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Exploring the Role of Social Support when Integrating Generative AI into Small Business Workflows

Quentin Romero Lauro, Jeffrey P. Bigham, Yasmine Kotturi

TL;DR

This study addresses how small business owners integrate generative AI into their workflows through offline social networks. Using 11 semi-structured interviews and storyboard probes with seven entrepreneurs and four support staff, the authors show that local, informal networks facilitate shared use of single-user AI tools, enabling prompt learning, collaboration, and discovery of new applications, while also mitigating techno-anxiety. However, social contexts introduce tensions around reputation, embarrassment, and unclear norms, which can impede adoption. The work contributes empirical insights on designing generative AI for social contexts in lean entrepreneurship, suggesting interfaces that support coopetition and configurable information sharing to balance cooperation with privacy and IP concerns. The findings have practical implications for building AI platforms that acknowledge the social fabric of small-business ecosystems and provide wrap-around, socially aware support mechanisms.

Abstract

Small business owners stand to benefit from generative AI technologies due to limited resources, yet they must navigate increasing legal and ethical risks. In this paper, we interview 11 entrepreneurs and support personnel to investigate existing practices of how entrepreneurs integrate generative AI technologies into their business workflows. Specifically, we build on scholarship in HCI which emphasizes the role of small, offline networks in supporting entrepreneurs' technology maintenance. We detail how entrepreneurs resourcefully leveraged their local networks to discover new use cases of generative AI (e.g., by sharing accounts), assuage heightened techno-anxieties (e.g., by recruiting trusted confidants), overcome barriers to sustained use (e.g., by receiving wrap-around support), and establish boundaries of use. Further, we suggest how generative AI platforms may be redesigned to better support entrepreneurs, such as by taking into account the benefits and tensions of use in a social context.

Exploring the Role of Social Support when Integrating Generative AI into Small Business Workflows

TL;DR

This study addresses how small business owners integrate generative AI into their workflows through offline social networks. Using 11 semi-structured interviews and storyboard probes with seven entrepreneurs and four support staff, the authors show that local, informal networks facilitate shared use of single-user AI tools, enabling prompt learning, collaboration, and discovery of new applications, while also mitigating techno-anxiety. However, social contexts introduce tensions around reputation, embarrassment, and unclear norms, which can impede adoption. The work contributes empirical insights on designing generative AI for social contexts in lean entrepreneurship, suggesting interfaces that support coopetition and configurable information sharing to balance cooperation with privacy and IP concerns. The findings have practical implications for building AI platforms that acknowledge the social fabric of small-business ecosystems and provide wrap-around, socially aware support mechanisms.

Abstract

Small business owners stand to benefit from generative AI technologies due to limited resources, yet they must navigate increasing legal and ethical risks. In this paper, we interview 11 entrepreneurs and support personnel to investigate existing practices of how entrepreneurs integrate generative AI technologies into their business workflows. Specifically, we build on scholarship in HCI which emphasizes the role of small, offline networks in supporting entrepreneurs' technology maintenance. We detail how entrepreneurs resourcefully leveraged their local networks to discover new use cases of generative AI (e.g., by sharing accounts), assuage heightened techno-anxieties (e.g., by recruiting trusted confidants), overcome barriers to sustained use (e.g., by receiving wrap-around support), and establish boundaries of use. Further, we suggest how generative AI platforms may be redesigned to better support entrepreneurs, such as by taking into account the benefits and tensions of use in a social context.
Paper Structure (16 sections, 3 figures, 1 table)

This paper contains 16 sections, 3 figures, 1 table.

Table of Contents

  1. Introduction
  2. Related Work
  3. Entrepreneurship in the Digital Age
  4. Generative AI in HCI
  5. Methodology
  6. Interviews
  7. Part 1: Background questions
  8. Part 2: Storyboards as Probes
  9. Data Analysis
  10. Findings
  11. Forms of Social Support, and Benefits
  12. Tensions of Social Support
  13. Limitations
  14. Discussion and Future Work
  15. Conclusion
  16. ...and 1 more sections

Figures (3)

  • Figure 1: Storyboard 9 probed how entrepreneurs may provide each other with informal social support alongside more formal resources kotturi2024deconstructing. In this storyboard, vetted peers who met at a local community center use a browser and chat-based generative AI platform collaboratively---when they cannot make it to the center---by seeing and building off of each others' prompts, and holding each other accountable to continued support.
  • Figure 2: Storyboard 17 probed how a SMS-based system for social use of generative AI may meet entrepreneurs where are by leveraging an existing technology piggybackPrototyping10.1145/3491102.3517708 to more readily share helpful prompts with other entrepreneurs. Similarly to Storyboard 9, this storyboard considers how entrepreneurs can support each other when they are unable to make it in person to their community center.
  • Figure 3: Storyboard 26 probed how entrepreneurs can learn about integrating generative AI into their business workflows by learning from peers in their local community center, specifically through watching demonstrative videos by those in their community.