Artificial Intelligence and Service Marketing: Transforming Local Kirana Shops in Vidarbha Region.

Artificial Intelligence and Service Marketing: Transforming Local Kirana Shops in Vidarbha Region.

Mr. Akshay Umbarkar

Sushila Suryawanshi Management Institute of Technology Advancement, Amravati, India

DOI: https://doi.org/10.51244/IJRSI.2025.120500153

Received: 06 June 2025; Accepted: 07 June 2025; Published: 18 June 2025

ABSTRACT

The integration of artificial intelligence (AI) into retail is globally transforming service marketing practices. However, in Vidarbha, India, kirana shops—the cornerstone of local retail—largely rely on basic digital tools like office automation software and social networking platforms, such as Facebook and Instagram, rather than advanced AI systems. This study evaluates the current state of digital adoption among kirana shops in Vidarbha using secondary data sources, including industry reports and academic literature. The findings reveal that while digital tools have enhanced customer engagement and operational efficiency, there are significant barriers to AI adoption, such as cost constraints, technical skills, and infrastructure limitations. This paper offers actionable strategies to enable AI integration and calls for targeted interventions to empower local shop owners. By addressing these challenges, AI can revolutionize service marketing for kirana shops, ensuring their sustainability in an increasingly competitive market.

Keywords: Artificial Intelligence, Service Marketing, Kirana Shops, Vidarbha, Local Retail, Digital Transformation, Social Media Marketing, India, Technology Adoption, Retail AI.

INTRODUCTION

Background

India’s retail ecosystem is a vibrant mix of organized and unorganized sectors, with kirana shops forming the backbone of the latter. These small, family-owned stores serve as the lifeline of daily commerce, particularly in semi-urban and rural regions. According to industry estimates, unorganized retail contributes approximately 88% of the total retail sales in India (FICCI, 2022). Despite the rise of e-commerce giants and organized retail chains, kirana shops continue to thrive, thanks to their localized operations, personal customer relationships, and unmatched convenience.

The Indian retail sector has witnessed rapid digitization over the past decade, driven by factors such as increased internet penetration, growing smartphone adoption, and government-led initiatives like Digital India. Larger retailers and e-commerce platforms have capitalized on these advancements, integrating artificial intelligence (AI) technologies to enhance customer experiences, streamline operations, and optimize marketing strategies. For instance, AI-driven recommendation systems, dynamic pricing models, and automated customer support have become standard in urban retail.

However, the penetration of such advanced technologies into the unorganized retail sector, particularly in regions like Vidarbha, remains minimal. Vidarbha, located in eastern Maharashtra, is predominantly agrarian, with semi-urban and rural areas making up a significant portion of its geography. Here, kirana shops cater to local communities, often operating with limited technological support. Unlike their urban counterparts, these small businesses primarily rely on traditional practices and basic digital tools, such as office automation software for billing and social media platforms for marketing.

The Vidarbha Context

Vidarbha presents a unique retail environment shaped by its demographic and economic landscape. The region’s semi-urban and rural character means that kirana shops are often the sole providers of essential goods, serving communities that lack access to organized retail chains or large supermarkets. Despite their importance, these shops face increasing challenges from both e-commerce platforms and organized retail outlets, which offer competitive pricing, doorstep delivery, and extensive product choices.

Digital transformation in Vidarbha has been slow compared to urban areas, primarily due to infrastructure constraints, including inconsistent internet connectivity and frequent power outages. Moreover, the limited financial capacity of kirana shop owners restricts their ability to invest in advanced technologies. Despite these limitations, some shop owners in Vidarbha have begun adopting basic digital tools to enhance their operations. For example, social networking platforms like Facebook and Instagram are being used to promote products, while office automation software is streamlining billing and inventory management. These early steps toward digitalization reflect the potential for further technological integration, including the adoption of AI tools.

Why Artificial Intelligence (AI)?

AI has emerged as a transformative force in retail, offering solutions that are reshaping customer experiences and business operations globally. Its ability to analyze vast amounts of data and deliver actionable insights enables businesses to personalize marketing efforts, predict customer behavior, optimize inventory, and automate customer service. While such applications are prevalent in organized retail, their adoption in unorganized retail, especially in semi-urban and rural regions like Vidarbha, remains underexplored.

For kirana shops in Vidarbha, AI has the potential to address several challenges. Predictive analytics can help shop owners manage inventory more effectively, reducing stockouts and overstocking. AI-powered chatbots and customer relationship management (CRM) systems can enhance customer engagement by personalizing promotions and automating order-taking processes. However, realizing these benefits requires overcoming significant barriers, including cost, awareness, and technical expertise.

The Research Gap

The majority of existing research on AI in retail focuses on large retailers and urban markets. Studies examining the use of AI in unorganized retail or small businesses, particularly in rural or semi-urban settings like Vidarbha, are sparse. Furthermore, while there is substantial literature on the adoption of basic digital tools by small businesses, little attention has been paid to the transitional journey from these tools to advanced AI systems.

This research addresses this gap by exploring how kirana shops in Vidarbha currently use basic digital tools and evaluating the potential for AI integration in their service marketing practices. It aims to provide actionable insights for stakeholders, including policymakers, technology providers, and shop owners, to facilitate the digital transformation of local retail.

Research Objectives

This study is guided by the following objectives:

To assess the use of digital tools such as office automation software and social media platforms for service marketing by kirana shops in Vidarbha.

To identify the barriers preventing the adoption of AI technologies in these businesses.

To propose strategies for the effective integration of AI tools into the marketing and operational practices of kirana shops.

Research Questions

To achieve these objectives, the study seeks to answer the following questions:

What is the current state of digital tool adoption among kirana shops in Vidarbha for service marketing?

How are these tools enhancing customer engagement and operational efficiency?

What challenges do kirana shop owners face in adopting advanced AI technologies?

What strategies can enable the successful integration of AI into the operations of kirana shops in Vidarbha?

LITERATURE REVIEW

The literature review explores existing research on AI adoption in retail, the role of digital tools in service marketing for small businesses, and the challenges faced by kirana shops in embracing AI technologies. This section identifies knowledge gaps and establishes the theoretical framework for understanding the potential transformation of service marketing practices among kirana shops in Vidarbha.

AI in Retail: Global and Indian Perspectives

AI has revolutionized the retail industry globally, enabling businesses to optimize operations, enhance customer experience, and drive revenue growth. AI applications in retail include predictive analytics, customer segmentation, chatbots, recommendation systems, and inventory optimization (McKinsey, 2021). These tools leverage big data and machine learning algorithms to predict customer preferences, improve service delivery, and minimize operational inefficiencies.

For example, Amazon’s AI-driven recommendation engine has been credited with generating 35% of its total sales by suggesting products based on customer browsing history and purchase patterns (Smith and Linden, 2017). Similarly, Walmart uses AI-powered shelf-scanning robots to monitor inventory levels and ensure product availability (TechCrunch, 2020).

In India, organized retail giants like Reliance Retail and Flipkart have adopted AI technologies to enhance customer engagement and streamline logistics (KPMG, 2020). Flipkart’s AI platform, AI for India, uses machine learning algorithms to provide personalized product recommendations and language localization for diverse Indian consumers (Economic Times, 2021). However, the adoption of AI in the unorganized retail sector, including kirana shops, remains limited due to financial, technical, and infrastructural barriers.

Service Marketing and Digital Tool Adoption in Small Retail Businesses

Service Marketing Evolution:

Service marketing emphasizes creating value for customers through personalized interactions, quality service delivery, and relationship management (Zeithaml et al., 1985). The evolution of service marketing has been closely tied to advancements in technology. Digital tools have emerged as critical enablers of modern service marketing, allowing businesses to target customers more effectively, communicate seamlessly, and deliver superior experiences (Kotler et al., 2017).

Digital Tools in Small Businesses:

Small businesses, including kirana shops, have increasingly adopted basic digital tools to remain competitive in the evolving retail landscape. According to a report by Nasscom (2020), more than 60% of small retailers in India use some form of digital payment system, while 40% rely on social media platforms for marketing. These tools include:

Point-of-Sale (POS) Systems: Simplify billing, track sales, and manage inventory (Haque and Ghosh, 2020).

Social Networking Platforms: Platforms like Facebook and Instagram enable kirana shop owners to promote products, announce offers, and engage directly with customers (Pradhan et al., 2022).

Messaging Apps: WhatsApp is widely used by small retailers for order-taking, sending promotional messages, and customer feedback (Jain and Singhal, 2021).

Although these tools improve customer engagement and operational efficiency, they lack the advanced capabilities of AI-driven systems, such as predictive analytics or dynamic customer segmentation.

Barriers to AI Adoption in Small Retail Businesses

Despite the potential benefits of AI, several challenges hinder its adoption among small businesses, especially kirana shops in semi-urban and rural areas like Vidarbha:

Financial Constraints:

AI systems require significant investment in software, hardware, and training. Small retailers with limited financial resources find it difficult to justify such expenses (Singh et al., 2021). A study by FICCI (2022) highlighted that 75% of small business owners in India perceive AI solutions as prohibitively expensive.

Lack of Awareness and Knowledge:

Many small business owners lack awareness of AI technologies and their potential applications. Even when aware, a lack of technical expertise prevents effective implementation (Gupta et al., 2020). This knowledge gap is particularly pronounced in regions like Vidarbha, where digital literacy levels are relatively low.

Infrastructure Gaps:

Rural and semi-urban areas often face challenges related to poor internet connectivity and unreliable electricity supply, which are critical for deploying AI solutions (Chakraborty and Mishra, 2021). Vidarbha, being a predominantly agrarian region, faces these infrastructural limitations.

Resistance to Change:

Small retailers, accustomed to traditional ways of doing business, often resist adopting new technologies due to fear of complexity or disruption of established practices (Bhatia and Chandra, 2019).

Theoretical Frameworks for Understanding AI Adoption

The adoption of AI in small businesses can be analyzed through various theoretical frameworks:

Technology Acceptance Model (TAM):

Developed by Davis in 1989, TAM provides a framework for understanding how users accept and use new technologies. It posits that two key perceptions influence adoption: (1) Perceived Usefulness — the belief that the technology will enhance job performance, and (2) Perceived Ease of Use — the belief that the technology will be effortless to operate. Applying this to kirana shops, a billing software system that automates calculations and is easy to navigate is more likely to be adopted by shop owners, particularly if it reduces their daily workload.

Diffusion of Innovations (DOI) Theory:

Everett Rogers’ (2003) Diffusion of Innovation theory explains how new ideas and technologies spread through communities over time. It identifies five key attributes influencing adoption: relative advantage, compatibility, complexity, trialability, and observability. For kirana shops in semi-urban Vidarbha, if one shop begins using AI tools and visibly benefits through improved customer engagement or stock management, neighbouring shops are more inclined to emulate the innovation. The social proof and perceived low risk can significantly accelerate technology adoption in close-knit retail communities.

Resource-Based View (RBV):

RBV emphasizes the role of a business’s internal resources in determining its competitive advantage (Barney, 1991). Small retailers with limited financial and human resources may struggle to adopt AI technologies, highlighting the need for external support mechanisms.

AI Potential for Kirana Shops in Vidarbha

AI offers transformative potential for kirana shops, even in regions like Vidarbha, where digital adoption is still in its early stages. Potential applications include:

Predictive Analytics for Inventory Management:

AI tools can analyze historical sales data to forecast demand, helping shop owners optimize inventory levels and reduce waste (Singh et al., 2020).

Personalized Marketing:

AI-powered customer relationship management (CRM) systems can segment customers based on purchase history and preferences, enabling kirana shops to deliver targeted promotions and improve customer loyalty (Pradhan et al., 2022).

Chatbots for Customer Engagement:

AI-driven chatbots can handle routine customer inquiries, such as product availability and pricing, freeing up shop owners to focus on other tasks (Jain and Singhal, 2021).

Dynamic Pricing Models:

AI systems can adjust prices dynamically based on market demand and competitor pricing, allowing kirana shops to remain competitive with organized retail and e-commerce platforms (Chakraborty and Mishra, 2021).

Research Gap

The adoption of artificial intelligence (AI) in retail has received considerable attention in recent years, particularly in the context of organized retail and e-commerce. However, a critical gap exists in understanding how AI technologies can be effectively applied in the unorganized retail sector, such as kirana shops, especially in semi-urban and rural regions like Vidarbha. This section elaborates on the key aspects of the research gap by analyzing various dimensions—sectoral focus, geographical emphasis, technological readiness, and the transitional phase from basic digital tools to advanced AI systems.

Sectoral Focus: Organized vs. Unorganized Retail

Existing literature predominantly explores the role of AI in organized retail and e-commerce platforms. Studies have highlighted how AI enhances operational efficiency, improves customer engagement, and increases profitability for large retailers such as Walmart, Amazon, and Flipkart (Smith and Linden, 2017; McKinsey, 2021). These businesses have the resources, technical expertise, and infrastructure to adopt advanced AI technologies like dynamic pricing models, inventory management systems, and AI-powered customer relationship management (CRM) tools.

In contrast, unorganized retail, which constitutes approximately 88% of the Indian retail market (FICCI, 2022), remains underrepresented in research. Kirana shops, as a significant part of this sector, rely heavily on traditional practices and are slow to adopt advanced technologies due to financial and logistical constraints (Haque and Ghosh, 2020). While there are studies on the use of basic digital tools, such as social media and POS systems, for small businesses, research focusing on the application and potential of AI in kirana shops is scarce.

Geographical Emphasis: Urban vs. Semi-Urban/Rural

Most studies on AI adoption in retail are urban-centric, focusing on metropolitan areas where technology infrastructure, consumer awareness, and financial resources are more advanced (KPMG, 2020). Large-scale organized retail outlets in cities benefit from AI adoption due to higher consumer traffic and better access to technology. Urban customers are also more familiar with AI-driven personalized services, such as chatbot interactions, recommendation systems, and tailored marketing campaigns.

However, semi-urban and rural areas, such as Vidarbha, present a vastly different retail environment. The region’s kirana shops operate in communities where internet penetration is inconsistent, digital literacy is limited, and infrastructure gaps pose significant challenges (Chakraborty and Mishra, 2021). Research specific to the technological realities and socio-economic conditions of such regions is limited, leaving a gap in understanding how AI can be adapted to their unique needs.

Technological Readiness: Basic Digital Tools vs. Advanced AI Systems

The journey toward digital transformation in retail typically begins with the adoption of basic digital tools, such as point-of-sale (POS) systems, inventory management software, and social media platforms for marketing. Studies have documented the increasing use of these tools by small retailers in India, noting their impact on customer engagement, operational efficiency, and financial performance (Jain and Singhal, 2021; Pradhan et al., 2022). However, the transition from basic digital tools to advanced AI systems remains largely unexplored in the literature.

For instance, while POS systems are widely used for billing and stock tracking, they lack the predictive capabilities of AI-powered inventory management systems. Similarly, social media platforms like Facebook and Instagram enable kirana shop owners to promote products and connect with customers, but they do not offer the advanced segmentation and personalization features provided by AI-driven CRM tools. Research has not sufficiently addressed how small retailers, particularly in semi-urban regions, can bridge this technological gap.

Adoption Barriers: Financial, Technical, and Behavioral

Numerous studies have identified barriers to AI adoption in small businesses, such as cost constraints, lack of technical expertise, and resistance to change (Gupta et al., 2020; Singh et al., 2021). However, these studies often generalize findings without considering the specific challenges faced by kirana shops in semi-urban and rural regions. Vidarbha, for example, experiences:

Financial Barriers: Kirana shop owners often operate on thin margins, making it difficult to invest in advanced AI tools. Research has not sufficiently explored financial models or government support mechanisms that could enable AI adoption in this sector.

Technical Barriers: Limited digital literacy and the absence of technical training hinder the effective use of AI tools. There is a lack of research on how training programs or simplified AI solutions can address this gap.

Behavioral Barriers: Many shop owners are reluctant to adopt new technologies due to fear of disrupting established business practices. While some studies have acknowledged this resistance, they rarely provide actionable insights on how to overcome it.

Lack of Context-Specific Solutions

AI solutions developed for organized retail are often not suited for the operational scale and customer dynamics of kirana shops. For instance, dynamic pricing models and advanced recommendation engines require significant data inputs, which are unavailable to small retailers relying on cash transactions and manual bookkeeping. Most existing research does not address how AI can be tailored to the specific needs of kirana shops, such as:

Simplified AI tools that require minimal technical expertise.

Offline-capable AI systems to mitigate internet connectivity issues.

Cost-effective models that align with the financial realities of small businesses.

There is also limited research on how government initiatives like Digital India or Make in India can be leveraged to develop AI solutions for the unorganized retail sector.

Sociocultural Dynamics

The adoption of technology in small businesses is influenced not only by economic and technical factors but also by sociocultural dynamics. In semi-urban and rural regions like Vidarbha, customer expectations, trust in technology, and cultural attitudes toward innovation play a significant role in determining the success of AI implementation. However, these sociocultural dimensions are often overlooked in the literature, resulting in a one-size-fits-all approach to AI adoption strategies.

In summary, the research gap lies in the limited understanding of:

How kirana shops, as part of the unorganized retail sector, can transition from basic digital tools to advanced AI systems.

The specific challenges faced by kirana shop owners in semi-urban and rural regions, such as Vidarbha, in adopting AI technologies.

Context-specific AI solutions tailored to the financial, technical, and operational realities of small retailers.

The role of sociocultural factors in influencing AI adoption in unorganized retail.

Addressing these gaps is critical for enabling the digital transformation of kirana shops and ensuring their competitiveness in an increasingly technology-driven retail environment.

METHODOLOGY

This study employs secondary data analysis to explore digital adoption and AI potential in Vidarbha’s kirana shops. The data sources include:

Industry Reports: Reports from organizations like FICCI and ASSOCHAM on the retail sector’s digital transformation in India.

Academic Literature: Peer-reviewed studies on AI and small business marketing practices.

Case Studies: Documented examples of kirana shops adopting digital tools in semi-urban and rural settings.

Secondary data was analyzed to identify trends, benefits, challenges, and opportunities for AI integration.

RESULTS AND DISCUSSION

This section presents a detailed analysis of the findings derived from secondary data and discusses the implications of these findings for kirana shops in Vidarbha. It addresses the current use of digital tools, evaluates their impact on service marketing, and identifies challenges and opportunities for adopting advanced AI technologies. The discussion links these findings to broader trends in the retail sector and provides actionable insights for stakeholders.

Current Use of Digital Tools

The secondary data analysis reveals that kirana shops in Vidarbha are in the early stages of digital transformation. Their reliance on basic digital tools demonstrates an incremental approach to technology adoption.

Office Automation Software

Office automation tools, such as billing and inventory management systems, are among the most widely used digital technologies in Vidarbha’s kirana shops. These tools provide essential functionalities, including generating invoices, tracking sales, and maintaining basic stock records.

Efficiency Gains: Automation tools have reduced manual errors in billing and simplified inventory management. For instance, shop owners using digital inventory systems reported fewer stockouts and better tracking of fast-moving items.

Limitations: However, these systems lack predictive capabilities, such as forecasting demand or analyzing sales trends, which are critical for long-term operational efficiency.

Social Media Platforms

Platforms like Facebook and Instagram are extensively used for service marketing. Kirana shop owners use these tools to:

Showcase products with images and videos.

Announce offers and discounts, particularly during festivals.

Interact with customers through comments and direct messaging.

For example, shop owners observed increased customer engagement during festive campaigns where they promoted special discounts via social media. However, these platforms primarily serve as communication channels and do not provide advanced analytics or customer segmentation features.

Messaging Apps

Messaging platforms like WhatsApp are gaining popularity for direct customer engagement. Shop owners use WhatsApp to:

Send personalized offers to frequent customers.

Accept orders and coordinate deliveries.

Collect feedback on products and services.

Key Insight: While these tools have brought immediate benefits, they fall short of leveraging advanced AI functionalities, such as customer behavior analysis, automated follow-ups, and personalized recommendations.

Benefits of Existing Digital Practices

The adoption of basic digital tools has resulted in several tangible benefits for kirana shops in Vidarbha:

Enhanced Customer Engagement

Social media platforms and messaging apps have improved customer communication, enabling shop owners to foster stronger relationships with their clientele. Customers appreciate the convenience of placing orders via WhatsApp and receiving timely updates on promotions.

Increased Sales and Visibility

Promotional campaigns on social media have boosted sales during festive seasons and special events. Shop owners who actively use Instagram reported a 20–30% increase in footfall during promotional campaigns.

Operational Efficiency

Automation tools have significantly reduced the time and effort required for administrative tasks, such as billing and stock management. This allows shop owners to focus more on customer service and strategic decision-making.

Barriers to AI Adoption

Despite the benefits of basic digital tools, the transition to advanced AI technologies faces several challenges:

Financial Constraints

The high cost of AI tools, such as customer analytics platforms and dynamic pricing models, is a major deterrent. For kirana shops operating on thin profit margins, investing in such technologies is perceived as a significant financial risk.

Example: A typical AI-powered CRM system, which can cost several thousand rupees annually, is out of reach for most kirana shop owners in Vidarbha.

Technical Expertise

AI tools require a certain level of technical proficiency to implement and manage. Many shop owners in Vidarbha lack the necessary digital literacy to utilize these tools effectively.

Infrastructure Challenges

Poor internet connectivity and frequent power outages in rural areas further hinder the adoption of AI technologies. For instance, cloud-based AI systems cannot function reliably in regions with inconsistent connectivity.

Resistance to Change

Shop owners accustomed to traditional business practices are often reluctant to adopt new technologies. They perceive AI tools as complex and fear that their implementation may disrupt established workflows.

Barrier	Explanation	Proposed Solutions
Financial Constraints	Most kirana shop owners operate on limited margins and find it challenging to invest in new tools.	Government subsidies, low-interest loans, and phased pricing models for affordable AI technology.
Technical Skill Gaps	Lack of formal education or exposure to digital tools hampers technology usage.	Local language training programs, simplified mobile apps, and vendor support during onboarding.
Infrastructure Deficiencies	Poor internet connectivity and power supply in rural Vidarbha affect the reliability of digital tools.	Promote offline-capable AI solutions and invest in digital infrastructure through public-private partnerships.
Cultural Resistance	Traditional business practices are deeply ingrained; change is often perceived as risky.	Conduct awareness campaigns showcasing success stories and offer trial opportunities with no risk upfront.

Table: – Barriers and Solutions for AI Adoption in Kirana Shops

Opportunities for AI Integration

While barriers exist, there are significant opportunities to integrate AI into service marketing for kirana shops in Vidarbha:

Predictive Analytics for Inventory Management

AI-powered inventory management systems can analyze historical sales data to predict demand, helping shop owners optimize stock levels. This reduces the risk of overstocking or running out of high-demand items.

Example: A kirana shop could use predictive analytics to identify seasonal demand for specific products, such as festive sweets or snacks, and stock accordingly.

Personalized Marketing and CRM

AI-driven customer relationship management (CRM) systems can segment customers based on their purchase history and preferences. This enables kirana shops to deliver targeted promotions and personalized recommendations, fostering customer loyalty.

Example: A CRM tool could automatically send a discount offer for a frequently purchased product to a specific customer segment.

AI-Powered Chatbots

Chatbots can automate routine customer interactions, such as responding to product inquiries or confirming order statuses. This reduces the workload for shop owners and ensures timely responses to customer queries.

Dynamic Pricing Models

AI tools can analyze market trends, competitor pricing, and demand patterns to dynamically adjust prices, helping kirana shops remain competitive with organized retail and e-commerce platforms.

Affordable AI Solutions

Government initiatives like Digital India and collaborations with technology providers could enable the development of cost-effective AI tools tailored to the needs of small businesses.

Implications for Stakeholders

The findings of this study have several implications for different stakeholders:

For Kirana Shop Owners

Embracing affordable and user-friendly AI tools can enhance customer engagement and operational efficiency.

Participating in digital literacy programs can improve their ability to adopt and manage new technologies.

For Policymakers

Government-led initiatives, such as subsidies and grants, can reduce the financial burden of adopting AI technologies.

Investments in rural infrastructure, including internet connectivity and reliable electricity, are essential for enabling digital transformation.

For Technology Providers

Simplifying AI solutions and offering them at affordable prices can increase adoption rates among small retailers.

Providing training and support to kirana shop owners can address technical skill gaps.

Figure 1: A visual model of the transformation pathway for kirana shops, showing how gradual adoption of technology—from POS systems to AI tools—can improve competitiveness and service marketing.

Comparison with Previous Research

The findings align with existing research highlighting the benefits of basic digital tools in small businesses (Jain and Singhal, 2021). However, this study uniquely focuses on the unorganized retail sector in Vidarbha, offering insights into region-specific challenges and opportunities for AI integration. While previous studies have largely emphasized urban retail settings, this study highlights the potential for AI-driven transformation in semi-urban and rural contexts.

CONCLUSION AND RECOMMENDATIONS

The conclusion synthesizes the key findings of the study and underscores the importance of addressing the challenges faced by kirana shops in Vidarbha to enable their digital transformation. The recommendations provide actionable steps for stakeholders, including kirana shop owners, policymakers, and technology providers, to foster the integration of artificial intelligence (AI) into the unorganized retail sector.

Conclusion

Kirana shops in Vidarbha form the backbone of the region’s retail sector, serving as essential suppliers of goods in semi-urban and rural areas. Despite their critical role, these shops face increasing competition from organized retail chains and e-commerce platforms, which leverage AI to enhance customer experience, operational efficiency, and profitability.

This study reveals that kirana shop owners in Vidarbha are in the early stages of digital transformation, with most relying on basic digital tools like office automation software and social media platforms. These tools have delivered measurable benefits, such as improved customer engagement, increased visibility, and enhanced operational efficiency. However, the adoption of advanced AI technologies remains minimal due to significant barriers, including financial constraints, lack of technical expertise, and infrastructure limitations.

The study highlights the immense potential of AI to revolutionize service marketing for kirana shops. AI-powered tools, such as predictive analytics, dynamic pricing models, and personalized customer relationship management (CRM) systems, could help kirana shops improve their competitiveness and customer loyalty. However, realizing this potential requires overcoming the identified barriers and developing region-specific solutions that cater to the unique needs of semi-urban and rural retailers.

The findings emphasize the need for a multi-stakeholder approach to foster AI adoption in kirana shops. By addressing financial, technical, and infrastructural challenges, stakeholders can empower kirana shop owners to harness the transformative power of AI, ensuring their sustainability in a rapidly evolving retail landscape.

Recommendations

To facilitate the adoption of AI technologies in kirana shops in Vidarbha, this study offers detailed recommendations for key stakeholders.

Recommendations for Kirana Shop Owners

Start with Affordable, Incremental Upgrades

Shop owners should begin their transition to AI by adopting affordable, user-friendly tools that require minimal technical expertise, such as AI-integrated point-of-sale (POS) systems.

Leveraging AI features gradually, such as automated inventory suggestions or customer feedback analysis, can provide immediate benefits without overwhelming the shop owner.

Leverage Social Media Analytics

Many social media platforms, like Instagram and Facebook, offer built-in analytics tools that provide insights into customer behavior and engagement metrics. Shop owners should use these tools to refine their marketing strategies.

Participate in Training Programs

Attending workshops or online courses on digital marketing and AI tools can help shop owners build the technical skills needed to use these technologies effectively. Local trade associations or NGOs could organize such programs in regional languages to ensure inclusivity.

Recommendations for Policymakers

Provide Financial Incentives for AI Adoption

Introduce subsidies, tax breaks, or low-interest loans specifically for small businesses to invest in AI technologies.

For example, the government could launch a scheme under Digital India to promote AI-powered POS systems and CRM tools for kirana shops.

Improve Infrastructure in Semi-Urban and Rural Areas

Invest in improving internet connectivity and ensuring stable electricity supply in rural and semi-urban areas like Vidarbha. These are prerequisites for effective AI implementation.

Partnering with private telecom providers to expand high-speed internet services to underserved areas can address connectivity issues.

Launch AI Awareness Campaigns

Conduct awareness campaigns in regional languages to educate shop owners about the benefits and practical applications of AI in retail.

Policymakers could collaborate with local trade associations to create targeted outreach programs.

Recommendations for Technology Providers

Develop Cost-Effective AI Solutions

Technology providers should create affordable AI tools tailored to the needs of small businesses.

For instance, lightweight AI applications that operate offline or require minimal internet connectivity could address the infrastructural challenges in Vidarbha.

Offer Training and Support Services

Providing end-to-end support, from installation to training, can help overcome the technical barriers to AI adoption.

Offering helplines and tutorials in regional languages ensures that shop owners feel confident in using these tools.

Collaborate with Government and NGOs

Technology providers can partner with government agencies and NGOs to scale the distribution of AI tools. Such collaborations could include pilot programs that demonstrate the benefits of AI adoption in small businesses.

Recommendations for Industry Associations and NGOs

Organize Digital Literacy Campaigns

Industry associations and NGOs can play a critical role in organizing digital literacy campaigns for kirana shop owners in Vidarbha.

These campaigns should focus on building familiarity with digital tools, from social media marketing to basic AI applications, and emphasize their practical benefits.

Facilitate Peer-to-Peer Learning

Establishing peer networks where shop owners who have successfully adopted AI share their experiences and strategies can inspire others to follow suit.

Industry associations could organize events or forums for knowledge-sharing within local business communities.

Recommendations for Academia and Researchers

Conduct Region-Specific Studies

Researchers should conduct longitudinal studies on AI adoption in semi-urban and rural retail sectors to assess the long-term impact of these technologies.

Studies focusing on the socio-economic context of regions like Vidarbha can provide actionable insights for stakeholders.

Develop AI Toolkits for Small Businesses

Collaborating with technology providers, researchers can develop simplified AI toolkits that address the specific needs of small retailers in semi-urban and rural areas.

Implications for the Future

By implementing these recommendations, stakeholders can create an enabling environment for the digital transformation of kirana shops in Vidarbha. Such transformation will not only enhance the competitiveness of these businesses but also contribute to the broader goals of economic growth and digital inclusion in India.

The adoption of AI in kirana shops has the potential to bridge the gap between unorganized and organized retail sectors, ensuring that local businesses remain relevant in an increasingly technology-driven marketplace. Policymakers, technology providers, and academia must collaborate to drive this change and unlock the transformative potential of AI for small retailers.

Broader Implications for Indian Retail

The integration of artificial intelligence into the operations of kirana shops carries significant implications for the broader Indian retail ecosystem. These shops, which make up the backbone of unorganized retail in India, serve millions of consumers across urban and rural landscapes. Enabling these shops with smart technologies can help reduce the widening gap between organized and unorganized retail sectors.

Firstly, AI-enabled kirana shops will be better equipped to meet evolving consumer expectations — faster service, better product availability, and personalized experiences. This not only enhances customer satisfaction but ensures the continued relevance of small retailers amid rising competition from large e-commerce platforms.

Secondly, empowering local retailers with technology can stimulate local economies. For instance, as shops grow more efficient, there is potential to generate new employment opportunities — in logistics, marketing, IT support, and digital payment facilitation. This localized growth model supports India’s broader goals of inclusive digital development.

Thirdly, a digitally literate small retailer ecosystem can act as a distribution backbone for national policy goals — from digital payment adoption to last-mile delivery of government schemes and subsidies.

By democratizing access to AI and digital tools, India can achieve a more equitable retail environment where small entrepreneurs thrive alongside corporate players.

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Conflict of Interest Declaration

Author declare that there are no conflicts of interest related to this research paper. The research, analysis, and conclusions presented in this study are solely the authors’ original work and have not been influenced by any personal, financial, or professional affiliations or relationships that could create a conflict of interest.