The growing availability of Artificial Intelligence (AI) tools is reshaping entrepreneurship education, particularly within design-driven approaches to startup creation. While AI is increasingly used to support entrepreneurial activities, there is still limited understanding of how it influences the different phases of the startup creation process in higher education contexts. This paper investigates the role of AI within a design-driven startup education course, where students develop entrepreneurial ideas from opportunity identification to business model definition. The course integrates design methodologies with entrepreneurial and managerial tools, supporting students in navigating uncertainty, feasibility, and strategic decision-making. A structured survey was administered to students to assess the extent of AI usage and its perceived usefulness across key phases of the startup process, including opportunity identification, need analysis, concept development, market exploration, and business model definition. The results show that AI is perceived as particularly useful in early and analytical phases, where it supports information gathering, synthesis, and the exploration of alternative solutions. In these stages, AI functions as a cognitive amplifier, helping students navigate uncertainty and structure complex inputs. However, its perceived usefulness decreases in more strategic and decision-intensive phases, where human judgment, critical thinking, and responsibility become central. These findings highlight a tension between the exploratory potential of AI and its tendency toward risk-averse reasoning. From an educational perspective, this suggests framing AI as a cognitive sparring partner that stimulates thinking without replacing decision-making. The study contributes to the design of startup education models that leverage AI while preserving the uncertainty and risk that are fundamental to innovation-driven entrepreneurship.

Exploring the role of artificial intelligence in design-driven startup education

G. Carella;M. Conte
2026-01-01

Abstract

The growing availability of Artificial Intelligence (AI) tools is reshaping entrepreneurship education, particularly within design-driven approaches to startup creation. While AI is increasingly used to support entrepreneurial activities, there is still limited understanding of how it influences the different phases of the startup creation process in higher education contexts. This paper investigates the role of AI within a design-driven startup education course, where students develop entrepreneurial ideas from opportunity identification to business model definition. The course integrates design methodologies with entrepreneurial and managerial tools, supporting students in navigating uncertainty, feasibility, and strategic decision-making. A structured survey was administered to students to assess the extent of AI usage and its perceived usefulness across key phases of the startup process, including opportunity identification, need analysis, concept development, market exploration, and business model definition. The results show that AI is perceived as particularly useful in early and analytical phases, where it supports information gathering, synthesis, and the exploration of alternative solutions. In these stages, AI functions as a cognitive amplifier, helping students navigate uncertainty and structure complex inputs. However, its perceived usefulness decreases in more strategic and decision-intensive phases, where human judgment, critical thinking, and responsibility become central. These findings highlight a tension between the exploratory potential of AI and its tendency toward risk-averse reasoning. From an educational perspective, this suggests framing AI as a cognitive sparring partner that stimulates thinking without replacing decision-making. The study contributes to the design of startup education models that leverage AI while preserving the uncertainty and risk that are fundamental to innovation-driven entrepreneurship.
2026
Education and New Developments 2026 – Volume II
978-989-36839-5-8
Artificial Intelligence, startup education, design education, design-driven entrepreneurship, human–AI collaboration
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1321345
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