2025年生成式+AI+投资回报率研究报告-谷歌

Core Insights - Generative AI (Gen AI) is a key driver for enterprise transformation, delivering significant financial returns and rapid effectiveness [1][3] - 74% of companies using Gen AI report achieving ROI within the first year, with 86% of those experiencing revenue growth of over 6%, and 34% reporting increases exceeding 10% [1][16] - 84% of organizations can move Gen AI use cases from concept to production in less than six months, with 34% achieving this in 1-3 months, enhancing innovation cycles and market responsiveness [1][17] Business Value - Gen AI provides multi-dimensional business value across four core areas: productivity, business growth, user experience, and security [1] - 45% of enterprises report doubling employee productivity, with significant efficiency improvements in both IT and non-IT processes [1][42] - 63% of companies leverage AI for business growth, while 77% expand their market through optimized customer acquisition and lead generation [1][45] - User engagement and satisfaction have improved for 85% and 80% of enterprises respectively, with notable performance in financial services and healthcare [1][49] - 56% of organizations report enhanced security posture, with 82% improving threat detection capabilities and 71% reducing the time to resolve security incidents [1][50] Characteristics of Gen AI Leaders - Gen AI Leaders, comprising 16% of surveyed companies, invest over 15% of their operating expenses in Gen AI, with 69% applying AI across core business functions [2] - These leaders have a clear growth-oriented vision, prioritize new product development, and have strong C-level executive support, with 76% aligning technology goals with business needs [2][18] - Investment strategies focus on business-technology collaboration (47%), talent development (46%), and data quality improvement (43%), with short-term plans to reinvest AI gains into new product development (47%) and operational profit margin enhancement (49%) [2] Strategic Recommendations - The report outlines seven core action recommendations for enterprises, including establishing unified C-level support, focusing on quick-win use cases, integrating AI into core business functions, and prioritizing data infrastructure [2]