The role of startups in creating innovative ecosystems
The purpose of the study is to identify key indicators that reflect the importance of AI startups in the formation. The methodology encompasses a diverse array of analytical tools and approaches to provide a comprehensive understanding of the subject.
Рубрика | Экономика и экономическая теория |
Вид | статья |
Язык | английский |
Дата добавления | 21.07.2024 |
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The role of startups in creating innovative ecosystems
Lizaveta Peniaz
F1 Student at AOI College of Languages,
Irvine, CA 92606, USA
Abstract
The article is dedicated to examining the role of startups in creating innovative ecosystems. The purpose of the study is to identify key indicators that reflect the importance of AI startups in the formation of these ecosystems. The research methodology encompasses a diverse array of analytical tools and approaches to provide a comprehensive understanding of the subject. It includes statistical analysis for quantifying and interpreting data related to startup activities and their impacts on innovation ecosystems. Additionally, the study incorporates general scientific approaches, which involve systematic inquiry, and theoretical framework development, to ensure a robust and well-rounded investigation of the role of startups in creating innovative ecosystems. The findings reveal that innovative ecosystems are networks of interdependent actors that drive entrepreneurship within a specific territory. There has been a significant global increase in such ecosystems, with a projection to reach 155 by 2025. Today, about 3% of companies use artificial intelligence technologies, and it is predicted that by 2030, 80% of companies will have adopted artificial intelligence technologies to some extent, and the global impact of AI on GDP will be $16 trillion. Startups are identified as crucial in these ecosystems, often leading their development, especially in countries like the United States, the UK, Israel, Canada, and Sweden. The global startup landscape shows fluctuations with sectors like life sciences and Deep Tech demonstrating resilience and growth, highlighting the essential role of AI startups in fostering innovation and economic development. The research concludes that startups are moving innovation ecosystems away from traditional corporate-driven models to more dynamic, agile, and open forms of innovation. They bring rapid, disruptive changes to markets, diversify funding sources, and create job opportunities, with big companies increasingly collaborating with startups for new ideas and technologies. The practical significance of this study lies in providing insights for policymakers, entrepreneurs, and investors on fostering and leveraging startups for economic growth and innovation. It highlights the need for supportive environments that encourage startup activities, particularly in emerging economies. innovative ecosystem entrepreneurship economic
Keywords: AI, startups, innovative ecosystems, entrepreneurship, economic development, innovation.
Formulation of the problem
In the contemporary business landscape, the emergence and proliferation of innovative ecosystems have become a focal point for discussions on economic development and technological advancement. At the heart of these ecosystems are startups - dynamic, agile entities known for their disruptive potential and capacity to drive significant change. Startups contribute to innovative ecosystems by pushing the frontiers of research and development, often translating cutting-edge academic insights into commercially viable products and services.
Globally, the number of innovative ecosystems is on the rise, with projections indicating a reach of 155 by 2025 [12]. This growth is not confined to traditionally strong economies; emerging markets are also displaying a surge in startup activities. Such a trend suggests a paradigm shift in the sources and drivers of innovation, moving beyond the confines of established corporate structures to more open, collaborative, and flexible models of business and creativity.
This exploratory study delves into the dynamics of these ecosystems, examining the critical role startups play in their development and sustenance. Undoubtedly, the United States and other developed countries are leading the way in the development of Al-based startups: Great Britain, Canada, Israel, and Sweden. But the recent US Executive Order [7] is designed to bolster the United States' position as a global leader in AI by streamlining immigration processes for individuals with AI expertise. This policy can significantly enhance the innovative capacity of the nation by ensuring a steady influx of global talent, which is crucial for startups that rely on highly specialized skills to drive innovation. As startups continue to break new ground, their influence extends beyond mere market disruption. They are key in diversifying funding sources, creating job opportunities, and fostering collaborations with large corporations, thereby enhancing the overall vitality and resilience of the innovation ecosystems they inhabit.
Analysis of recent research and publication
The collective body of research on startups and innovation ecosystems reveals varied perspectives and contributions to the field. Moore's seminal work [8] from the early 1990s still resonates today, introducing a metaphorical comparison of business competition to natural ecosystems. His concept of companies as predators and prey in a business context has influenced how we understand the competitive dynamics within innovation ecosystems. Brooks' work [2] offers a practical viewpoint, focusing on the essential features of entrepreneurial innovation ecosystems. His insights are particularly valuable for understanding how these ecosystems can be nurtured and developed in different cultural and economic contexts. Ianioglo [4] contributes a theoretical perspective, examining the interplay between innovation and entrepreneurship within these ecosystems. His research adds depth to the understanding of how various elements within an ecosystem interact and support the growth of startups. O'Connor, Stam, Sussan, and Audretsch [9] provide a comprehensive overview of entrepreneurial ecosystems, their transformations, and transitions. Their research is pivotal in understanding the evolution of these ecosystems over time and across different geographical settings.
Antoniuk and Antoniuk's study [1] provides a nuanced understanding of startup ecosystems in Eastern European countries, emphasizing their role in Ukraine's post-war reconstruction. This research is significant for its focus on the geopolitical and economic factors influencing startup ecosystems in a transitional economy.
Lanovska's work [6], on the other hand, delves into the core principles that define innovation ecosystems. This study is critical for understanding the structural dynamics that underpin these complex environments.
Each of these authors contributes uniquely to the topic, offering a blend of theoretical insights, practical approaches, and comparative analyses that enrich our understanding of how startups catalyze innovation within different ecosystems.
Despite the significant strides made in AI technology, there remains a distinct gap in contemporary, comprehensive research specifically focused on the critical role of AI startups in shaping innovation ecosystems. Much of the existing literature tends to emphasize general projects that showcase the development of these ecosystems or consists of reports from statistical agencies that purport to cover the subject. However, there is a dearth of in-depth academic exploration that scrutinizes the transformative impact AI startups have on the evolution and dynamics of innovation ecosystems. This oversight represents both a practical and theoretical void, underscoring an urgent need for scholarly research that examines the substantial contributions of AI startups to the broader innovation landscape. Identifying this gap is a call to action for future research to investigate and elucidate the fundamental role of AI startups in driving technological advancement and economic growth.
The purpose of the study is to identify key indicators that reflect the importance of startups in the formation of innovation ecosystems.
Research results
Innovative ecosystems, a concept with roots in biology, have been adapted to the economic and entrepreneurial context to describe complex networks of interdependent actors and factors. The term was first introduced in the economic domain by J. Moore in 1993 [8], who described it as encompassing both the internal and external environment of a business. This includes not only the business owners and employees but also government agencies, competitors, suppliers, and other stakeholders (Fig.1).
Fig.1. Common ecosystem components [1]
The composition of an ecosystem varies with its area of activity. For instance, in a healthcare ecosystem, the network commonly encompasses hospitals, clinics, research laboratories, and other related medical institutions. Such diversity in components is contingent upon the particular industry domain of the ecosystem.
The concept has evolved to focus on the territorial spread and the holistic view of entrepreneurship, rather than concentrating on individual entities. E. Stam and B. Spiegel [12] defined the entrepreneurial ecosystem as a set of coordinated, interdependent actors and factors that promote productive entrepreneurship within a certain territory. This definition distinguishes these ecosystems from clusters and innovation systems by emphasizing the geographical scope and the collective approach to fostering entrepreneurship [9].
Summarizing the research of scholars, an innovative ecosystem is a coordinated network of interdependent actors and factors that facilitate productive entrepreneurship within a specific territory.
The trend in the development of innovative ecosystems has been one of rapid expansion. Starting from a handful of ecosystems in 2013, there has been a steady and significant increase in their number worldwide, reflecting the growing recognition of their importance in fostering economic growth and innovation
Fig.2. Global ecosystem development [11]
Note: author's forecast
This growth trajectory suggests a burgeoning interest and investment in creating environments that nurture collaborative innovation, with a forecast of 155 innovative ecosystems globally by 2025. This trend underscores the critical role these ecosystems play in driving entrepreneurial activity and economic development across various regions.
Regarding the role of startups in the development of ecosystems, it is worth noting that this phenomenon is just beginning to gain momentum. Largely, startups operate independently and autonomously, without forming clusters or ecosystems. Globally, the United States holds the leadership position in the startup arena, followed by the United Kingdom, Israel, Canada, and Sweden (Table 1).
Table 1
Country ranking in creating a favorable environment for startups [131
Rank |
Country |
Rank |
Country |
Rank |
Country |
Rank |
Country |
|
1 |
United States |
14 |
Estonia |
27 |
Brazil |
40 |
Colombia |
|
2 |
UK |
15 |
Spain |
28 |
UAE |
41 |
Indonesia |
|
3 |
Israel |
16 |
Ireland |
29 |
Russia |
42 |
Romania |
|
4 |
Canada |
17 |
Lithuania |
30 |
Italy |
43 |
Malaysia |
|
5 |
Sweden |
18 |
Japan |
31 |
New Zealand |
44 |
Croatia |
|
6 |
Singapore |
19 |
Denmark |
32 |
Iceland |
45 |
Turkiy |
|
7 |
Germany |
20 |
South Korea |
33 |
Poland |
46 |
Greece |
|
8 |
France |
21 |
India |
34 |
Luxembourg |
47 |
Argentina |
|
9 |
Australia |
22 |
Belgium |
35 |
Czechia |
48 |
Slovenia |
|
10 |
The Netherlands |
23 |
Norway |
36 |
Chile |
49 |
Ukraine |
|
11 |
Switzerland |
24 |
Taiwan |
37 |
Mexico |
50 |
Hungary |
|
12 |
China |
25 |
Austria |
38 |
Bulgaria |
|||
13 |
Finland |
26 |
Portugal |
39 |
Latvia |
These countries have managed to create environments that effectively support the birth and growth of startups, contributing to their status as top innovative ecosystems. The adoption of artificial intelligence (AI) by businesses is growing but still not fully widespread. Specifically, only about 3.8% of businesses reported using AI to produce goods and services [3]. However, this usage varied widely among different sectors, with the Information sector reporting higher levels of AI use at 13.8%. Similarly, businesses in the Professional, Scientific, and Technical Services sector reported a significant share of AI adopters at 9.1%.
According to statistics, the artificial intelligence market is estimated at USD 196.6 billion in 2023 [5]. At the same time, artificial intelligence is most often used in the field of advertising (use in social networks).
OpenAI is the most widespread among all AI startups. Let's consider the most popular startups in each of the considered sectors of the economy, systematizing the data in Table 2.
Fig. 3. Use of artificial intelligence by economic sectors, % [5]
Note: systematized by the author
AI Startups play a foundational role in the construction of innovative ecosystems, often serving as the catalysts for their development. These ecosystems tend to emerge more rapidly around new, agile business ventures rather than established companies [2].
Traditionally, big corporations have been the mainstays of innovation, leveraging substantial resources to fuel research and development, and holding tightly to intellectual property rights. Their scale allowed for significant internal investment and a certain level of creative exploration, albeit within a more structured, linear, and often closed-off environment. The dependency on these corporate 'hosts' and 'gatekeepers' meant that innovation was typically a top-down process, with ideas and inventions being driven by the financial might and research capabilities of these large entities [10].
Fig. 4. Expansion of the innovation ecosystem through startups [10]
Table 2
The most |
widely used startups in various industries |
|||
Industry |
Startup Name |
Investment Received |
Description |
|
AI Research and Application |
OpenAI |
$1 billion (approximately) in initial funding, with later rounds undisclosed |
An AI research and deployment company that aims to ensure that artificial general intelligence (AGI)-- highly autonomous systems that outperformhumansatmost economically valuable work--benefits all of humanity. OpenAI develops the GPT series, including ChatGPT. |
|
Healthcare |
DeepMind |
Acquired by Google for $500M+ |
Develops AI for various applications, including healthcare, where their AlphaFoldprogrammadea breakthrough in protein folding. |
|
BFSI |
Affirm |
Raised $500M in Series G round |
Provides services in the financial industry offering buy now, pay later options for consumers through point of sale loans. |
|
Law |
ROSS Intelligence |
Raised $13.1M in funding over 4 rounds |
Creates legal research software that uses AI to help lawyers find relevant case law faster than traditional search methods. |
|
Retail |
Stitch Fix |
Went public with an IPO valuation of $1.4B |
Offers a personal styling service that uses algorithms to tailor clothing recommendationstoindividual customer preferences. |
|
Advertising |
Cognitiv |
Raised $5M in Series A & Seed rounds |
Uses deep learning to automate media buying, making advertising campaigns more effective and efficient. |
|
Automotive & Transportation |
Waymo |
Funding rounds totaling $3B+ |
Focuses on the development of autonomous driving technology to improve transportation safety and accessibility. |
|
Agriculture |
Blue River Technology |
Acquired by John Deere for $305M |
Specializes in smart farming equipment that uses AI and computer vision for more precise application of fertilizers and herbicides. |
|
Manufacturing |
Desktop Metal |
Raised $430M before going public |
Innovates in the 3D printing sector, particularly focusing on metal 3D printing for |
Note: systematized by the author
In contrast, the startup ecosystem injects a fresh dynamism into this landscape. Startups epitomize the transition to a non-linear, globally networked world where technology, platforms, and go-to-market channels are increasingly accessible and cost-effective. These agile entities thrive on fast-paced, flexible, and highly motivated approaches to innovation, often supported by both private and public funding sources that are eager to back new solutions. The process of innovation within startups is inherently open and more directly exposed to market validation from the outset.
Moreover, as the corporate world gradually recognizes the limitations of its 'best level' operations and seeks 'next level' solutions, smart big companies are shifting towards open innovation models. They collaborate with startups, acquire the most promising ones, and tap into the vast pool of entrepreneurial talent. In essence, startups become an 'outsourced innovation' arm for big companies, similar to how app developers create for software platforms like iOS and Android.
Startups and innovative small to medium-sized enterprises (SMEs) are not only significant as job creators but also as catalysts for change in the innovation ecosystem. They embody the outsider strategies and methods, bringing customer development into the core of the innovation process. The commitment and initiative that startups bring to the table are essential for innovation to occur, as they often take risks that larger entities cannot afford to take, pioneering in areas unexplored by their bigger counterparts. This symbiosis between startups and big companies is reshaping the innovation landscape, where startups are increasingly recognized for their critical role in driving growth, creativity, and societal progress.
Startups, particularly those specializing in AI technologies, are at the forefront of innovation, significantly influencing the development of modern innovative ecosystems. Their role is multifaceted and impacts various aspects of technology, economy, and society.
Startups are central to the vibrancy and success of innovation ecosystems, contributing essential qualities and functions that complement the roles of established companies and other stakeholders.
Table 3
Key drivers of the AI startup's role in shaping innovation ecosystems [4]
Component |
Role of AI Startups |
|
Innovation |
AI startups are at the cutting edge of technological innovation, rapidly developing and applying AI solutions to disrupt traditional markets and create new ones. |
|
Research and IPR |
AI startups often emerge from academic research, bringing new intellectual property to the market and collaborating closely with research institutions to commercialize AI breakthroughs. |
|
Funding |
AI startups attract significant investments from venture capital, specialized AI funds, government grants, and corporate venture arms due to the high potential of AI technology. |
|
Market Validation |
AI startups are adept at leveraging user data and feedback to iterate and improve their AI models and solutions swiftly, ensuring product-market fit. |
|
Job Creation |
AI startups contribute to job creation not only directly by hiring for diverse roles but also indirectly by fostering new industries around AI applications. |
|
Corporate Collaboration |
These startups are valuable partners for larger corporations seeking to innovate through AI, often leading to strategic partnerships or acquisitions. |
|
Flexibility and Adaptability |
With the innate capacity to refine algorithms and pivot applications, AI startups exemplify adaptability in the face of evolving technological landscapes. |
|
Entrepreneurial Culture |
AI startups foster a culture of rapid innovation, data-driven decision-making, and embracing technological challenges. |
|
Ecosystem Diversity |
They introduce a range of AI-powered products and services, from machine learning tools to intelligent automation, enriching the ecosystem's offerings. |
|
Global Networking |
AI startups are inherently global, often collaborating across borders to access data, talent, and markets, which enhances cross-border knowledge transfer. |
Based on the study by Ianioglo A. [4] and O'Connor A. [9], the development of startup ecosystems is characterized by a distinct lack of uniformity in strategic approaches across different countries. However, in the United States, the landscape is poised for refinement following President Biden's Executive Order of October 30, 2023. This order is set to enhance ecosystem development strategies through an expanded immigration policy that targets specialists in AI technology development. The directive serves as a countermeasure to China's five-year plan aimed at becoming a technology leader by 2030.
Globally, by 2030, AI is expected to underpin $16 trillion in global economic activity, marking a substantial increase from the $6 trillion contribution to global GDP observed today. This growth is indicative of AI's pervasive integration across industries alongside other transformative technologies.
Analysts also anticipate that around 70% of companies worldwide will adopt at least one form of AI by 2030 as part of their scaling operations. A significant proportion of large enterprises will leverage the full spectrum of existing innovations to enhance their business vectors.
Countries recognized as AI leaders - primarily developed nations - may gain 20-25% more economic benefits compared to the current level. In contrast, developing countries might only see half of this increase. Concurrently, the demand for experts in this field is expected to surge, potentially reaching tens of millions of professionals within the next decade.
Conclusions
An innovative ecosystem is characterized by a dynamic network of interdependent actors who promote and sustain entrepreneurship within a given territory. As of 2023, there has been a noticeable proliferation of such ecosystems, particularly influenced by the surge of startups specializing in artificial intelligence. These AI startups are central to the innovative vigor within ecosystems, especially in technologically advanced countries like the United States, which has recently enacted policies to further bolster this sector. The introduction of the Executive Order on AI and immigration by President Biden exemplifies a strategic move to enhance the United States' competitive edge in AI by facilitating the influx of global AI talent, potentially accelerating the country's position in the race against other tech leaders such as China.
While traditionally stronger economies have led in startup activity, there is a significant presence of AI startups in emerging economies, indicating a global embracement of AI innovation. The resilience and growth seen in sectors like life sciences and Deep Tech underscore the essential role of AI startups in driving technological advancement and economic development. These startups are transforming innovation ecosystems from the traditional corporate-centric models to more fluid, adaptable, and collaborative structures. AI startups act as catalysts for rapid, disruptive market changes, foster diverse funding avenues, and generate substantial employment opportunities.
References:
1. Antoniuk, D. and Antoniuk, K. (2023). Comparative analysis of startup ecosystems in the development models of Eastern European countries: experience for the post-war reconstruction of Ukraine. Management and Entrepreneurship: Trends of Development, 2(24), pp. 59-69. DOI: https://doi.org/10.26661/2522-1566/2023-2/24-06
2. Brooks, O. (2023). 10 features of an Entrepreneurial Innovation Ecosystem: Think BIG Jamaica. Linkedin. URL: https://www.linkedin.com/pulse/features-entrepreneurial-innovation- ecosystem-jamaica-brooks-
3. Census Bureau (2023). How Many U.S. Businesses Use Artificial Intelligence? URL: http://www.census.gov/library/stories/2023/11/businesses-use-ai.html
4. Ianioglo, A. (2022). Innovation and Entrepreneurial Ecosystems. IntechOpen. DOI: 10.5772/intechopen.102344
5. Kulik J. (2023). Artificial Intelligence (AI) Statistics & Facts for 2024. Neurosys. URL: https://neurosys.com/blog/artificial-intelligence-statistics-and-facts
6. Lanovska, G. (2017). Innovation ecosystem: essence and principles. Economy and society. 11, 257-262. URL: https://economyandsociety.in.ua/journals/11_ukr/43.pdf
7. Masse M., Ruemenapp D. (2023). Artificial Intelligence & Immigration: President Biden's New Executive Order. The National Law Review. URL: https://www.natlawreview.com/ article/artificial-intelligence-immigration-president-bidens-new-executive-order
8. Moore, J.F. (1993). Predators and prey: A new ecology of competition. Harvard Business Review, 71(3), 75-86
9. O'Connor, A., Stam, E., Sussan, F., Audretsch, D. (2018). Entrepreneurial ecosystems: Place-based transformations and transitions. New York: Springe. DOI: 10.1007/978-3-319-63531-6.
10. SC (2023). From Innovation Ecosystems to Startup Ecosystems. URL: https:// www.startupcommons.org/from-innovation-ecosystems-to-startup-ecosystems.html
11. Sidhu K.K. (2020). Global Startup Ecosystem Report flags risk of mass extinction event for startups globally. DNA. URL: https://www.digitalnewsasia.com/startups/global-startup- ecosystem-report-flags-risk-mass-extinction-event-startups-globally
12. Stam, E., & Spigel, B. (2016). Entrepreneurial ecosystems. U.S.E. Discussion Paper Series, 16(13), 1-15.
13. Startup Genome (2023). The Global startup ecosystem report 2023. URL: https:// startupgenome.com/reports/gser2023
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