Generative AI as a Co-Founder: How Language Models Mediate Entrepreneurial Communication and Early-Stage Traction
Generative AI as a Co-Founder: How Language Models Mediate Entrepreneurial Communication and Early-Stage Traction

Author(s): Muntaqim Meherab, Sanela Hossain, Azizur Rahman, Zarif Mahmud
Subject(s): Economy, Business Economy / Management, Marketing / Advertising, ICT Information and Communications Technologies
Published by: Университет за национално и световно стопанство (УНСС)
Keywords: generative AI; entrepreneurship; research agenda; rhetoric, persuasion; startup traction
Summary/Abstract: Generative language models now help founders draft the words that launch new ventures: pitch decks, landing pages, outreach emails, and product microcopy. We treat a capable LLM as an “AI co-founder” for the communication function and lay out a research agenda that links four micro-rhetorical levers – clarity, cohesion, specificity, and call-to-action (CTA) strength – to early traction: click-throughs, sign-ups, replies, and first sales. Building on evidence that wording can move behavior and that AI support may narrow capability gaps, we pose research questions about whether, how, and for whom AI-assisted language changes outcomes. We outline measurement strategies for the four levers, suggest study designs (observational pipelines, field A/B programs where feasible, and causal-mediation plans), and spell out equity, credibility, and safety considerations to guide future work. We close with a practitioner toolkit and open instruments to help founders apply these ideas and to make progress cumulative.

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