, with 51.5% citing a lack of technical expertise and 21.2% highlighting high implementation costs. These limitations hinder startups from fully leveraging AI’s potential, ultimately weakening their competitive edge.

The Role of Formal Education in Entrepreneurial Success

The relationship between formal education and entrepreneurial success presents an ongoing debate. While traditional business and management programs in higher education provide essential theoretical foundations, they often fall short in addressing the dynamic and fast-paced realities of entrepreneurship. As Blank (2013) critically observes, many entrepreneurs mistake business plans for execution roadmaps, failing to recognize them as sets of unproven assumptions. He argues that “entrepreneurs often mistake their business plan as a cookbook for execution, failing to recognize that it is only a collection of unproven assumptions” (p. 68). This perspective highlights a core challenge: business education must evolve beyond static frameworks to embrace adaptive and experiential learning.

A key tension in entrepreneurial education lies in balancing theoretical knowledge with real-world application. While strong foundational principles in finance, strategy, and leadership are valuable, their effectiveness is limited without hands-on experience. To bridge this gap, higher education institutions must integrate practical elements such as startup simulations, mentorship programs, and AI-driven business analytics training. These approaches prepare entrepreneurs to navigate uncertainty, refine their business models iteratively, and adapt to rapidly changing market conditions.

The rise of alternative learning models has opened new pathways for entrepreneurial education. Accelerators, bootcamps, and online platforms such as Coursera and Udemy offer targeted, flexible, and experiential learning opportunities. These programs emphasize problem-solving, innovation, and adaptability—key skills often underemphasized in traditional curricula. However, our survey reveals a significant gap in the adoption of these alternative learning approaches. While 33.3% of respondents have participated in accelerators, 51.5% have engaged in alternative education programs such as bootcamps and online courses. Still, 15.2% have not taken part in any structured entrepreneurial education, highlighting the continued lack of access to practical, skills-based training for many entrepreneurs.

One of the most critical aspects of entrepreneurial education is fostering a mindset of experimentation and data-driven decision-making. Blank (2013) underscores this by emphasizing the importance of hypothesis testing, stating that “to turn hypotheses into facts, founders need to get out of the building and test them in front of customers” (p. 72). This iterative process of testing, learning, and refining strategies is fundamental for startup success, bridging the gap between theoretical instruction and practical execution.

By integrating experiential learning with formal education and leveraging alternative training models, entrepreneurial education can better equip founders with the skills necessary to build resilient and adaptable ventures. Institutions that embrace this evolution will play a crucial role in shaping the next generation of entrepreneurs. Consequently, accreditation bodies like ACBSP, are called to play a pivotal role in shaping business and management educational programs, ensuring they prepare students not only for traditional corporate roles but also for the challenges of startup ecosystems.

 AI as a Catalyst for Startup Resilience

Artificial intelligence has rapidly emerged as a transformative force in the entrepreneurial ecosystem, offering startups powerful tools to enhance efficiency, innovation, and decision-making. By leveraging AI, startups can better navigate uncertainty, optimize resource allocation, and strengthen their ability to adapt to changing market conditions—key aspects of resilience.

One of AI’s most significant contributions is its ability to address critical startup challenges through predictive analytics. Sophisticated algorithms now enable startups to forecast market trends with greater accuracy, optimize pricing strategies based on real-time data, and anticipate customer behavior. Previously, such capabilities were exclusive to well-established corporations, but AI has democratized access to data-driven insights, empowering even early-stage ventures to make informed strategic decisions.

AI has also revolutionized marketing and customer engagement. Intelligent chatbots and AI-driven targeted campaigns have transformed how startups acquire and retain customers, offering personalized experiences at scale. These advancements allow emerging businesses to compete more effectively, even in highly saturated markets. Additionally, AI-driven operational solutions enhance efficiency by optimizing workflows, reducing costs, and improving resource allocation, enabling startups to do more with limited resources.

Despite its advantages, AI adoption presents significant challenges. Financial constraints remain a primary hurdle, as many startups struggle to afford sophisticated AI solutions and the necessary infrastructure—an issue particularly pronounced for early-stage ventures with limited funding. The technical expertise gap further complicates AI adoption; our research indicates that 51.5% of respondents identified a lack of specialized skills as a major obstacle. Implementing AI goes beyond programming knowledge; it requires expertise in model training, data interpretation, and system integration within specific business contexts, making it difficult for many startups to fully leverage AI’s potential.

Beyond technical and financial barriers, ethical considerations pose an additional challenge. Startups must carefully navigate issues related to data privacy, potential algorithmic bias, and evolving regulatory compliance. These are not merely technical concerns but fundamental elements that can impact a company’s reputation, customer trust, and long-term sustainability.

To fully harness AI’s potential as a resilience-building tool, startups must adopt a strategic approach—securing financial support, investing in skill development, and implementing AI responsibly. As AI continues to reshape the entrepreneurial landscape, those who successfully integrate it into their operations will be better positioned to withstand market fluctuations and drive sustainable growth.

Synthesizing Key Insights: AI, Formal Education, and Startup Resilience

As discussed above, startups operate in an inherently volatile landscape, where success depends on their ability to navigate challenges in market positioning, leadership, financial sustainability, and technological integration. This analysis highlights that failures often stem from a lack of market demand, leadership gaps, and financial constraints—yet solutions to these challenges require a multidimensional approach that goes beyond technological adoption.

Artificial intelligence has emerged as a transformative force, not merely enhancing operational efficiency but reshaping business models and unlocking new opportunities. As McKinsey (2023) notes, “Respondents from AI high performers are twice as likely as others to say their organizations’ top objective for generative  AI is to create entirely new businesses or sources of revenue” (p. 8) ? . This underscores the importance of startups embracing AI as a core driver of innovation and competitive differentiation. However, the rapid adoption of AI also introduces challenges, particularly in workforce adaptation. As McKinsey (2023) also highlights: “The expected business disruption from generative AI is significant, and respondents predict meaningful changes to their workforces. They anticipate workforce cuts in certain areas and large reskilling efforts to address shifting talent needs” (p. 1).. This reinforces the necessity for educational institutions to integrate AI literacy and experiential entrepreneurial training into their curricula, ensuring future founders are equipped to leverage AI effectively.

Beyond AI, formal education and skill development remain critical pillars of startup success. As emphasised above, formal education alone is insufficient; entrepreneurs must complement theoretical knowledge with experiential learning, mentorship, and exposure to real-world business challenges. Programs such as accelerators and bootcamps play a crucial role in bridging the gap between academic instruction and practical execution, offering founders opportunities to refine their business models, test hypotheses, and develop resilience through iterative learning. However, access to these alternative learning models remains uneven, with 31.6% of surveyed entrepreneurs having never participated in structured entrepreneurial programs. Expanding these opportunities—especially for early-stage and underserved founders—will be essential to fostering a more inclusive and dynamic startup ecosystem.

As Gómez Romero and González Herrera (2022) aptly observe, “A distinctive feature of the current era is constant change, which has created an uncertain and highly volatile environment. In this unstable setting, organizations must develop, adapt, and thrive. Their ability to reinvent themselves is crucial to their survival in the face of the rapid volatility of their surroundings” (p. X). This insight highlights the need for startups to embrace adaptability not just in their business strategies but also in their approach to combine formal education, skill development, and technological integration.

Ultimately, fostering startup resilience demands a holistic approach—one that blends strategic market insight, sound financial management, technological adaptability, and an evolving business and management education system. By embracing AI-driven innovation, refining business strategies, and expanding access to experiential learning, startups can not only survive in an increasingly complex environment but position themselves for long-term, sustainable success.

IV. Recommendations and Implications

Enhancing startup success and mitigating failure requires a coordinated effort between three key actors: educational institutions, entrepreneurs, and policymakers, each playing a critical role in fostering a resilient and innovative ecosystem. This analysis suggests that entrepreneurial education must evolve to bridge the gap between theoretical knowledge and practical execution. Developing hybrid learning models that integrate startup simulations, industry collaborations, and AI-driven case studies will better prepare students for real-world challenges. Additionally, embedding AI and data analytics training into business and management educational programs is essential to ensure that future entrepreneurs acquire both technical literacy and core business skills. Expanding access to accelerators and mentorship programs, particularly for underserved communities, will further democratize entrepreneurial opportunities.

For entrepreneurs, adaptability and strategic AI adoption are key to navigating today’s fast-paced business environment. Prioritizing lifelong learning through accelerators, online courses, and mentorship networks fosters resilience and innovation. Leveraging AI-driven tools—such as customer segmentation, predictive analytics, and process automation—can significantly enhance decision-making and competitive positioning. However, the technical expertise gap remains a significant barrier. Addressing this challenge requires fostering collaborations with universities, AI-focused bootcamps, and industry specialists to equip entrepreneurs with the necessary skills to integrate AI effectively into their business operations.

Policymakers must create a supportive environment that facilitates startup growth by expanding funding initiatives for entrepreneurial education and AI adoption, ensuring that resources are accessible to a broader range of founders. Public-private collaborations should be encouraged to align academic research with industry needs, making entrepreneurial education more relevant and impactful. Moreover, the responsible implementation of AI policies is crucial, requiring transparent data governance, efforts to mitigate algorithmic bias, and adherence to ethical standards. To further drive innovation, facilitating hackathons and innovation labs will provide valuable opportunities for entrepreneurs, students, and researchers to tackle industry and societal
challenges collaboratively.

A fourth emerging key actor in this discussion is accreditation bodies like ACBSP, which, as already mentioned above, play a pivotal role in shaping business and management educational programs. Given the growing complexity of the entrepreneurial landscape, ACBSP´s role becomes crucial in ensuring that business curricula evolve to meet industry demands. By integrating AI training, experiential learning, and interdisciplinary education, accreditation bodies can help bridge the gap between academia and industry, fostering startup resilience and innovation. Furthermore, they can drive collaboration between business schools, industry leaders, and policymakers, ensuring that educational frameworks align with the rapidly evolving needs of entrepreneurs in the digital age. Accreditation bodies must also lead in evaluating and promoting best practices in AI-driven business education, ensuring that business schools prepare students not only for traditional corporate roles but also for the challenges of startup ecosystems.

Future research should explore the long-term impact of AI adoption on startup success and its influence on emerging business models. Investigating the effectiveness of hybrid education models in equipping entrepreneurs with real-world skills will help refine educational frameworks. Additionally, alternative funding mechanisms, such as venture debt and public-private investment models, must be analyzed to address the capital constraints that hinder startup scalability.

In accordance with these recommendations, a crucial role for these four key stakeholders across the entrepreneurial ecosystem is to find new ways to foster collaboration and innovation. Educational institutions have the opportunity to shape well-rounded, tech-savvy entrepreneurs equipped for real-world challenges, while entrepreneurs themselves can explore AI and continuous learning to better navigate market complexities. Policymakers, through strategic interventions, can contribute to a more supportive framework that encourages sustainable and responsible growth. Meanwhile, ACBSP and other accreditation bodies can drive the transformation of business education, ensuring that academic programs remain relevant, innovative, and aligned with the needs of modern entrepreneurs. While challenges remain, these insights aim to inform discussions and initiatives that could help strengthen the entrepreneurial landscape over time.

V. Conclusion

Reducing the high failure rate of startups requires a comprehensive, adaptive approach that integrates formal education, experiential learning, and artificial intelligence. This paper confirms that entrepreneurs who blend academic training with real-world experience and AI-driven strategies are better equipped to overcome leadership challenges, market misalignment, and financial constraints.

While formal education provides essential theoretical knowledge, its real impact emerges when combined with practical methodologies such as accelerator programs, mentorship, and industry collaborations. Institutions like ACBSP and other accreditation bodies must play a pivotal role in ensuring that educational programs evolve alongside the entrepreneurial landscape, fostering a curriculum that aligns with real-world startup challenges and AI-driven business solutions.

Despite AI’s transformative potential—enhancing efficiency, reducing costs, and improving decision-making—significant barriers to adoption remain, including technical skill gaps and high implementation costs. Overcoming these obstacles will require collaborative efforts among entrepreneurs, educational institutions, and policymakers to expand AI accessibility and equip future founders with the skills needed to thrive in an increasingly digital economy.

Ultimately, startup resilience hinges on adaptability—the ability to anticipate market shifts, leverage technology strategically, and continuously refine business models. The future of entrepreneurship will depend on how effectively we bridge the gap between education, technology, and real-world business challenges. Only through a concerted effort between academia, industry, and policymakers can we build a startup ecosystem that not only fosters innovation but sustains long-term growth and impact.

References

• Blank, S. (2013). The Startup Owner’s Manual: The Step-by-Step Guide for Building a Great Company. K&S Ranch.
• Brown, T. (2009). Change by Design: How Design Thinking Creates New Alternatives for Business and Society. HarperBusiness.
• Christensen, C. M. (1997). The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail. Harvard Business Review Press.
• Checkland, P. (1981). Systems Thinking, Systems Practice. Wiley.
• Gómez Romero, J. G. I., & González Herrera, M. B. (Eds.). (2022). Investigación organizacional: desafíos y perspectivas. Universidad Juárez del Estado de Durango.
• Jackson, M. C. (2000). Systems Approaches to Management. Springer.
• KPMG. (2021). AI-driven startups in healthcare: Revenue growth analysis [Informe].
• Maurya, A. (2012). Running Lean: Iterate from Plan A to a Plan That Works. O’Reilly Media.
• McGrath, R. G. (2013). The End of Competitive Advantage: How to Keep Your Strategy Moving as Fast as Your Business. Harvard Business Review Press.
• McKinsey & Company. (n.d.). The state of AI in 2023: Adoption and impact on business [Informe].
• Morales, C. (2014). El emprendedor de organizaciones innovadoras. Siglo del Hombre Editores. 
• Osterwalder, A., & Pigneur, Y. (2010). Business Model Generation: A Handbook for Visionaries, Game Changers, and Challengers. Wiley.
• Ries, E. (2011). The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses. Crown Business.
• CB Insights. (2024, Enero 15). Startup Failure Rates and Statistics (2024): Why Do Startups Fail? https://www.cbinsights.com/research/startup-failure-reasons-top/

Appendix 1: Startup Founders Questionnaire

Empowering Success and Innovation among Startup Founders

Introduction and Instructions

At BICTIA, our mission is to strengthen the entrepreneurial ecosystem by providing strategic support and accelerating innovative startups. In order to continue enhancing our programmes and tailoring them to the real needs of our entrepreneurs, we seek to gain a deeper understanding of their experiences, challenges, and perspectives.

This questionnaire aims to gather valuable information on educational backgrounds, the impact of acceleration programmes, and the use of technologies such as Artificial Intelligence (AI) in business development. 

The insights collected will be critical for:

1. Identifying key challenges faced by startups at various stages of development.
2. Improving our acceleration, mentoring, and educational initiatives.
3. Designing targeted strategies to foster the sustainable growth of the companies within our portfolio.

Instructions:

1. This questionnaire is designed to be completed in approximately 25–30 minutes.
2. It includes both multiple-choice and open-ended questions to capture quantitative and qualitative data.
3. Please answer as sincerely and accurately as possible, as your input is essential to the continuous improvement of
   our programmes.

Confidentiality: All responses will be treated confidentially and used solely for internal analysis and service improvement purposes.

Thank you for being part of our community and for contributing to the strengthening of the entrepreneurial ecosystem with your valuable responses.

Section 1: General Information

1. What is your name and role within the startup?
   • (Short text response)
2. How long has your startup been operating?
   • Less than 1 year
   • 1–3 years
   • 4–6 years
   • More than 6 years
3. What is the primary sector of your startup?
   • Technology
   • Health
   • Education
   • E-commerce
   • Energy
   • Agriculture
   • Other: (Short text response)

Section 2: Educational Background

1. What is your highest level of formal education?
   • Secondary education
   • Undergraduate degree
   • Master’s degree (MBA or other)
   • Doctorate
   • Self-taught
2. Have you participated in alternative education programmes or accelerators?
   • Yes, in alternative education programmes (bootcamps, online courses, etc.)
   • Yes, in accelerator programmes
   • No, I have not participated in any
3. How many acceleration programmes have you participated in over the past six years?
   • 1 programme
   • 2–4 programmes
   • 4 or more programmes
   • None

Section 3: Education and Entrepreneurship

1. How do you perceive the value of formal education (undergraduate and postgraduate) in your entrepreneurial journey? (Scale from 1 to 5)
   • 1: Not relevant
   • 2: Slightly relevant
   • 3: Moderately relevant
   • 4: Highly relevant
   • 5: Extremely relevant
2. Do you believe that current educational institutions adequately prepare entrepreneurs for the challenges of starting a business?
   • Yes, completely
   • Partially, but with limitations
   • No, there are significant shortcomings
   • Other: (Short text response)
3. How important do you consider experiential learning compared to formal education in developing entrepreneurial skills? (Scale from 1 to 5)
   • 1: Not important
   • 2: Slightly important
   • 3: Moderately important
   • 4: Very important
   • 5: Extremely important
4. What do you consider to be the main limitations educational institutions face in preparing entrepreneurs? 
   • (Open-ended question)

Section 4: Accelerators and Skills Development

1. Describe your experience with acceleration programmes (if applicable). 
   • (Open-ended question)
2. How have these programmes influenced your skills and the development of your startup? 
   • (Open-ended question)
3. What do you consider to be the main skill gaps that should be addressed for entrepreneurs?
   • (Open-ended question)

Section 5: Integration of Artificial Intelligence (AI)

1. Does your startup use tools or technologies based on Artificial Intelligence (AI)?
   • Yes (Optional: provide examples – open-ended)
   • No
2. What are the main challenges you face when adopting AI technologies?
   • High costs
   • Lack of technical expertise
   • Ethical concerns (privacy, bias, etc.)
   • Other: (Short text response)
3. How has AI impacted the efficiency and growth of your startup?
   • (Open-ended question)

Section 6: General Reflections

1. Based on your experience, what advice would you give to new entrepreneurs regarding educational and technological tools?
   • (Open-ended question)
2. How do you envision the role of AI in entrepreneurship evolving over the next five years?
   • (Open-ended question)

Section 7: Post-Acceleration Programme Impact

1. Have you generated additional employment in your company over the past year?
   • Yes, 1–5 jobs
   • Yes, 6–10 jobs
   • Yes, more than 10 jobs
   • No additional jobs generated
2. How has your sales performance evolved in the past year?
   • Increased by more than 50%
   • Increased by 21% to 50%
   • Increased by 15% to 20%
   • Increased by 5% to 14%
   • Remained relatively stable (between -5% and +5%)
   • Decreased by 6% to 20%
   • Decreased by more than 20%
3. How difficult has it been for your startup to access capital? What have been your main sources of funding?
   • (Open-ended question)

Appendix 2: Startup Questionnaire Analysis

I. Overview of Entrepreneurial and Startup Profiles

Experience and Sector Distribution

• 54.5% of startups have been in operation for more than six years, while 9.1% have been active for less than a year.
• The majority of startups (48.5%) operate in the technology sector, followed by a more diverse distribution including health (6.1%), fintech (3.0%), e-commerce (3.0%), agriculture (3.0%), and others such as legal services, engineering, and manufacturing.

II. Education and Skill Development

• 36.4% of entrepreneurs hold a master’s degree, 45.5% have a professional degree, and 6.1% only completed secondary education.
• 51.5% have participated in alternative education programs like bootcamps and online courses, while 33.3% attended accelerators. However, 15.2% have not taken part in any structured entrepreneurial education.
• 42.4% have engaged in 2-4 accelerator programs, but 30.3% have never participated in one.

III. Perception of Education and Skill Gaps

• Education is valued with an average score of 3.85 out of 5: 33.3% rated it a 5, and 30.3% rated it a 4.
• Key skill gaps identified include sales, strategic vision, financial management, marketing, and leadership.

IV. AI Adoption and Challenges

• 48.5% of startups use AI, while 51.5% do not.
• The main barriers to AI adoption include:
  • 51.5% cite lack of technical expertise.
  • 21.2% cite high implementation costs.
  • 12.1% cite ethical concerns like privacy and bias.

V. Business Growth and Financial Challenges

• 48.5% of startups have not created additional jobs in the past year, while 39.4% have generated 1-5 new jobs.
• 33.3% of startups reported stable sales, while 12.1% experienced a revenue decline of over 20%.
• Access to capital remains a major challenge, with many founders describing it as “very difficult” or “impossible.”
• 47.0% rely primarily on self-financing, followed by grants, bank loans, and investment rounds.