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Making Sense of Signals: How Equity Providers Evaluate AI startups
: How AI startups are evaluated by different Equity Providers

  • Alyssa Howe
  • Ludmilla Júlio Gonçalves

Student thesis: Master, one year

Abstract

The rapid rise of artificial intelligence has created a paradox for early‑stage equity providers. AI ventures attract strong investor interest, yet their technological opacity, reliance on intangible assets, and limited performance indicators make them difficult to assess through conventional criteria. This study examines how venture capitalists, business angels, and government‑backed investors interpret and prioritise signals when evaluating AI startups under high uncertainty, treating evaluation as a form of marketing communication in which founders must convey credibility to audiences with different logics. Drawing on signalling theory and semi‑structured interviews with five investors, the analysis identifies three tensions shaping evaluative practice: technical opacity versus comprehension, narrative versus substance, and hype versus discipline. The findings extend signalling theory in three ways. First, they introduce interpretive direction, capturing the positive or negative meaning investors assign to signals such as opacity or hype. Second, they highlight coherence as an alternative basis for credibility when objective benchmarks are limited. Third, they conceptualise market hype as a meta‑signal that shapes how first‑order signals are decoded. These insights shift attention from what AI technologies can achieve to how ventures are evaluated in practice. The study offers implications for sustainable business management by showing how speculative dynamics can channel capital toward ventures with limited long‑term viability. For founders, it provides guidance on aligning signal portfolios with the interpretive logics of different investors. For policymakers, it illustrates how public investment mandates can stabilise AI funding markets and support a more sustainable allocation of capital within innovation ecosystems.
Date of Award2026-Jun
Original languageEnglish
SupervisorSimon Down (Supervisor), Indira Kjellstrand (Assessor) & Christian Koch (Examiner)

Educational program

  • Master of Science in Marketing for Sustainable Business Management

University credits

  • 15 HE credits

Swedish Standard Keywords

  • Business Administration (50202)

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