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Introduction
Partner Organisation: Canberra Business Chamber, Australia.
Canberra Business Chamber (CBC) is the voice of business in the Canberra Region located in the Australian Capital Territory (ACT). Established in 1934, the chamber has been helping businesses start, grow, and transform. The CBC is a member-based not for profit organisation that also represents many of the ACT’s key industry associations and community organisations. As the peak body for the Canberra Region’s private sector, the key purpose is to drive the economic prosperity and growth of the ACT through business.
https://www.canberrabusiness.com/
Practical Challenge
A recent survey found that 65 percent of respondents reported that their organizations regularly use Generative AI (Gen AI) , nearly double that of 10 months prior (McKinsey, 2024). One type of organisation that can benefit from Gen AI are small businesses. Gen AI allows small businesses to address the perennial business challenges of cost, time, skills and scale, and increase competitive advantage which can help ‘level the playing field’ (Acar and Gvirtz 2024). Examples of Gen AI tools that can assist small business are AI-generated video, customer insight tools, virtual assistants, (Acar and Gvirtz 2024).
However small businesses face challenges around AI implementation, including knowing where to begin the process, and the technical expertise in using and navigating AI tools (NSW Small Business Commissioner 2024). Concerns have also been raised around the privacy and security of data generated by AI as well as the biases in AI. (NSW Small Business Commissioner 2024).
Generative AI is becoming increasingly accessible to small businesses – there is a growing range of AI tools available at a price point that makes them accessible to almost any small business. Gen AI promises to deliver efficiencies and productivity improvements, enabling small businesses to deliver better services to customers (Acar and Gvirtz 2024). However, uptake is not without problems. The Canberra Business Chamber has identified four key issues for small business:
(i) there are potential confidentiality and privacy issues associated with using AI if the tools do not adequately protect and ringfence business data;
(ii) generative AI tools have not yet reached a maturity level where they are highly accurate, raising the prospect that their output could be erroneous, with potentially serious business consequences; and
(iii) there may still be consumer pushback and resistance to the use of generative AI by businesses, especially where the interaction is at the frontline interface with customers.
(iv) small businesses often lack the capacity to fully understand available technology solutions. They sometimes do not understand what they don't know or how to identify and mitigate the business risks involved in using Gen AI systems.
Therefore, this special issue will address the practical challenge of how small businesses might harness the benefits of Gen AI while minimizing the pitfalls associated with the adoption and deployment of this new technology. The special issue seeks to provide guidance and practical strategies to create positive social impact for business owners, employees and customers.
Practical challenge special issues are a unique feature of the Journal of Social Impact in Business Research. This type of special issue partners with a real world organisation who establish the purpose of the special issue. All submissions must directly address the stated practical challenge as well as a theoretical problem related to this challenge. The practical challenge partner will contribute a commentary article which responds directly to each article accepted in the special issue to identify the merits of each article and how the content can be used practically. In this way, practical challenge special issues not only generate knowledge on the social impact of a phenomenon, they also create evidence of social impact of the articles. This provides a high level of benefit to both the partner organisation and the author(s).
Background Literature
Gen AI refers to “computational techniques capable of generating seemingly new, meaningful content such as text, images, or audio from training data” (Feuerriegel et al., 2024, p111). Gen AI goes beyond the traditional AI focus of prediction and classification by creating original outputs that mimic human creativity. Technologies like DALL-E 2, GPT-4, Gemini, and Copilot are revolutionizing how we work and communicate, assisting not only with artistic tasks like generating text or videos, but also with practical functions such as IT support, validating business ideas, creating business processes, and providing medical advice (Feuerriegel et al., 2024). Nearly all human thinking and communication activities can be performed - to varying degrees of quality.
For business, Gen AI enhances customer experiences and streamlines decision-making. by automating knowledge work and personalizing content, As noted by Chui et al. (2023), it plays a growing role in boosting productivity and creating new economic opportunities, signaling a fundamental shift in how businesses operate, innovate, and engage with customers. Gen AI is advancing through developments such as multimodality, industry-specific fine-tuning, and deeper integration into creative and enterprise solutions. For example, OpenAI's GPT-4 now leverages multimodality by processing both text and images, enabling more comprehensive outputs, while fine-tuned models are being employed in healthcare to generate diagnostic insights based on medical records. Ethical concerns, regulation, and AI safety are also becoming more important alongside innovations like deepfake detection and personalized experiences. While much research focuses on the impact on large corporations, there is growing interest in exploring generative AI's applications, benefits, and challenges for small businesses (Dwivedi et al., 2023). To date there is limited evidence in the small business sector who could greatly benefit from harnessing the power of these technologies. This benefit can be realised for business-owners, employees and customers.
The scientific business literature highlights both the potential and challenges of Gen AI for small and medium enterprises (SMEs). Norbäck and Persson (2024) argue that Gen AI fosters innovation through "creative destruction," encouraging new business models while minimizing disruption to existing firms. Rajaram and Tinguely (2024) show how SMEs can leverage Gen AI for greater efficiency in customer service, marketing, and operations, though tailored strategies are needed to navigate its complexities. Small businesses are positioned to lead GenAI adoption due to its scalability, but access to data and expertise remains a challenge (Grégoire et al. 2024). Huang and Rust (2021) discuss GenAI's ability to help SMEs deliver data-driven marketing, leveling the playing field with larger firms. Indeed, AI-powered chatbots can enhance customer service and stock performance, hinting at benefits for SMEs (Fotheringham and Wiles, 2023). Overall, SMEs can innovate and grow with GenAI, but overcoming resource limitations and investing in expertise are essential for success.
In particular, GenAI can create positive social impact for small business owners, employees and customers . Social impact is defined as the improvement in outcome phenomena that is a goal of society (Aiello et al 2021). The 17 United Nations Sustainable Development Goals (SDGs) provides a useful list of goals that represent social impact that can be translated into the small business sector. Using the SDG synthesised list (Russell-Bennett et al 2024), there is potential social impact of GenAI for the small business sector for all seven themes. For example, theme 2 Services that provide opportunity for all humans (SDG 4, 5 and 10) involves social impact outcomes for GenAI in small business of access to work by people with a disability. Likewise theme 3 Services that manage resources for all humans could involve social impact outcomes for GenAI in small business of efficiently and cost-effectively managing business supplies in a regenerative way. However to date, we do not know how GenAI can create these positive social impacts in the small business sector.
Despite the encouraging potential of Gen AI, current business literature on Gen AI and small and medium enterprises (SMEs) lacks a detailed exploration of key areas critical for understanding how these businesses can effectively adopt and benefit from AI technologies. In other words, what is the social impact of Gen AI for small businesses (business owners, employees and/or customers)? Research opportunities exist in how Gen AI offers SMEs unique prospects to automate tasks, personalize marketing efforts, enhance data-driven decision-making, and support rapid product innovation, which helps them remain competitive in dynamic markets and address labor shortages. Despite this potential, SMEs face specific challenges in GenAI adoption due to financial constraints, resource limitations, and lack of expertise. More research is needed on how SMEs can integrate Gen AI into workflows tailored to their needs, as well as on the role of external partnerships with technology providers, academic institutions, or other businesses in facilitating Gen AI adoption. Additionally, the impact of government policies on supporting SMEs through financial aid, training, and infrastructure development deserves further attention, as does the need to address issues like cybersecurity risks and data management challenges associated with Gen AI adoption. Lastly, there is a call for more studies on leveraging accessible AI-as-a-Service (AIaaS) platforms, which enable SMEs to adopt advanced AI tools without significant investment.
The overall purpose of this special issue is to create an evidence base for harnessing the power of Generative AI for Small Business to Create Social Impact: Enablers and Barriers. In doing so, this special issue seeks to examine the enablers and barriers for using Gen AI in terms of the social impact on business owners, employees and/or customers.
List of topic areas
We invite scholars, practitioners, and policymakers to contribute to our special issue and specifically address the practical challenge of the partner organisation outlined in this call for papers. We seek submissions that present innovative strategies, case studies, systematic literature reviews, empirical research, commentaries, policy papers, practice papers or viewpoints that shed light on how business research can provide useful guidance to small business can create positive social impact for business owners, employees and customers using Gen AI.
- How might positive social impact be created that address the SDGs by GenAI in the small business sector?
- Strategies for integrating multiple Gen AI tools in small businesses
- Bridging the competitive gap with larger firms and providing financial and wellbeing benefit to business owners
- Marketing through Gen AI: Analysing how Gen AI can help small businesses compete with larger corporations in content creation, market insights, and customer interaction.
- The social impact of business use of Gen AI for customer or employee wellbeing
- Identification of the barriers for small business to create social impact for business owners, employees or customers using Gen AI
- The use of multimodal Gen AI tools and their potential to enhance accessibility and productivity for small businesses.
- Case studies on how Gen AI impacts different sectors, highlighting innovation and social impact across industries.
- Identification of the mechanisms that explain how Gen AI enhances the innovation process and business agility for small businesses to create social impact.
- Success factors for small business use of Gen AI that creates positive social impact
- Gen AI strategies that address governance, privacy, and security concerns
- The use of Gen AI for improving sustainability efforts of small business
- Investigating how Gen AI supports small businesses in research, brainstorming, and data-driven decision-making, fostering innovation and social impact.
- Identifying the unique aspects of Gen AI in the small business sector compared to other sectors that can create social impact
- Small business governance and strategy surrounding Gen AI.
- Gen AI and its impact on small business productivity, including revenue, staffing and other cost and business function effects.
- Privacy and security factors surrounding Gen AI and small business data.
- Intellectual Property (IP) and other legal issues surrounding Gen AI for small business.
- Small Business case studies that demonstrate social impact through the use of Gen AI
Guest Editors
Professor Lorne Cummings, University of Canberra, [email protected]
Professor Dominik Mahr, Maastricht University, [email protected]
Mr Mark Steins, Maastricht University, [email protected]
Submissions Information
Submissions are made using ScholarOne Manuscripts. Author guidelines must be strictly followed.
Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to ““Please select the issue you are submitting to”.
Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.
Key deadlines
Opening date for manuscripts submissions: 01/03/2025
Closing date for manuscripts submission: 30/04/2025
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