Implementation of AI for Solving Business Tasks
The study provides a comprehensive assessment of strategies and empirical results of implementing artificial intelligence-based solutions aimed at improving the efficiency of business processes in small and medium-sized enterprises (SMEs). The purpose of the work is to systematize and analyze the effectiveness of two key AI directions: conversational systems (conversational AI) and generative digital avatars in the context of lead generation, marketing communications, and customer service. The scientific novelty of the work lies in the proposal of a unified model for the synergistic integration of conversational and generative AI technologies, aimed at creating a seamless customer journey and maximizing marketing ROI while simultaneously increasing operational efficiency. Methodologically, the study is based on a review of relevant scientific literature from recent years. The conclusion confirms the initial hypothesis regarding a significant increase in operational efficiency and return on marketing investment when AI is strategically implemented. The work is of substantial practical and theoretical interest for SME executives, marketers, digital transformation experts, and researchers of applied aspects of artificial intelligence.
Authors
- Yerzhan Zheldibayev
Institutions
- Kazakh-American University (KZ)
Publication Details
- Journal
- The American Journal of Interdisciplinary Innovations and Research
- Published
- 2025-09-26
- DOI
- https://doi.org/10.37547/tajiir/volume07issue09-09
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00