Leveraging ChatGPT for Empowering MSMEs: A Paradigm Shift in Problem Solving ^†

Abstract

This paper delves into the potential of harnessing ChatGPT, an AI-driven language model, to empower micro, small, and medium enterprises (MSMEs) by revolutionising their approach to problem solving. The research aims to explore the integration of ChatGPT into MSME operations and evaluate its impact on enhancing their problem-solving efficiency. By scrutinising the literature and reviewing several case studies, a comprehensive framework emerges, detailing the utilisation of ChatGPT as a problem-solving tool for MSMEs. This involves training the model with industry-specific data and incorporating it into MSME communication channels, enabling intelligent responses to queries. The results highlight the substantial improvement in problem-solving capabilities, with the model’s real-time assistance diminishing response time, elevating accuracy, and furnishing tailored solutions to intricate challenges. However, limitations arise from the model’s reliance on existing data, potentially introducing biases. Significantly, this research offers practical implications for both MSMEs and policymakers. ChatGPT’s integration holds promise in terms of heightened efficiency, productivity, and competitiveness for MSMEs, counteracting resource constraints, and fostering growth. Policymakers can aid this transition by formulating ethical guidelines to ensure the equitable and transparent application of AI in the MSME sector. This study’s novelty lies in its focus on MSME empowerment through ChatGPT integration, bridging a research gap. Its value emanates from the actionable insights provided, offering guidance to MSMEs, policymakers, and practitioners keen on leveraging AI-driven solutions to amplify problem-solving capacities within the realm of MSMEs.

1. Introduction

The rapid advancements in artificial intelligence (AI) and natural language processing (NLP) have unveiled novel possibilities for addressing the barriers encountered by micro, small, and medium enterprises (MSMEs) [1,2]. MSMEs are crucial in driving economic growth and generating employment opportunities globally. This study explores the paradigm shift by leveraging ChatGPT, a powerful language model, to empower MSMEs to overcome their challenges [3]. By utilising the conversational abilities of ChatGPT, MSMEs can tap into a vast repository of knowledge; gain valuable insights; and make informed decisions fostering innovation, growth, and sustainability in their operations. This paper delves into the transformative potential of ChatGPT as a problem-solving tool for MSMEs by providing an overview of the challenges and prospects of integrating AI-based chat systems in the MSME sector.

The findings of this research impact the existing body of knowledge on leveraging AI technologies for MSME empowerment, offering practical insights for policymakers, researchers, and industry professionals to drive inclusive economic development. Numerous economies rely heavily on the micro, small, and medium enterprise (MSME) sector, which also makes a considerable contribution to innovation, job creation, and altogether economic growth. Emerging technologies have been investigated as potential solutions to these problems; one such interesting approach is the use of Chat Generative Pre-Trained Transformers (ChatGPT) [4]. This powerful natural language processing (NLP) model has proved promising for changing how MSMEs approach their difficulties. This study explores the use of ChatGPT and its significant influence on improving MSMEs’ problem-solving skills, thereby promoting their development and sustainability in a dynamically changing business environment.

Figure 1 illustrates the infographic representation of integrating ChatGPT in MSMEs. The detailed integration process is as follows:

• Data Preparation: pertinent data are gathered from internal sources such as customer databases, product information, and documentation.
• Preprocessing: the collected data are cleansed, organised, and prepared for analysis;
• ChatGPT Knowledge Base Integration: an internal knowledge base is developed using ChatGPT, inputting key data, FAQs, and procedural information. Employees engage with ChatGPT by providing natural language queries pertaining to tasks and information needs.
• Automated Insights and Content Creation: ChatGPT is used for automated data analysis, allowing employees to derive insights by posing natural language questions. ChatGPT is leveraged to aid employees in automating repetitive tasks and understanding workflow processes, and it is used for content creation, encompassing report writing, documentation, and textual content generation.
• Enriched Customer Interaction—Multichannel Engagement: ChatGPT’s capabilities are extended, covering customer-facing platforms like websites, social media, and messaging channels. It is then activated for real-time customer support, promptly addressing common queries and escalating complex issues when necessary.
• Continuous Enhancement and Oversight: The regular monitoring of ChatGPT’s performance in both internal processes and customer interactions is crucial, as this facilitates necessary updates and improvements. This streamlined workflow encapsulates the essential steps in integrating ChatGPT within MSMEs, showcasing its potential to enhance data utilisation, streamline workflows, and improve customer interactions.

2. Methodology

The methodology applied in this study was designed to delve into the transformative influence of ChatGPT on micro, small, and medium enterprises (MSMEs). This section delineates the essential steps taken to execute an exhaustive secondary research inquiry. The initiation of the research involved formulating the primary problem statement: evaluating the implications of integrating ChatGPT technology in MSMEs and discerning its potential to revolutionise problem-solving methodologies within this sector. To establish a foundational understanding, a comprehensive literature review was conducted, encompassing the current landscape of MSMEs, their challenges, and the prevalent state of technology adoption in problem-solving strategies. A thorough investigation into scholarly articles, industry reports, and case studies pertaining to ChatGPT and its applications in business environments complemented this review.

The subsequent phase encompassed the collection of data, with a focus on sourcing information from reputable academic journals, industry publications, official reports, and case studies. The primary objective was to garner insights into the application of ChatGPT in augmenting problem-solving capabilities within MSMEs. In conclusion, the research methodology is summarised, highlighting the systematic approach employed to explore the paradigm shift in problem-solving approaches within MSMEs through the integration of ChatGPT. The findings derived from this secondary research lay the groundwork for further exploration and potential empirical studies in this dynamic field.

3. Results and Discussion

3.1. Global Landscape of MSMEs

SMEs have a significant impact on economies, especially in developing nations, as they comprise the bulk of businesses globally and significantly contribute to job formation and universal economic growth [5]. These enterprises account for approximately 90% of businesses worldwide and over 50% of total employment. In developing economies, formal SMEs alone provide up to 40% of the collective state income (GDP), and these values rise substantially when informal SMEs are contemplated. It is anticipated that there will be around 600 million jobs by 2030, preparing the development of SMEs as a top priority area for governments globally. However, the lack of access to finance remains a significant obstacle to SME growth, ranking as the second most frequently cited challenge hindering their business expansion in emerging markets and developing countries [5]. MSMEs play a vital role in the economic landscape of several countries, including India, the UK, the USA, Australia, Germany, China, Brazil, Japan, Canada, and South Africa. However, the situations and challenges faced by MSMEs differ across these nations.

In India, MSMEs form the spine of nations’ economies, significantly contributing to employment generation and industrial growth. They face various hurdles such as limited access to credit, outdated technology, and inadequate infrastructure. However, government initiatives like the “Make in India” campaign and policy reforms aim to address these issues and foster MSME development. The UK has a thriving MSME sector known for its innovation and entrepreneurial spirit. However, Brexit has posed challenges for these enterprises due to uncertainties surrounding trade agreements and access to the European market. In the USA, MSMEs face competition from larger corporations and encounter difficulties in accessing financing. Government agencies, such as the Small Business Administration (SBA), provide support through loan programs and resources to foster MSME growth. Australia has a diverse and dynamic MSME sector that significantly contributes to the economy. These enterprises often face challenges related to scalability, limited market access, and high operating costs due to the country’s geographic isolation. Germany is renowned for its ‘Mittelstand’, which comprises many successful MSMEs. These enterprises excel in niche markets, prioritise innovation, and maintain strong relationships with their employees and local communities.

In China, MSMEs form a substantial portion of the economy and contribute to employment generation. While they benefit from a large domestic market, these enterprises face issues such as fierce competition, rising costs, and intellectual property concerns. Brazil boasts a diverse MSME sector that faces challenges related to high tax burdens, bureaucracy, and limited access to credit. Government initiatives aim to simplify regulations, reduce red tape, and provide financing options to support MSME growth. In Japan, MSMEs are integral to the economy, particularly in sectors like manufacturing and technology. These enterprises often face difficulties related to an aging population, labour shortage, and global market competition. In Canada, MSMEs are crucial for economic growth and job creation. They face challenges such as limited access to capital, talent shortages, and market saturation. South Africa has a diverse MSME sector that contributes to employment and economic inclusion. However, challenges persist, including limited access to finance, skills gaps, and regulatory barriers.

The MSME sector is essential to the nation’s socioeconomic growth. Due to its contribution to the GDP and exports, this industry is of great significance in India (Skokan et al., 2013) [6]. The classification of enterprises as micro, small, and medium enterprises (MSMEs) in India centres around their investment in plant and machinery or equipment, and their turnover. This categorisation is significant for understanding the landscape of MSMEs and designing tailored policies and support mechanisms. A micro enterprise is defined by an investment not exceeding one crore rupees (₹1 crore) and a turnover not exceeding five crore rupees (₹5 crores). Small enterprises are characterised by an investment not exceeding ten crore rupees (₹10 crores) and a turnover not exceeding fifty crore rupees (₹50 crores). Medium enterprises fall within the investment range of up to fifty crore rupees (₹50 crores) and have a turnover not exceeding two hundred and fifty crore rupees (₹250 crores). These thresholds provide a framework for classifying enterprises, enabling policymakers, researchers, and stakeholders to analyse and focus on the precise needs or challenges faced by each category (MSME, 2020) [7].

The regulations enacted by the 2006 Micro, Small, and Medium Enterprise Development (MSMED) Act govern the classification of MSMEs, which extends beyond separating manufacturing enterprises from service enterprises [8,9]. The investment in equipment criterion helps determine the scope of activities and technological capabilities of MSMEs [10,11]. The government may create an environment where MSMEs can thrive and more effectively contribute to the nation’s overall economic growth by adjusting aid and incentives in accordance with the specific needs of each category [12].

3.2. Challenges Faced by MSMEs

Various challenges faced by MSMEs are related to diverse areas like marketing, technology, etc. Figure 2 shows the challenges faced by MSMEs.

Policymakers, financial institutions, and other stakeholders play a pivotal role in promoting the growth of MSMEs. To bridge this information gap, it is imperative that MSMEs receive consistent and active support in accessing pertinent data. Ultimately, a proactive approach to supporting MSMEs through categorisation and data provision can pave the way for a more prosperous and resilient business ecosystem.

Marketing: Enhancing marketability poses a formidable challenge for micro, small, and medium enterprises (MSMEs) and large-scale corporations alike. The constraints of limited resources, encompassing time, financial capital, and access to skilled personnel present a particularly formidable hurdle for small-scale enterprises in their quest to boost visibility and generate high-quality leads. The provision of mentorship, networking opportunities, and comprehensive strategic planning proves instrumental in enabling MSMEs to not only reach their intended target audience but also foster sustainable growth. Through such multifaceted support, these enterprises can transform into formidable players in the market.

Technology: Despite having the third-largest pool of technologically skilled workers, India nevertheless has a sizable number of MSMEs that use antiquated and out-of-date technology. Their capacity to keep up with technological innovations is hampered by this predicament [13]. The adoption of new technology and the accompanying personnel training on these technical advancements are not only difficult but also expensive.

Upskilling: Having a trained staff is essential for corporate expansion. As a result, multinational corporations (MNCs) place a high priority on on-the-job training as a pillar of their business practices. Unfortunately, small businesses frequently overlook the need to upskill their personnel, thus impeding their own growth and development.

Business Expertise: Entrepreneurs frequently have specialised understanding of their goods and services, but they may not have the business sense needed to operate their businesses successfully. Their capacity to handle financial issues, track sales performance, and efficiently manage costs may be significantly improved by filling this knowledge gap by learning business skills and receiving expert help, which will in turn promote the success and longevity of their businesses.

Innovation: MSMEs must incorporate an innovation-focused culture into their everyday operations if they want to remain competitive. They gain the ability to respond to changing client wants, grasp new opportunities, and negotiate the dynamic business environment by embracing innovation.

Management: The development and competitiveness of small businesses are significantly hampered by a lack of adequate management skills. A company’s capacity to expand its workforce, meet varied consumer wants, manage inventories, and maintain a strong organisational culture are all key factors in its success. Unfortunately, many business owners disregard the value of efficient administration and face several difficulties as their companies expand.

3.3. CHATGPT and Its Application to MSMEs

Figure 3 shows the application of ChatGPT to MSMEs. With its chatbot interface, ChatGPT’s AI-powered natural language processing tool allows users to have discussions that are like those between people. This powerful tool has a wide range of applications, including customer assistance, virtual aides, content creation, and problem solving. However, OpenAI announced ChatGPT Plus, a subscription-based version, starting in February 2023. On 30 November 2022, ChatGPT was made available to the public by the AI research firm OpenAI. ChatGPT continues to evolve and improve, pushing the boundaries of human–machine interaction and paving the way for more effective and engaging interactions in various domains.

MSMEs can gain various advantages via ChatGPT. By serving as a virtual assistant, offering individualised assistance, and reducing the burden on scarce resources, it helps businesses better support their consumers. Enhanced Customer Support: For MSMEs, ChatGPT serves as a beneficial virtual assistant by providing quick and individualised customer service. It has the capacity to respond to client queries, provide thorough product information, and even help with problem solving. Time and Cost Savings: MSMEs may gain considerable benefits from ChatGPT’s automated features due to their constrained resources in terms of both money and personnel. These organisations may automate a variety of jobs and procedures by using the chatbot. Improved Efficiency and Productivity: MSMEs have the chance to simplify their internal procedures and processes using ChatGPT. Businesses might profit from using the chatbot for tasks such as managing schedules, organising data, and taking care of basic administrative duties. Enhanced Decision-Making Support: MSMEs may significantly benefit from ChatGPT since it provides immediate information and insights that support making wise decisions. The chatbot may provide information on market research, business trends, and competition analysis.

3.4. Limitations of ChatGPT for MSMEs

While ChatGPT has many advantages, it also has several drawbacks that can prevent it from completely meeting the demands of MSMEs. In client contacts, which frequently place a priority on developing personal relationships, a lack of empathy and human touch might be a detriment.

Lack of Human Touch: MSMEs prioritise building human connections with their clients, which might be difficult to reproduce purely through a chatbot interface. While ChatGPT can automate answers and offer effective assistance, it can fall short of MSMEs’ needs for a more individualised and sympathetic customer experience.

The Complexity of Business-Specific Queries: MSMEs regularly run into complex, industry-specific problems that require the knowledge and experience of human experts to solve. Due to its general-purpose architecture, ChatGPT might not be able to offer the specialised information and insights required to respond to such enquiries. Language Limitations: Although ChatGPT possesses impressive language understanding capabilities, it has certain limitations. It may face challenges in comprehending colloquial language, industry-specific jargon, or complex technical terms that are commonly used in specific MSME sectors. Inability to Handle Complex Decision Making: While ChatGPT has superior performance in a variety of activities, it may not effectively handle complicated decision-making processes that need human judgement and skill. Intricate subtleties and contextual awareness are frequently required for strategic planning, financial analysis, and regulatory compliance.

3.5. Implementation of Regulations in the Application of ChatGPT in Micro, Small, and Medium Enterprises (MSMEs)

Ensuring compliance with information protection regulations is crucial for the application of ChatGPT in MSMEs, especially when considering protocols like the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA). ChatGPT implementation in MSME operations should follow the norms of data minimisation and purpose limitation. Only essential data required for the intended purpose should be processed, and the use of the chatbot should be clearly defined. Conducting data protection impact assessments (DPIAs) to detect potential risks related to the use of ChatGPT is particularly important for high-risk processing activities, ensuring GDPR compliance. Compliance with both GDPR and HIPAA requires a careful consideration of data lifecycle management.

3.6. Ethical Perceptions Regarding AI Integration in Micro, Small, and Medium Enterprises

MSMEs should prioritise obtaining informed consent from users interacting with AI technologies like ChatGPT. Transparency about the use of AI, the purpose of data collection, and potential impacts on users can address the ethical concerns related to user autonomy and decision making. Ethical concerns arise when AI systems, including chatbots like ChatGPT, exhibit biases. MSMEs should be vigilant in detecting and modifying prejudices in training data to ensure fair and equitable outcomes, particularly in areas where biased outcomes may have serious results. The integration of AI, including ChatGPT, raises concerns about user privacy. MSMEs must prioritise robust data protection measures, secure storage, and clear communication regarding data handling practices to address ethical concerns related to user privacy infringement. Ethical considerations extend to the potential impact of AI on employment in MSMEs. Companies should proactively address concerns about job displacement by considering retraining programs, upskilling initiatives, and fostering a work environment that values human–AI collaboration.

3.7. Explicit Strategies or Methodologies to Mitigate Biases in ChatGPT’s Training Data

One fundamental step in mitigating unfairness in ChatGPT’s training information involves conducting meticulous bias audits of the training data. This process entails a thorough examination to identify and comprehend potential biases, particularly in relation to the representation of various demographic groups. Metrics such as demographic parity, equalised odds, false-positive rate (FPR), false-negative rate (FNR), and others can be employed to quantitatively assess biases, ensuring continuous and vigilant monitoring throughout the developmental stages. Other effective strategies can involve a careful balancing of training data to prevent the undue over-representation of specific groups. Additionally, regular evaluations of the model’s performance on diverse test datasets prove instrumental in the timely identification of emerging biases over the course of development.

3.8. Collaboration between MSMEs and AI Developers in Refining ChatGPT

Several actionable partnership models that illustrate potential collaborations between MSMEs and AI developers in refining ChatGPT are joint workshops and ideation sessions, pilot projects, partnership models, collaborative sessions, community forums, knowledge-sharing platforms, and proof of concept (PoC). MSMEs and AI developers may conduct joint workshops to identify and brainstorm sector-specific challenges. In this regard, collaborative sessions can involve domain experts from MSMEs and AI developers working together to understand specific industry hurdles. Ideation sessions can generate innovative use cases for ChatGPT in addressing MSME challenges. A continuous active collaboration and shared learning will foster a mutually beneficial relationship between MSMEs and AI developers in refining ChatGPT for specific industry applications. Even creating online forums or platforms and establishing a virtual community where MSMEs and AI developers can share insights, challenges, and best practices can be considered beneficial. This ongoing dialogue contributes to a collective understanding of sector-specific challenges and potential solutions.

3.9. Comparative Framework between the Use of ChatGPT and Other AI Chatbot Solutions in Micro, Small, and Medium Enterprises (MSMEs)

A comparative framework between the use of ChatGPT and other AI chatbot solutions in MSMEs is highlighted in

Table 1. A comparative framework between the use of ChatGPT and other AI chatbots in MSMEs (authors’ compilation).

Criteria	ChatGPT	Other AI Chatbots
Model Architecture	GPT (Generative Pre-trained Transformer)	Various, including rule-based, retrieval-based, and generative models
Training Data and Pre-training	Diverse internet text, fine-tuned for specific tasks	Customised training data for the intended domain, various models used
Customisation and Adaptability	Fine-tuning for specific contexts or industries	Customisation varies, and some limitations exist in adapting to unique MSME requirements
Natural Language Understanding (NLU)	Strong NLU, context handling	NLU capabilities vary, and some struggle with contextual understanding
Generative vs. Retrieval-based Approach	Generative, not limited to predefined responses	Retrieval-based models select predefined responses, limited to knowledge encoded during training
Scalability and Resource Requirements	Resource-intensive during training, efficient inference	Resource requirements vary based on model complexity
Continuous Learning and Updates	Supports fine-tuning and ongoing learning	Retraining is required for some models, and manual adjustments are needed for rule-based bots
User Interaction and Engagement	More engaging, handles a wider range of user inputs	Interaction styles vary and may struggle with diverse user inputs
Ethical Considerations	It has potential biases in training data, and it requires monitoring for ethical use	Ethical concerns depend on training data and design choices; bias may be less in rule-based systems

.

3.10. Specific Ethical Considerations in ChatGPT Integration for MSMEs

Ensuring transparency in how ChatGPT generates responses and providing explanations for its decisions can enhance trust, addressing ethical concerns related to the ‘black box’ nature of the model. MSMEs should prioritise obtaining informed consent from users interacting with ChatGPT. Users should be intimated about the objective of information gathering and have control over the extent of their engagement. Continuous efforts are needed to assess and mitigate biases to make certain that ChatGPT’s answers are fair and inclusive, avoiding discrimination against specific user groups.

4. Conclusions

The implementation of ChatGPT for resolving MSMEs’ challenges illustrates both its potential advantages and disadvantages. In the future, further study and development will be required to improve the means of AI language models like ChatGPT. Future work may focus on minimising biases in the training process, strengthening contextual awareness, and improving the system’s capacity to address challenging and industry-specific enquiries. Additionally, MSMEs should carefully assess the appropriateness and value of AI solutions like ChatGPT, considering elements like resource availability, the unique requirements of their industry, and the significance of preserving human interaction and tailored customer experiences.

Furthermore, MSMEs must consider the security and privacy implications of using ChatGPT. Sharing sensitive business information or customer data with the model can pose risks if not handled and secured properly. Implementing a robust information protection system and adhering to relevant privacy regulations is crucial.