Doctorate in Business Administration Student, Westcliff University, College of Business, California, USA.
World Journal of Advanced Research and Reviews, 2025, 25(02), 2219-2248
Article DOI: 10.30574/wjarr.2025.25.2.0575
Received on 12 January 2025; revised on 20 February 2025; accepted on 23 February 2025
The integration of Artificial Intelligence (AI) into strategic decision-making is transforming business landscapes, offering startups unprecedented opportunities to scale, optimize operations, and drive innovation. While AI adoption is well-documented in large enterprises, startups often face unique challenges, including limited financial and technical resources, ethical concerns, and the need for adaptable frameworks. This article bridges the gap by presenting a scalable AI adoption model tailored for startups, outlining resource-efficient strategies, and emphasizing ethical governance to ensure responsible AI deployment. Key AI applications such as predictive analytics, dynamic pricing, and AI-powered market intelligence are examined to illustrate their impact on business growth and competitive positioning. Additionally, the role of AI-driven decision-support systems and autonomous AI agents in facilitating agile and data-driven decision-making is explored. The article also delves into emerging AI trends, including quantum computing, real-time AI optimization, and autonomous decision-making systems, which will redefine startup scalability in the near future. By addressing the technical, strategic, and ethical dimensions of AI adoption, this research provides startups with a robust framework to harness AI for sustainable growth and competitive advantage in an increasingly AI-driven economy.
Artificial Intelligence; Startups, Strategic Decision-Making; Ai Governance; Predictive Analytics; Dynamic Pricing; Ai Agents; Ethical Ai; Market; Intelligence; Autonomous Ai
Preview Article PDF
Arunraju Chinnaraju. AI-driven strategic decision-making on innovation: Scalable, ethical approaches and ai agents for startups. World Journal of Advanced Research and Reviews, 2025, 25(02), 2219-2248. Article DOI: https://doi.org/10.30574/wjarr.2025.25.2.0575.
Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0