Artificial Intelligence and Bias: Questions, Challenges and Opportunities for Entrepreneurship

Call for Papers – Artificial Intelligence and Bias: Questions, Challenges and Opportunities for Entrepreneurship

Journal: International Journal of Entrepreneurial Behavior & Research
Publisher: Emerald Publishing

Submission window: 1 July 2026 – 31 August 2026

This special issue explores how artificial intelligence (AI) and AI‑induced bias shape entrepreneurship, innovation, and organisational behaviour—both as a source of risk and as a springboard for new opportunities. It seeks research that connects AI bias (in data, algorithms, and human–AI interaction) with entrepreneurial processes, decision‑making, and societal outcomes, and asks how entrepreneurship can help build fairer, more inclusive, and sustainable AI‑driven ecosystems.

Why this issue matters

• AI is reshaping opportunity recognition, innovation, and value‑creation processes across sectors, but biased AI systems can reinforce discrimination, under‑represent marginalised groups, and erode trust in entrepreneurial ventures.

• At the same time, the growing need to detect, measure, and mitigate AI bias creates entrepreneurial opportunities in AI‑fairness services, explainable‑AI tools, auditing platforms, and inclusive business models.

• This SI responds to an emerging research gap at the intersection of entrepreneurship and AI‑bias scholarship, and aligns with broader debates on responsible innovation, digital ethics, and the Sustainable Development Goals (SDGs).

Key themes and topic areas

Submissions may be theoretical, empirical, or practice‑oriented, and should clearly link AI‑related bias to entrepreneurial settings and outcomes.

• AI bias and entrepreneurial processes

  • How AI‑driven tools affect opportunity detection, new‑venture creation, scaling, and internationalisation.

  • Case studies of AI‑biased decisions in start‑ups and small firms across sectors (e.g., fintech, healthtech, edtech, retail).

• AI bias in innovation processes across industries

  • Examples where AI‑biased algorithms distort product development, customer targeting, or service personalisation.

  • Entrepreneurial innovation in bias‑detection tools, fairness‑enhancing technologies, and inclusive AI‑solutions.

• Entrepreneurship and mitigation of AI bias

  • New business models focused on AI‑fairness audit, certification, consulting, and bias‑management platforms.

  • Startups and SMEs pioneering inclusive design, diverse data strategies, and equitable AI‑access policies.

• AI bias, entrepreneurial and organisational culture

  • How entrepreneurial and organisational cultures shape awareness, governance, and resistance to AI‑related bias.

  • Roles of ethical leadership, transparency, and stakeholder engagement in AI‑driven ventures.

• AI, big data management, and business opportunities

  • Use of AI and big‑data analytics to identify new markets, optimise offerings, and create platforms.

  • Risks of data‑driven discrimination, privacy violations, and surveillance‑based business models in entrepreneurial contexts.

• Biased AI adoption in entrepreneurial settings

  • Empirical work on how start‑ups, incubators, accelerators, and SMEs adopt AI tools and the resulting bias in hiring, lending, marketing, and customer service.

  • Regulatory and policy environments that influence responsible AI‑entrepreneurship.

• AI bias and entrepreneurial decision‑making

  • Impact of AI‑assisted decisions on investment choices, resource allocation, and partnership strategies.

  • Human–AI interaction, cognitive bias, and uncertainty under AI‑supported conditions.

• AI bias, entrepreneurship, and sustainable society

  • Linking AI‑bias research with social innovation, inclusion, and SDG‑related themes (e.g., reduced inequalities, decent work, responsible consumption).

  • Entrepreneurial roles in inclusive AI ecosystems, digital‑rights initiatives, and community‑driven AI‑governance.

• Methodologies for AI‑bias management

  • New methods, metrics, or frameworks for identifying, measuring, and mitigating AI bias in entrepreneurial contexts.

  • Mixed‑methods, action‑research, or participatory designs involving entrepreneurs, communities, and regulators.

Guest editors

• Prof. Francesco Schiavone, University of Naples Parthenope, Italy

• Dr. Tais Siqueira Barreto, Nova Southeastern University, USA

• Dr. Anna Bastone, University of Naples Parthenope, Italy

Submission details

• Submission portal: ScholarOne Manuscripts for International Journal of Entrepreneurial Behavior & Research:
  https://mc.manuscriptcentral.com/ijebr

• Authors must select the Special Issue title (“Artificial Intelligence and Bias: Questions, Challenges and Opportunities for Entrepreneurship”) under the “Please select the issue you are submitting to” field.

• Key dates:

  • Submission opening: 1 July 2026

  • Submission closing: 31 August 2026

• Manuscripts must be original, unpublished, and not under review elsewhere while under consideration for the journal.

• All submissions must follow the journal’s Author Guidelines:
  https://www.emeraldgrouppublishing.com/journal/ijebr#jlp_author_guidelines

Papers should clearly articulate where and how AI‑related bias emerges in entrepreneurial settings, and how entrepreneurship can both respond to bias risks and leverage them as opportunities for responsible innovation.

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