Umeå University's logo

This thesis examines the VC decision-making process toward AI startups, specifically how risks to humans are factored into the decision-making process. AI as a disruptive technology offers significant potential, however, it also introduces both tangible and intangible risks to individuals and society. These risks are rarely considered in academic literature in the field of business and management. VC assessment frameworks, where financial returns and potential for scalability tend to dominate.

Using a qualitative research design informed by a relativist ontology and interpretivist epistemology, this study explores how venture capitalists perceive and address human risk during screening and due diligence processes. Two research questions guide the study: (1) how are human risks considered and incorporated into VC decision-making for investment in AI startups? (2) how are VC firms screening and conducting due diligence on AI startups? Insights were drawn from nine semi-structured interviews with VCs across different geographies and firm types.

The analysis revealed three key themes. First, a tangible commercial drive, where financial priorities remain key in decision-making. Second, an intangible moral foundation, where venture capitalists' personal ethics and will to make an impact shape investment choices. Third, a pragmatic relational solution, where responsibility for assessing human risk is often delegated to startup founders. Human risk was also found to be inconsistently defined, rarely formalized, and often overlooked in screening and due diligence. As a result, venture capitalists place a high level of trust in founders, viewing them and their relationship as the critical safeguard.

To interpret the findings, the study uses shareholder theory, stakeholder theory, and Dual- Investor theory. While the first two offer useful yet limited insights, Dual-Investor theory highlights the coexistence of financial and social goals and proves most relevant for understanding the dual logic within AI investment.

This thesis contributes to the growing body of research at the intersection of business ethics, technology, and finance by contextualizing Dual-Investor theory in the VC landscape. It calls for practical tools to help VCs evaluate human risk and encourages a more balanced, ethically informed approach to AI startup investment.