The Role of Artificial Intelligence in Evolving the Theory of Effectuation Within Entrepreneurial Practice

Abstract

The Fourth Industrial Revolution, characterized by rapid advancements in artificial intelligence (AI), is transforming industries and redefining business practices globally. This thesis examines how AI impacts the application of Sarasvathy's Effectuation Theory within the entrepreneurial processes of early-stage startups. Effectuation Theory, which focuses on leveraging available means and making adaptive decisions under uncertainty, is re-evaluated considering AI's capabilities. The research employs a qualitative methodology, utilizing in-depth interviews with startup founders and AI experts to gather insights.

Findings reveal that AI significantly enhances entrepreneurial efficiency by automating routine tasks, enabling sophisticated data analysis, and facilitating rapid decision-making. AI's ability to predict market trends and optimize operations allows entrepreneurs to navigate uncertainties with greater precision and agility. However, the reliance on AI for innovation presents limitations, as AI excels in optimization but falls short in generating truly disruptive ideas. Human creativity and strategic thinking remain indispensable for groundbreaking innovation.

The study also explores the ethical considerations and challenges associated with AI integration, including data privacy, potential biases, and job displacement. Despite these challenges, AI democratizes access to advanced technologies, leveling the playing field between small startups and large corporations.

This research contributes to the ongoing dialogue on entrepreneurship in the digital era, suggesting that Effectuation Theory should incorporate AI as a core resource. The enhanced decision-making and operational capabilities provided by AI necessitate an augmentation of entrepreneurial strategies, blending AI's analytical strengths with human creativity to drive sustainable growth and innovation.

The Fourth Industrial Revolution, characterized by rapid advancements in artificial intelligence (AI), is transforming industries and redefining business practices globally. This thesis examines how AI impacts the application of Sarasvathy's Effectuation Theory within the entrepreneurial processes of early-stage startups. Effectuation Theory, which focuses on leveraging available means and making adaptive decisions under uncertainty, is re-evaluated considering AI's capabilities. The research employs a qualitative methodology, utilizing in-depth interviews with startup founders and AI experts to gather insights.

Findings reveal that AI significantly enhances entrepreneurial efficiency by automating routine tasks, enabling sophisticated data analysis, and facilitating rapid decision-making. AI's ability to predict market trends and optimize operations allows entrepreneurs to navigate uncertainties with greater precision and agility. However, the reliance on AI for innovation presents limitations, as AI excels in optimization but falls short in generating truly disruptive ideas. Human creativity and strategic thinking remain indispensable for groundbreaking innovation.

The study also explores the ethical considerations and challenges associated with AI integration, including data privacy, potential biases, and job displacement. Despite these challenges, AI democratizes access to advanced technologies, leveling the playing field between small startups and large corporations.

This research contributes to the ongoing dialogue on entrepreneurship in the digital era, suggesting that Effectuation Theory should incorporate AI as a core resource. The enhanced decision-making and operational capabilities provided by AI necessitate an augmentation of entrepreneurial strategies, blending AI's analytical strengths with human creativity to drive sustainable growth and innovation.