AI-Augmented Business Analytics in Innovative Startups

Ketevan Nozadze () and Keti Tskhadadze ()
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Ketevan Nozadze: The University of Georgia
Keti Tskhadadze: The University of Georgia

A chapter in Advanced Data Analytics, Machine Learning and AI in Business, 2026, pp 185-194 from Springer

Abstract: Abstract Artificial Intelligence (AI) is increasingly transforming how innovative startups generate insights and make decisions in uncertain and rapidly changing environments. This study examines the integration of AI-augmented business analytics in early-stage Georgian startups using a multiple-case study approach. The analysis highlights how firms apply AI in market forecasting, customer behavior analysis, and product development, and how hybrid intelligence, combining human judgment with algorithmic capabilities, supports strategic agility. Findings show that AI enhances startups’ ability to interpret dynamic data, accelerate learning cycles, and optimize resource allocation. Key enablers include data agility, explainable AI, and lean organizational structures, while challenges relate to limited expertise, data governance, and interpretability. Based on cross-case insights, the paper proposes a conceptual framework to guide early-stage firms in embedding AI within their analytical workflows. The study contributes empirical evidence from an emerging ecosystem and advances understanding of AI-driven analytics in startups.

Keywords: Artificial Intelligence; AI Integration; Customer Behavior Analysis; Innovative Startups; Market Forecasting (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-3-032-23493-3_11

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DOI: 10.1007/978-3-032-23493-3_11

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