ARTIFICIAL INTELLIGENCE AND AUGMENTED DECISION-MAKING: MACHINE LEARNING INTEGRATION IN STRATEGIC PLANNING, RISK ASSESSMENT, AND PERFORMANCE OPTIMIZATION

  • Dr. Madhuri Girish Shete Ramachandran International Institute of Management, Pune.
  • Ms. Snehal Sampatrao Jadhav Ramachandran International Institute of Management, Pune.
  • Indrajeet Bharat Kole Ramachandran International Institute of Management, Pune.
Keywords: Artificial Intelligence, Machine Learning, Strategic Planning, Risk Assessment, Performance Optimization, Decision-Making, Business Intelligence

Abstract

This research examines the transformative role of artificial intelligence (AI) in augmenting organizational decision-making processes across strategic planning, risk assessment, and performance optimization. Through analysis of market data, implementation case studies, and empirical evidence from 2020-2024, this study reveals significant growth in AI adoption, with 78% of organizations now using AI in at least one business function, up from 55% in early 2023. The global AI market, valued at $391 billion in 2024, is projected to reach $1.81 trillion by 2030, representing a 35.9% CAGR. Key findings demonstrate that AI-augmented decision-making processes deliver substantial improvements: 20-30% gains in productivity, enhanced risk detection rates of up to 87%, and reduced strategic planning time from weeks to days. However, implementation challenges persist, with only 1% of organizations considering themselves mature in AI deployment. This research provides a comprehensive framework for understanding AI's impact on decision-making while identifying critical success factors, implementation barriers, and future opportunities for organizational transformation.

References

ABI Research. (2024). Artificial Intelligence Market Size: Global Forecast to 2030. Retrieved from https://www.abiresearch.com/news-resources/chart-data/report-artificial-intelligence-market-size-global
Biloslavo, R., Edgar, D., Aydin, E., & Bulut, C. (2024). Artificial intelligence (AI) and strategic planning process within VUCA environments: a research agenda and guidelines. Management Decision. https://doi.org/10.1108/MD-10-2023-1944
Boston Consulting Group. (2024). AI Adoption in 2024: 74% of Companies Struggle to Achieve and Scale Value. Retrieved from https://www.bcg.com/press/24october2024-ai-adoption-in-2024-74-of-companies-struggle-to-achieve-and-scale-value
Fortune Business Insights. (2024). Artificial Intelligence Market Size, Share, Growth Drivers & Opportunities. Retrieved from https://www.fortunebusinessinsights.com/industry-reports/artificial-intelligence-market-100114
Grand View Research. (2024). Artificial Intelligence Market Size, Share | Industry Report, 2030. Retrieved from https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-ai-market
Hostinger. (2024). 47 AI statistics and trends for 2024: Latest insights and data. Retrieved from https://www.hostinger.com/tutorials/ai-statistics
Hypersense Software. (2024). Key Statistics Driving AI Adoption in 2024. Retrieved from https://hypersense-software.com/blog/2024/01/29/key-statistics-driving-ai-adoption-in-2024/
McKinsey & Company. (2024). The state of AI: How organizations are rewiring to capture value. Retrieved from https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai
McKinsey & Company. (2024). How AI is transforming strategy development. Retrieved from https://www.mckinsey.com/capabilities/strategy-and-corporate-finance/our-insights/how-ai-is-transforming-strategy-development
McKinsey & Company. (2024). Superagency in the workplace: Empowering people to unlock AI's full potential. Retrieved from https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/superagency-in-the-workplace-empowering-people-to-unlock-ais-full-potential-at-work
MDPI. (2024). Technology-Driven Financial Risk Management: Exploring the Benefits of Machine Learning for Non-Profit Organizations. Mathematics, 12(10), 416. https://doi.org/10.3390/math12100416
MDPI. (2024). Machine learning in internet financial risk management: A systematic literature review. PLoS One, 19(4), e0300195. https://doi.org/10.1371/journal.pone.0300195
Mintz. (2024). The State of the Funding Market for AI Companies: A 2024-2024 Outlook. Retrieved from https://www.mintz.com/insights-center/viewpoints/2166/2024-03-10-state-funding-market-ai-companies-2024-2024-outlook
National University. (2024). 131 AI Statistics and Trends for 2024. Retrieved from https://www.nu.edu/blog/ai-statistics-trends/
NMS Consulting. (2024). Using AI for Strategic Business Consulting in 2024. Retrieved from https://nmsconsulting.com/insights/using-ai-for-strategic-business-consulting-in-2024/
OECD. (2024). Emerging divides in the transition to artificial intelligence. Retrieved from https://www.oecd.org/content/dam/oecd/en/publications/reports/2024/06/emerging-divides-in-the-transition-to-artificial-intelligence_eeb5e120/7376c776-en.pdf
PwC. (2024). 2024 AI Business Predictions. Retrieved from https://www.pwc.com/us/en/tech-effect/ai-analytics/ai-predictions.html
UNCTAD. (2024). AI market projected to hit $4.8 trillion by 2033, emerging as dominant frontier technology. Retrieved from https://unctad.org/news/ai-market-projected-hit-48-trillion-2033-emerging-dominant-frontier-technology
Vena Solutions. (2024). 100+ AI Statistics Shaping Business in 2024. Retrieved from https://www.venasolutions.com/blog/ai-statistics
Somnath Patil, Smita Jadhav, Atul Kumar and Bhawani Panwar (2021), “Perspective human capital in food industry performance”, Proceedings of the International Culture, Art and Literature Congress, UKSEK Publications, Ankara, Turkey, (October 8, 2021), pp. 391, ISBN 978-625-7464-29-1. DOI: https://doi.org/10.5281/zenodo.6815669

Dr. Atul Kumar, Dr. Sheetal Darekar, Ms. Pooja Patil and Ms. Heena Ludhria (2021), “Vocal to local as effective retail marketing strategies for small retailing business in India 2021”, Proceedings of the International Archeology, Art, History and Cultural Heritage Congress, Adana, IKSAD Publications, Turkey (November 13-14, 2021), pp. 208, ISBN 978-625-7464-49-9. DOI: https://doi.org/10.5281/zenodo.6815681

Kumar, A., Trivedi, A., Bagul, S., Shikari, P., & Mahoday, A. (2021), “Assessing the influence of covid-19 on household digital payments: A study”, Proceedings of the International Congress of Recycling Economy & Sustainability Policy, Baku Eurasian University, Azerbaijan (October 12, 2023), pp. 204, ISBN 978-625-8254-29-7. DOI: https://doi.org/10.5281/zenodo.11076844

Kumar, A., Saxena, J. M., Saha, S., Aljapurkar, A., Ingawale, S., Bagul, S. P., Brar, V., & Gupta, D. (2023), “E-commerce business model analysis in urban area using machine learning”, Proceedings of the 3rd International Conference on Smart Generation Computing, Communication and Networking, Ghousia College of Engineering, Ramanagaram – 562159, India (December 29 to 31, 2023), pp. 90. DOI: https://doi.org/10.5281/zenodo.11080298

Kumar, A., & Gawande, A. (2023), “Navigating the modern marketing landscape: Embracing hybrid marketing as the new normal for comprehensive outreach strategies”, Proceedings of the International Conference on Sustainability, Innovation and Multi-Disciplinary Research for Tomorrow’s Challenges, Eastern University, Sri Lanka (January 23, 2024), pp. 205, ISBN 978-624-5731-40-4. DOI: https://doi.org/10.5281/zenodo.11080381
Published
2025-12-10
How to Cite
Shete, D. M., Jadhav, M. S., & Kole, I. (2025). ARTIFICIAL INTELLIGENCE AND AUGMENTED DECISION-MAKING: MACHINE LEARNING INTEGRATION IN STRATEGIC PLANNING, RISK ASSESSMENT, AND PERFORMANCE OPTIMIZATION. Asian Journal For Convergence In Technology (AJCT) ISSN -2350-1146, 11(2), 59-72. Retrieved from https://asianssr.org/index.php/ajct/article/view/1479

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.