计算机科学
软件部署
任务(项目管理)
知识管理
自动化
适应性
创造力
过程管理
过程(计算)
业务流程
人工智能
管理科学
工程类
系统工程
管理
软件工程
在制品
心理学
运营管理
机械工程
社会心理学
经济
操作系统
出处
期刊:International Journal for Research in Applied Science and Engineering Technology
[International Journal for Research in Applied Science and Engineering Technology (IJRASET)]
日期:2024-12-25
卷期号:12 (12): 1475-1487
标识
DOI:10.22214/ijraset.2024.66051
摘要
Purpose: This paper proposes structured frameworks for effective Human-AI collaboration within business processes. It aims to identify and model optimal task divisions where humans contribute oversight, creativity, and strategic judgment while AI provides computational power, automation, and analytical insights. Methodology: We explore collaboration models based on role-based division, process integration, and task adaptability. We analyze real-world business applications to demonstrate the efficacy of these models in improving productivity, decision-making, and innovation. Findings: We propose three key frameworks: (1) Augmented Creativity, where AI enhances human ideation, (2) Hybrid Decision Systems, where AI assists human judgment through predictive insights, and (3) Oversight-Driven Automation, where humans maintain control over automated tasks. Implications: The study highlights pathways for achieving synergistic Human-AI interactions to optimize business outcomes, enhance agility, and ensure ethical AI deployment
科研通智能强力驱动
Strongly Powered by AbleSci AI