Artificial intelligence (AI) is increasingly reshaping business analytics, organizational processes, and decision-making in the United States. This study examines the evolution of AI adoption from early digital transformation to contemporary AI-enabled business applications between 2018 and 2026. A longitudinal secondary-data design was employed, integrating evidence from the U.S. Census Bureau’s Annual Business Survey (ABS) and Business Trends and Outlook Survey (BTOS), Bureau of Labor Statistics (BLS) productivity statistics, Business Dynamics Statistics, and Bureau of Economic Analysis (BEA) Digital Economy Accounts, complemented by a structured literature review. Findings indicate that AI adoption increased from approximately 3.0% of firms in 2018 to 19.8% by May 2026, although changes in BTOS measurement after November 2025 limit direct comparability across the full period. Adoption was substantially higher in Information and Finance and Insurance and among larger firms. Among AI-using businesses, applications were concentrated in Sales and Marketing (52%), Strategy and Business Development (45%), and Information Technology (41%). Employment-weighted AI use in worker tasks (41%) exceeded firm-weighted adoption (23%), highlighting the broader workforce implications of organizational AI integration. U.S. productivity also increased during 2024–2025, although the available aggregate evidence does not establish a causal relationship with AI adoption. The study concludes that AI’s business value depends on integration with digital infrastructure, Business Analytics capabilities, human capital, and adaptive organizational processes. Strengthening these complementary capabilities, particularly among smaller firms, is therefore essential for inclusive and sustainable AI-enabled business transformation.