Artificial Intelligence Driven Big Data and Business Analytics: A Comprehensive Review of Multi-Sectoral Applications in Healthcare, Finance, Supply Chain, and Organizational Innovation
Abstrak
Artificial Intelligence (AI) is transforming the way businesses operate across various sectors, including healthcare, finance, supply chain management, and organisational development. This shift is all about harnessing the power of big data to create more intelligent and efficient systems that benefit both organisations and their customers. In healthcare, for instance, AI is playing a pivotal role in improving diagnostics and patient care. From predicting health outcomes to personalising treatment plans and accelerating drug discovery, AI is making healthcare more efficient and effective. In the finance sector, AI is reshaping how institutions interact with their clients. With advanced algorithms, financial services can offer personalised advice, manage risks more effectively, detect fraud, and ensure compliance with regulations. Companies are using AI-driven tools to engage with customers more effectively and automate various processes, allowing them to allocate resources more efficiently and adopt sustainable practices. Concerns about data privacy, potential biases in algorithms, the complexity of integrating new technologies, workforce adaptation, and regulatory compliance are all hurdles that need to be addressed. Looking ahead, the future of AI seems promising, especially as it converges with other emerging technologies and sustainability initiatives. By embracing AI thoughtfully, organisations can not only gain a competitive edge but also build operational resilience and create lasting value. Ultimately, it’s crucial to find a balance between technological advancement and ethical responsibility. When implemented correctly, AI-driven analytics can pave the way for more equitable, efficient, and intelligent systems across various industries, ultimately benefiting everyone involved.
Penulis (2)
Md Nazmuddin
Moin Khan
Akses Cepat
- Tahun Terbit
- 2025
- Bahasa
- en
- Total Sitasi
- 2×
- Sumber Database
- Semantic Scholar
- DOI
- 10.70818/pjbis.v02i04.0130
- Akses
- Open Access ✓