Evaluating Investment Risks in LATAM AI Startups: Ranking of Investment Potential and Framework for Valuation
Abraham Ramos-Torres, Laura N. Montoya

TL;DR
This paper assesses investment risks and potential in LATAM AI startups, proposing a ranking framework and valuation model to guide investors amidst regional challenges and opportunities.
Contribution
It introduces a regional startup valuation framework using TAM, SAM, SOM, and DCF methods tailored for LATAM's unique market conditions.
Findings
Argentina, Colombia, Uruguay, Costa Rica, Panama, and Ecuador show high startup potential.
AI-driven startups in LATAM present significant growth opportunities despite regional risks.
Diversification in emerging markets can enhance investment returns.
Abstract
The growth of the tech startup ecosystem in Latin America (LATAM) is driven by innovative entrepreneurs addressing market needs across various sectors. However, these startups encounter unique challenges and risks that require specific management approaches. This paper explores a case study with the Total Addressable Market (TAM), Serviceable Available Market (SAM), and Serviceable Obtainable Market (SOM) metrics within the context of the online food delivery industry in LATAM, serving as a model for valuing startups using the Discounted Cash Flow (DCF) method. By analyzing key emerging powers such as Argentina, Colombia, Uruguay, Costa Rica, Panama, and Ecuador, the study highlights the potential and profitability of AI-driven startups in the region through the development of a ranking of emerging powers in Latin America for tech startup investment. The paper also examines the…
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Taxonomy
TopicsImpact of AI and Big Data on Business and Society
