Startup Valuation with Artificial Intelligence: A SWOT Analysis

 Startup Valuation with Artificial Intelligence: A SWOT Analysis

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Proceedings of The 5th International Conference on Research in Business, Management and Economics

5th International Conference on Research in Business, Management and Economics (ICRBME)

08-10 April 2022                                                           Paris, France

 Startup Valuation with Artificial Intelligence: A SWOT Analysis

Ph.D. Candidate Athanasios Davalas1, Professor Yannis Charalabidis2, MBA Panagiota Fenekoy3

1Department of Information and Communication Systems Engineering, University of the Aegean

2 Department of Information and Communication Systems Engineering, University of the Aegean

3Department of Business Administration in West Attica University, Aegean University KEDIVIM Student

Startup Valuation with AI
Analyzing data for new startup business with ai

Abstract

The study in question is aimed at examining the use of AI in evaluation processes in startups. The research seeks to address the issues surrounding the use of AI in startup evaluation. The introduction presents some background information concerning AI use in evaluation processes in a newly created organization. A literature review presents more information as proof of the strengths and weaknesses of AI use in evaluating a startup. A clear presentation of the SWOT analysis of the use of AI in evaluating startup organizations. The findings paint a clearer picture of what startup organizations should expect when implementing the use of AI to evaluate themselves. A discussion of the findings is presented in the research to ensure that people understand the issues surrounding the use of AI in evaluating startups and that they know the strengths and weaknesses of using AI in such processes. A brief conclusion summarizes what has been discussed in the study.

1. Introduction

Technological advancements in the recent past have resulted in the use of artificial intelligence (AI) on many occasions. Startup organizations are some of the beneficiaries of artificial intelligence regarding the evaluation processes. Startups need to undergo an evaluation to assure that their owners understand how to manage them more efficiently, so they can meet the goals they have set. AI tools are useful in ensuring that the evaluation process takes place in startups and basic implementation for entrepreneurs to understand their shortcomings and adopt better strategies to combat the challenges.

However, it is essential to note that there will always be challenges in using these tools to evaluate an organization. The implication of this argument is that there are strengths, weaknesses, opportunities, and threats to using AI. In the current digital era, everything that concerns the use of technology-related tools needs proper scrutiny to establish that every uncertainty and opportunity is put into consideration. This yields the idea of conducting a SWOT analysis regarding the use of AI tools in evaluating startups.

It is essential to note that the use of AI tools in evaluating startups is useful. It can detect many aspects of the organization, which is vital in decision-making processes. Accordingly, the SWOT analysis will reveal the effectiveness of these tools in the evaluation of newly formed organizations. Thus, the examination of the four components of which the SWOT analysis consists is essential in establishing the effectiveness of them using AI tools in evaluating new organizations in the markets.

2. Literature Review

The evaluation of startups is necessary because of many reasons that would be useful in helping such business ventures to survive. According to (Davalas, 2020), evaluating startups is necessary because it determines the point of interaction between the customers and the business. The interaction with people can only exist when the startups find time to evaluate themselves and weed out the problems that may be undermining their relationships with consumers and customers. Therefore, there is a need to understand that a strategic plan and a strategic management approach through evaluation is not an optional choice for entrepreneurs who want their new business ventures to prosper.

AI tools have different roles to play in ensuring that the evaluation of the startups is successful. According to (Prentice & Nguyen, 2020), AI tools are technology-related, which can help organizations provide vital information about the market and customers. Consequently, such data can prove quite meaningful for managers. It is essential to note that despite the demand to assess startups, technology-related tools often have something to celebrate and something to mourn about. It is paramount that the startups scrutinize the AI tools that are to be used in evaluation to ensure that they understand how effective such tools can be to the newly formed companies. The best way to determine such kind of effectiveness is by conducting a SWOT analysis on the use of AI in evaluation. A SWOT analysis would uncover different perspectives of why using AI to evaluate a startup is recommendable. It is essential to understand that examining the strengths, weaknesses, opportunities, and threats will provide more insights into the essence of examining businesses in that manner.

2.1 SWOT Analysis

2.1.1 Strengths

Many strengths exist in sing AI to evaluate startup businesses. Some of the strengths include the saving of time when undertaking tasks aimed during the evaluation. According to (Leyer & Schneider, 2021), AI tools are technology-related, which means that they enable the automation of processes within a startup company. The essence of saving time in the evaluation of a startup business is that it creates an opportunity for the business owners to concentrate on other important issues of the evaluation processes. Evaluating a startup organization entails many processes that, if one would perform manually, would be time-consuming. As a result, utilizing AI is crucial to the acquisition of more time that can be used to perform other vital tasks—involved in evaluating startups.

Moreover, AI use in evaluating startups has the strength of improving the quality of evaluation and reducing human error. According to (Agrawal et al., 2017), AI guarantees that evaluations are of high quality of a newly created organization are high in the sense that it digs deep into the details that managers need to examine when evaluating their organizations. Since AI is not human in nature, it is bound to perform more tasks with relatively higher accuracy than humans. The idea of accuracy comes in, which ensures that the possibility of human error is eliminated in the evaluation process. Hence, it is justifiable to argue that the strength of using AI in evaluating startups is that it ensures that errors are minimal and improves the quality of the process. which improves the quality evaluation process? When humans manually conduct the evaluation, the time taken is long, and the chances of committing errors are high. This proves the idea that, indeed, AI is necessary

In addition, personalized financial planning will be offered from the startups’ managers to the potential investors to match their needs and goals. Through the development of fully customized investment solutions, their financial plans will be managed in a dynamic way because of using AI during the evaluation process. This is one of the great important strength characteristics (Rao &Verweij, 2017).

Likewise, as AI can learn, remember, and comply with all applicable rules, it can assist startups through their evaluation in complying with government regulations when it comes to the financial services industry. In a continuously compound bureaucratic environment, gaining insights can drastically cut operating expenses, and it can be a game-changing impact from an investor’s perspective (Mou, 2019).

2.1.2 Weaknesses

Despite the presence of many strengths that are attributable to using AI in evaluating newly formed companies, weaknesses equally exist. According to (Allen, 2020), one of the greatest weaknesses of using AI in evaluating startups is that it is expensive. The use of AI tools requires human expertise and software that some newly formed companies may find too expensive. A startup organization does not expect to spend too many resources on evaluation because it is still trying to make efforts to provide that it breaks into the market and competes with the giant organizations that are already established. Despite the excellent work that the AI tools do in evaluating a startup, the costs prove too much for some of the newly formed business ventures. A few of the software used in the AI tools require a lot of money to acquire and install. Hence, it is justifiable to argue that using AI in evaluating startups has a weakness in terms of the costs incurred when implementing the use of AI tools.

Another major weakness of using AI in evaluating startups is that it cannot replicate what humans do. According to (Ranjan et al., 2018), machines are always regarded as better performers than humans, which means that AI is expected to work better than human beings do. Machines work based on the programming that is done on them by humans. Hence, AI cannot do some specific tasks that are better undertaken by humans. The implication of this argument is that AI cannot do some tasks best, which is a significant weakness when deciding whether to use AI to evaluate startups.

In addition to the above, managers often do not take into thought the need to determine constraints for when the AI will be permitted to form choices independently. When it’ll be administered by them and when it’ll basically guide a manager in making a choice (Gonfalonieri, 2020).

Once someone decides to use AI, it is pivotal to perform regular upgrades to the AI applications, to have the desirable and most updated results but also frequent model up-dating on a weekly or monthly basis in order to be more agile and have a tailor-made evaluation approach, (Chui et al., 2018).

Moreover, as AI technology has grown in popularity, a phenomenon known as AI bias has emerged. It occurs when an algorithm delivers biased results due to faulty assumptions made during the machine learning process. It can also contribute to and perpetuate biases in recruiting, financing and evaluating as a whole. Bias can appear in a variety of ways impacting the evaluation of startups in many different areas and during the phases of the educational process, setting the determinants of what should be achieved by the model, and gathering the insights that reflect preconceptions in order to enhance the startups’ profit. Biases can affect the evaluation process when the preparation and the presentation of large data sets need to be done, deciding which properties of the algorithms should be considered or ignored. Mitigating these biases may be difficult, but there is a strong movement within startups to do so, detecting hidden biases in training data and models, as well as processes to hold users of these models accountable for fairer outcomes and defining fairness in various contexts, (Hao, 2019).

2.1.3 Opportunities

Opportunities are often available anywhere that technology such as AI is used. According to (Adam et al., 2021), using AI in the evaluation processes can help an organization improve the services provided to customers, which in turn influences customer relations positively. Many AI tools will evaluate the relationship between customers and the company establishing better ways through which the startups can improve. The more elaborative the evaluation, the more loopholes are discovered that exist in their relationship with them. Consequently, more solutions keep arising, which help the companies enhance their relationships.

Another important issue related to AI tools is the use of different types of data to assist them in deciding where to invest in the technical capabilities and which of them will have the most impact.

2.1.4 Threats

The biggest threat of using AI in evaluating startups is that they threaten the existence of human jobs. According to (Huang & Rust 2018), human beings will have few roles to play once a startup decides to incorporate the use of AI tools in self-evaluation. Consequently, humans will always be skeptical of using AI in the process because they often feel that the company may find them obsolete, which renders them jobless automatically. It is essential for such companies to maneuver carefully into matters regarding human labor and AI tools application to avoid the conflict of interests between technology and humans. Startups can figure out other duties that can be assigned to humans to avoid retrenchment processes once the utilization of AI tools in evaluation is underway. Therefore, threats exist, which is why sometimes conflicts arise in organizations once employees realize that technology is being implemented.

One additional threat that exists in the use of AI is the urgent need to build strong trust in data management and usage. There are barriers that need to be overcome to some of the most technologically developed applications and tools to gain acceptance to seek from startups (Rao &Verweij, 2017).

Figure 1:SWOT analysis of startup valuation with artificial intelligence

3. Methods

The research in question concentrated on utilizing the mixed research methodology. This means that the use of both qualitative and quantitative data was crucial in establishing the effectiveness of using AI in evaluating startups. The advantage of using a mixed research methodology is that it ensures that a wider range of information is gathered to support the research in question (Belardinelli & Mele, 2020). Also, it was essential to incorporate different ideas from the sources of information that yield qualitative and quantitative data. The mixed research method ensures that the findings are grounded on concrete data that can be traced from the original participants in different studies.

The research in question adopted the mixed research methodology because it helps to avoid the challenges that come up due to adopting the single approaches that concentrate on qualitative or quantitative data only but also one can rely on different sources of information. This provides more credibility and reliability to the analysis because there is more information that can be used as proof of the claims that are being made. The use of AI in evaluating startups can be analyzed better by comparing qualitative and quantitative data.

It is essential to note that the mixed research method herein entailed gathering data from scholarly articles that formed a strong literature review. The essence of relying on the literature review is that most of the scholars who wrote the articles conducted extensive research to try to find out more about the use of AI in evaluating startups. Hence, information from previous scholars provides a great background from which to begin researching because they produce proven information. Questionnaires and surveys were also adopted in the research in question to enrich the data sources. The meaning of questionnaires is to acquire information on specific aspects of the research. Questionnaires are more effective in research because they can be administered to large groups of people physically or remotely. Research participants who may not be able to present themselves physically can take part in the study by accessing the questionnaires from an online platform such as their email accounts. Surveys are more similar to questionnaires concerning the additional value they provide in the analysis. Surveys can be done physically and remotely through online platforms.

It is crucial to touch on the question of sampling in the discussions concerning the methodology used in this research. Random sampling was utilized to ensure that there was no bias in the study. The participants were obtained from the larger populations at random. Random sampling is always advisable when conducting research because it ensures that the representative population that is selected does not in any way jeopardize the study through bias. Understanding the dynamics surrounding the use of AI in evaluating startups required the incorporation of ideas from random sample populations that constitute individuals who have dealt with the evaluation of startups using AI. Therefore, the methodology, and in extension, the data collection methods and sampling method used for this study were ideal in ensuring that more information concerning the use of AI in evaluating startups is gathered. Findings were determined based on the information obtained from the different data sources that aided in the provision of qualitative and quantitative data.

4. Findings

Derived from the review of literature, questionnaires issued, and the surveys conducted, findings were obtained in relation to the use of AI in evaluating startups, and the SWOT analysis on the same equally yielded a significant amount of data. It is important to note that one of the most significant findings was that the use of AI in evaluating startups is necessary because of the evolving nature of the business world. With the enhancements in technology, activities in startups need to be conducted at a faster pace to provide that such ventures catch up with the giant organizations in the market (Moretti, 2020). Irrespective of whether the use of AI is advantageous or not, the current business world demands that organizations, including startups, adopt a technology-based system that would help them to evaluate themselves effectively and efficiently.

Another significant finding drawn from the data obtained was that the most crucial strength of engaging AI in startup evaluation processes is that it saves time and enhances the quality of processes. AI is faster than humans are, which makes it most effective in carrying out tasks associated with startup evaluation. This finding was pivotal in creating an understanding of the idea that time is a critical factor in today’s business ventures and their operations. It is fundamental to elucidate that more startups are shifting towards the adoption of AI in their organizations, most specifically for the evaluation processes.

However, a negative finding was also discovered in that research indicated that using AI to evaluate startups is an expensive affair. Startup companies are forced to invest hugely in AI tools to ensure that their evaluation processes are enhanced. Startups do not need to overspend because they are still trying to establish themselves in the market. However, the use of AI in evaluating startups demands that they spend more to acquire the services that they seek from AI. Hence, it is essential to note that using AI to evaluate startups has its shortcomings as much as it has benefits.

5. Discussion

The usefulness of AI in evaluating startups lies in the ability to integrate information concerning distinct aspects of the organization’s operations. When scholars argue that AI is necessary for the evaluation of startups, they mean that the AI tools are vital in providing the information necessary for evaluating newly formed companies. For example, AI tools help the organization to understand more about the customer base in the market. Such information is crucial in ensuring that managers know how the company is fairing. It is necessary to consider that many AI tools exist, and they play different roles in contributing to the accomplishment of the evaluation processes in startups.

The need to save time when evaluating startups stems from the idea that such companies need to concentrate most of their time on vital issues that will help them grow. The argument that AI involvement in the evaluation of startups saves time is reasonable because such organizations require more time to promote themselves, develop better relationships with customers, and many other tasks, to ensure that they grow into bigger ventures in the shortest time possible. Wasting time on evaluation processes could prove costly for startups because they will lack time to do other activities such as marketing and promotions, which are critical to their survival in the market in their early days before they grow into big organizations. It is fundamental to comment that AI makes work easier for managers, despite it being a bit expensive. Once the evaluation processes are made easier, the saved time can be invested elsewhere to ensure that the startup in question can concentrate on profit-making activities.

Understanding the idea that AI is expensive helps organizations plan themselves accordingly. Now that AI is a necessity for most startups if they want to have smooth operations, such organizations need to plan themselves well to ensure that they have better ways of offsetting the deficits that may be caused by the requirements of AI tools. For instance, the companies could plan their budgets in a way that they reduce costs to aid the financing of AI incorporation in the organizations’ operations. It is important to comment that planning is the key to establishing a way through which startups can balance between obtaining AI services and maintaining their pace of growth in the market.

6. Conclusion

Accordingly, it is important to illustrate that the idea of utilizing AI in the evaluation of startups is a crucial matter to such organizations because they need to use tools and processes that guarantee efficiency and effectiveness. Most startups are shifting towards the acquisition of AI tools to help them because these tools are faster compared to human beings, meaning they save abundant time. Consequently, they can concentrate on other important issues that can help them grow. The use of AI in evaluating startups has its strengths and weaknesses because AI is advantageous to some extent and disadvantageous from other perspectives. When a startup decides to use AI in evaluating itself, it is more likely to be effective because of the way AI ensures the fulfillment of tasks. Startups need all the resources, time, and effectiveness they find to ensure that they create their path to growth in the best way possible. It is crucial to note that the argument that AI is necessary for startups and numerous other organizations is justifiable because the AI tools perform very crucial tasks that human beings might be slower in fulfilling. Faster and effective evaluation of startups often yields positive results.

However, startups should be wary of the weaknesses of using AI to evaluate themselves. Using AI tools could mean that most of the resources of the organization are channeled towards the acquisition, maintenance, and management of these tools, which could prove costly for a startup. Such scenarios are not healthy for organizations that are looking to grow shortly after they have introduced themselves in the market and industry. Hence, it is required for startups to plan themselves accordingly such that their spending does not wholly focus on AI incorporation into the evaluation processes to the extent that they forget about other operations that need to be undertaken.

Some of the threats from the adoption of AI during the evaluation process include job losses for humans. Whenever technology-related tools are associated with the evaluation of business organizations, humans are often threatened because they are boxed into a situation where they feel no job security. If AI tools can perform the tasks meant for humans, company owners often retrench their workforce to save costs. For startups, the case is even worse because company owners are looking to save more resources and invest them in other crucial departments. Additionally, it is logical to argue that workers of startups would be scared whenever the introduction of AI tools is done to boost the evaluation processes of such organizations. Similarly, opportunities can also be created using AI in evaluating startups. For instance, the observation of customer relations is crucial in deciding the links between customers and the organization. Therefore, startups can invest in AI tools when evaluating themselves because they offer more advantages than disadvantages. Through such gains achieved by the adequacy of using AI in evaluating startups, newly created organizations get to grow gradually and become bigger with time. Therefore, a brighter future is expected for most startup organizations that may decide to use AI tools to evaluate themselves.

References

Adam, M., Wessel, M., & Benlian, A. (2021). AI-based chatbots in customer service and their effects on user compliance. Electronic Markets31(2), 427-445.

Agrawal, A., Gans, J., & Goldfarb, A. (2017). What to expect from artificial intelligence?

Allen, G. (2020). Understanding AI technology. Joint Artificial Intelligence Center (JAIC) The Pentagon United States.

Belardinelli, P., & Mele, V. (2020). Mixed methods in public administration: advantages and challenges. In Handbook of Research Methods in Public Administration, Management and Policy. Edward Elgar Publishing.

Chui, M., Manyika, J., Miremadi, M., Henke, N., Chung, R., Nel, P., & Malhotra, S. (2018) McKinsey Global Institute analysis. Notes from the AI frontier insights from hundreds of use cases. Discussion paper. https://www.mckinsey.com/media/mckinsey /notes-from-the-ai-frontier-insights-from-hundreds-of-use-cases-discussion-paper.pdf

Davalas, A. (2020). Use of big data and AI tools to evaluate and assist startups.

Hao, K. (2019). “This is How AI Bias Really Happens—And Why it’s so Hard to Fix.” MIT Technology Review. https://www.technologyreview. com/s/612876/this-is-how-aibias-really-happensand-why-its-so-hard-to-fix

Huang, M. H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research21(2), 155-172.

Leyer, M., & Schneider, S. (2021). Decision augmentation and automation with artificial intelligence: Threat or opportunity for managers? Business Horizons.

Moretti, G. (2020). Educational Technology and the Startup Nation: a Black Box Reasoning (Bachelor’s thesis, Università Ca’Foscari Venezia).

Mou, X. (2019). Artificial Intelligence: Investment Trends and

Selected Industry Uses. Fresh Ideas About Business in Emerging Markets. IFC, a member of the World Bank Group.

Prentice, C., & Nguyen, M. (2020). Engaging and retaining customers with AI and employee service. Journal of Retailing and Consumer Services56, 102186.

Ranjan, R., Sankaranarayanan, S., Bansal, A., Bodla, N., Chen, J. C., Patel, V. M., … & Chellappa, R. (2018). Deep learning for understanding faces: Machines may be just as good or better than humans. IEEE Signal Processing Magazine35(1), 66-83.

Rao A., S., & Verweij, G., (2017). Global Artificial Intelligence Study: Sizing the prize. PwC Publications. https://www.pwc.com/gx/en/issues/analytics/assets/pwc-ai-analysis-sizing-the-prize-report.pdf

5th International Conference on Research in Business, Management and Economics (ICRBME)

08-10 April 2022                                                           Paris, France

 Startup Valuation with Artificial Intelligence: A SWOT Analysis

Ph.D. Candidate Athanasios Davalas1, Professor Yannis Charalabidis2, MBA Panagiota Fenekoy3

1Department of Information and Communication Systems Engineering, University of the Aegean

2 Department of Information and Communication Systems Engineering, University of the Aegean

3Department of Business Administration in West Attica University, Aegean University KEDIVIM Student

Abstract

The study in question is aimed at examining the use of AI in evaluation processes in startups. The research seeks to address the issues surrounding the use of AI in startup evaluation. The introduction presents some background information concerning AI use in evaluation processes in a newly created organization. A literature review presents more information as proof of the strengths and weaknesses of AI use in evaluating a startup. A clear presentation of the SWOT analysis of the use of AI in evaluating startup organizations. The findings paint a clearer picture of what startup organizations should expect when implementing the use of AI to evaluate themselves. A discussion of the findings is presented in the research to ensure that people understand the issues surrounding the use of AI in evaluating startups and that they know the strengths and weaknesses of using AI in such processes. A brief conclusion summarizes what has been discussed in the study.

1. Introduction

Technological advancements in the recent past have resulted in the use of artificial intelligence (AI) on many occasions. Startup organizations are some of the beneficiaries of artificial intelligence regarding the evaluation processes. Startups need to undergo an evaluation to assure that their owners understand how to manage them more efficiently, so they can meet the goals they have set. AI tools are useful in ensuring that the evaluation process takes place in startups and basic implementation for entrepreneurs to understand their shortcomings and adopt better strategies to combat the challenges.

However, it is essential to note that there will always be challenges in using these tools to evaluate an organization. The implication of this argument is that there are strengths, weaknesses, opportunities, and threats to using AI. In the current digital era, everything that concerns the use of technology-related tools needs proper scrutiny to establish that every uncertainty and opportunity is put into consideration. This yields the idea of conducting a SWOT analysis regarding the use of AI tools in evaluating startups.

It is essential to note that the use of AI tools in evaluating startups is useful. It can detect many aspects of the organization, which is vital in decision-making processes. Accordingly, the SWOT analysis will reveal the effectiveness of these tools in the evaluation of newly formed organizations. Thus, the examination of the four components of which the SWOT analysis consists is essential in establishing the effectiveness of them using AI tools in evaluating new organizations in the markets.

2. Literature Review

The evaluation of startups is necessary because of many reasons that would be useful in helping such business ventures to survive. According to (Davalas, 2020), evaluating startups is necessary because it determines the point of interaction between the customers and the business. The interaction with people can only exist when the startups find time to evaluate themselves and weed out the problems that may be undermining their relationships with consumers and customers. Therefore, there is a need to understand that a strategic plan and a strategic management approach through evaluation is not an optional choice for entrepreneurs who want their new business ventures to prosper.

AI tools have different roles to play in ensuring that the evaluation of the startups is successful. According to (Prentice & Nguyen, 2020), AI tools are technology-related, which can help organizations provide vital information about the market and customers. Consequently, such data can prove quite meaningful for managers. It is essential to note that despite the demand to assess startups, technology-related tools often have something to celebrate and something to mourn about. It is paramount that the startups scrutinize the AI tools that are to be used in evaluation to ensure that they understand how effective such tools can be to the newly formed companies. The best way to determine such kind of effectiveness is by conducting a SWOT analysis on the use of AI in evaluation. A SWOT analysis would uncover different perspectives of why using AI to evaluate a startup is recommendable. It is essential to understand that examining the strengths, weaknesses, opportunities, and threats will provide more insights into the essence of examining businesses in that manner.

2.1 SWOT Analysis

2.1.1 Strengths

Many strengths exist in sing AI to evaluate startup businesses. Some of the strengths include the saving of time when undertaking tasks aimed during the evaluation. According to (Leyer & Schneider, 2021), AI tools are technology-related, which means that they enable the automation of processes within a startup company. The essence of saving time in the evaluation of a startup business is that it creates an opportunity for the business owners to concentrate on other important issues of the evaluation processes. Evaluating a startup organization entails many processes that, if one would perform manually, would be time-consuming. As a result, utilizing AI is crucial to the acquisition of more time that can be used to perform other vital tasks—involved in evaluating startups.

Moreover, AI use in evaluating startups has the strength of improving the quality of evaluation and reducing human error. According to (Agrawal et al., 2017), AI guarantees that evaluations are of high quality of a newly created organization are high in the sense that it digs deep into the details that managers need to examine when evaluating their organizations. Since AI is not human in nature, it is bound to perform more tasks with relatively higher accuracy than humans. The idea of accuracy comes in, which ensures that the possibility of human error is eliminated in the evaluation process. Hence, it is justifiable to argue that the strength of using AI in evaluating startups is that it ensures that errors are minimal and improves the quality of the process. which improves the quality evaluation process? When humans manually conduct the evaluation, the time taken is long, and the chances of committing errors are high. This proves the idea that, indeed, AI is necessary

In addition, personalized financial planning will be offered from the startups’ managers to the potential investors to match their needs and goals. Through the development of fully customized investment solutions, their financial plans will be managed in a dynamic way because of using AI during the evaluation process. This is one of the great important strength characteristics (Rao &Verweij, 2017).

Likewise, as AI can learn, remember, and comply with all applicable rules, it can assist startups through their evaluation in complying with government regulations when it comes to the financial services industry. In a continuously compound bureaucratic environment, gaining insights can drastically cut operating expenses, and it can be a game-changing impact from an investor’s perspective (Mou, 2019).

2.1.2 Weaknesses

Despite the presence of many strengths that are attributable to using AI in evaluating newly formed companies, weaknesses equally exist. According to (Allen, 2020), one of the greatest weaknesses of using AI in evaluating startups is that it is expensive. The use of AI tools requires human expertise and software that some newly formed companies may find too expensive. A startup organization does not expect to spend too many resources on evaluation because it is still trying to make efforts to provide that it breaks into the market and competes with the giant organizations that are already established. Despite the excellent work that the AI tools do in evaluating a startup, the costs prove too much for some of the newly formed business ventures. A few of the software used in the AI tools require a lot of money to acquire and install. Hence, it is justifiable to argue that using AI in evaluating startups has a weakness in terms of the costs incurred when implementing the use of AI tools.

Another major weakness of using AI in evaluating startups is that it cannot replicate what humans do. According to (Ranjan et al., 2018), machines are always regarded as better performers than humans, which means that AI is expected to work better than human beings do. Machines work based on the programming that is done on them by humans. Hence, AI cannot do some specific tasks that are better undertaken by humans. The implication of this argument is that AI cannot do some tasks best, which is a significant weakness when deciding whether to use AI to evaluate startups.

In addition to the above, managers often do not take into thought the need to determine constraints for when the AI will be permitted to form choices independently. When it’ll be administered by them and when it’ll basically guide a manager in making a choice (Gonfalonieri, 2020).

Once someone decides to use AI, it is pivotal to perform regular upgrades to the AI applications, to have the desirable and most updated results but also frequent model up-dating on a weekly or monthly basis in order to be more agile and have a tailor-made evaluation approach, (Chui et al., 2018).

Moreover, as AI technology has grown in popularity, a phenomenon known as AI bias has emerged. It occurs when an algorithm delivers biased results due to faulty assumptions made during the machine learning process. It can also contribute to and perpetuate biases in recruiting, financing and evaluating as a whole. Bias can appear in a variety of ways impacting the evaluation of startups in many different areas and during the phases of the educational process, setting the determinants of what should be achieved by the model, and gathering the insights that reflect preconceptions in order to enhance the startups’ profit. Biases can affect the evaluation process when the preparation and the presentation of large data sets need to be done, deciding which properties of the algorithms should be considered or ignored. Mitigating these biases may be difficult, but there is a strong movement within startups to do so, detecting hidden biases in training data and models, as well as processes to hold users of these models accountable for fairer outcomes and defining fairness in various contexts, (Hao, 2019).

2.1.3 Opportunities

Opportunities are often available anywhere that technology such as AI is used. According to (Adam et al., 2021), using AI in the evaluation processes can help an organization improve the services provided to customers, which in turn influences customer relations positively. Many AI tools will evaluate the relationship between customers and the company establishing better ways through which the startups can improve. The more elaborative the evaluation, the more loopholes are discovered that exist in their relationship with them. Consequently, more solutions keep arising, which help the companies enhance their relationships.

Another important issue related to AI tools is the use of different types of data to assist them in deciding where to invest in the technical capabilities and which of them will have the most impact.

2.1.4 Threats

The biggest threat of using AI in evaluating startups is that they threaten the existence of human jobs. According to (Huang & Rust 2018), human beings will have few roles to play once a startup decides to incorporate the use of AI tools in self-evaluation. Consequently, humans will always be skeptical of using AI in the process because they often feel that the company may find them obsolete, which renders them jobless automatically. It is essential for such companies to maneuver carefully into matters regarding human labor and AI tools application to avoid the conflict of interests between technology and humans. Startups can figure out other duties that can be assigned to humans to avoid retrenchment processes once the utilization of AI tools in evaluation is underway. Therefore, threats exist, which is why sometimes conflicts arise in organizations once employees realize that technology is being implemented.

One additional threat that exists in the use of AI is the urgent need to build strong trust in data management and usage. There are barriers that need to be overcome to some of the most technologically developed applications and tools to gain acceptance to seek from startups (Rao &Verweij, 2017).

Figure 1:SWOT analysis of startup valuation with artificial intelligence

3. Methods

The research in question concentrated on utilizing the mixed research methodology. This means that the use of both qualitative and quantitative data was crucial in establishing the effectiveness of using AI in evaluating startups. The advantage of using a mixed research methodology is that it ensures that a wider range of information is gathered to support the research in question (Belardinelli & Mele, 2020). Also, it was essential to incorporate different ideas from the sources of information that yield qualitative and quantitative data. The mixed research method ensures that the findings are grounded on concrete data that can be traced from the original participants in different studies.

The research in question adopted the mixed research methodology because it helps to avoid the challenges that come up due to adopting the single approaches that concentrate on qualitative or quantitative data only but also one can rely on different sources of information. This provides more credibility and reliability to the analysis because there is more information that can be used as proof of the claims that are being made. The use of AI in evaluating startups can be analyzed better by comparing qualitative and quantitative data.

It is essential to note that the mixed research method herein entailed gathering data from scholarly articles that formed a strong literature review. The essence of relying on the literature review is that most of the scholars who wrote the articles conducted extensive research to try to find out more about the use of AI in evaluating startups. Hence, information from previous scholars provides a great background from which to begin researching because they produce proven information. Questionnaires and surveys were also adopted in the research in question to enrich the data sources. The meaning of questionnaires is to acquire information on specific aspects of the research. Questionnaires are more effective in research because they can be administered to large groups of people physically or remotely. Research participants who may not be able to present themselves physically can take part in the study by accessing the questionnaires from an online platform such as their email accounts. Surveys are more similar to questionnaires concerning the additional value they provide in the analysis. Surveys can be done physically and remotely through online platforms.

It is crucial to touch on the question of sampling in the discussions concerning the methodology used in this research. Random sampling was utilized to ensure that there was no bias in the study. The participants were obtained from the larger populations at random. Random sampling is always advisable when conducting research because it ensures that the representative population that is selected does not in any way jeopardize the study through bias. Understanding the dynamics surrounding the use of AI in evaluating startups required the incorporation of ideas from random sample populations that constitute individuals who have dealt with the evaluation of startups using AI. Therefore, the methodology, and in extension, the data collection methods and sampling method used for this study were ideal in ensuring that more information concerning the use of AI in evaluating startups is gathered. Findings were determined based on the information obtained from the different data sources that aided in the provision of qualitative and quantitative data.

4. Findings

Derived from the review of literature, questionnaires issued, and the surveys conducted, findings were obtained in relation to the use of AI in evaluating startups, and the SWOT analysis on the same equally yielded a significant amount of data. It is important to note that one of the most significant findings was that the use of AI in evaluating startups is necessary because of the evolving nature of the business world. With the enhancements in technology, activities in startups need to be conducted at a faster pace to provide that such ventures catch up with the giant organizations in the market (Moretti, 2020). Irrespective of whether the use of AI is advantageous or not, the current business world demands that organizations, including startups, adopt a technology-based system that would help them to evaluate themselves effectively and efficiently.

Another significant finding drawn from the data obtained was that the most crucial strength of engaging AI in startup evaluation processes is that it saves time and enhances the quality of processes. AI is faster than humans are, which makes it most effective in carrying out tasks associated with startup evaluation. This finding was pivotal in creating an understanding of the idea that time is a critical factor in today’s business ventures and their operations. It is fundamental to elucidate that more startups are shifting towards the adoption of AI in their organizations, most specifically for the evaluation processes.

However, a negative finding was also discovered in that research indicated that using AI to evaluate startups is an expensive affair. Startup companies are forced to invest hugely in AI tools to ensure that their evaluation processes are enhanced. Startups do not need to overspend because they are still trying to establish themselves in the market. However, the use of AI in evaluating startups demands that they spend more to acquire the services that they seek from AI. Hence, it is essential to note that using AI to evaluate startups has its shortcomings as much as it has benefits.

5. Discussion

The usefulness of AI in evaluating startups lies in the ability to integrate information concerning distinct aspects of the organization’s operations. When scholars argue that AI is necessary for the evaluation of startups, they mean that the AI tools are vital in providing the information necessary for evaluating newly formed companies. For example, AI tools help the organization to understand more about the customer base in the market. Such information is crucial in ensuring that managers know how the company is fairing. It is necessary to consider that many AI tools exist, and they play different roles in contributing to the accomplishment of the evaluation processes in startups.

The need to save time when evaluating startups stems from the idea that such companies need to concentrate most of their time on vital issues that will help them grow. The argument that AI involvement in the evaluation of startups saves time is reasonable because such organizations require more time to promote themselves, develop better relationships with customers, and many other tasks, to ensure that they grow into bigger ventures in the shortest time possible. Wasting time on evaluation processes could prove costly for startups because they will lack time to do other activities such as marketing and promotions, which are critical to their survival in the market in their early days before they grow into big organizations. It is fundamental to comment that AI makes work easier for managers, despite it being a bit expensive. Once the evaluation processes are made easier, the saved time can be invested elsewhere to ensure that the startup in question can concentrate on profit-making activities.

Understanding the idea that AI is expensive helps organizations plan themselves accordingly. Now that AI is a necessity for most startups if they want to have smooth operations, such organizations need to plan themselves well to ensure that they have better ways of offsetting the deficits that may be caused by the requirements of AI tools. For instance, the companies could plan their budgets in a way that they reduce costs to aid the financing of AI incorporation in the organizations’ operations. It is important to comment that planning is the key to establishing a way through which startups can balance between obtaining AI services and maintaining their pace of growth in the market.

6. Conclusion

Accordingly, it is important to illustrate that the idea of utilizing AI in the evaluation of startups is a crucial matter to such organizations because they need to use tools and processes that guarantee efficiency and effectiveness. Most startups are shifting towards the acquisition of AI tools to help them because these tools are faster compared to human beings, meaning they save abundant time. Consequently, they can concentrate on other important issues that can help them grow. The use of AI in evaluating startups has its strengths and weaknesses because AI is advantageous to some extent and disadvantageous from other perspectives. When a startup decides to use AI in evaluating itself, it is more likely to be effective because of the way AI ensures the fulfillment of tasks. Startups need all the resources, time, and effectiveness they find to ensure that they create their path to growth in the best way possible. It is crucial to note that the argument that AI is necessary for startups and numerous other organizations is justifiable because the AI tools perform very crucial tasks that human beings might be slower in fulfilling. Faster and effective evaluation of startups often yields positive results.

However, startups should be wary of the weaknesses of using AI to evaluate themselves. Using AI tools could mean that most of the resources of the organization are channeled towards the acquisition, maintenance, and management of these tools, which could prove costly for a startup. Such scenarios are not healthy for organizations that are looking to grow shortly after they have introduced themselves in the market and industry. Hence, it is required for startups to plan themselves accordingly such that their spending does not wholly focus on AI incorporation into the evaluation processes to the extent that they forget about other operations that need to be undertaken.

Some of the threats from the adoption of AI during the evaluation process include job losses for humans. Whenever technology-related tools are associated with the evaluation of business organizations, humans are often threatened because they are boxed into a situation where they feel no job security. If AI tools can perform the tasks meant for humans, company owners often retrench their workforce to save costs. For startups, the case is even worse because company owners are looking to save more resources and invest them in other crucial departments. Additionally, it is logical to argue that workers of startups would be scared whenever the introduction of AI tools is done to boost the evaluation processes of such organizations. Similarly, opportunities can also be created using AI in evaluating startups. For instance, the observation of customer relations is crucial in deciding the links between customers and the organization. Therefore, startups can invest in AI tools when evaluating themselves because they offer more advantages than disadvantages. Through such gains achieved by the adequacy of using AI in evaluating startups, newly created organizations get to grow gradually and become bigger with time. Therefore, a brighter future is expected for most startup organizations that may decide to use AI tools to evaluate themselves.

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