THE IMPLICATIONS OF INTEGRATING ARTIFICIAL INTELLIGENCE INTO DATA-DRIVEN DECISION-MAKING

Integrating artificial intelligence (AI) into data-driven decision-making offers advantages like increased performance, reduced costs and improved organisational efficiency; however, there are associated risks. The study employs a PRISMA protocol to systematically review academic articles from Scopus, ScienceDirect, and Web of Science databases to determine whether the risks AI pose are worth the rewards they offer. Literature trends reveal a growing interest in AI-driven decision-making, with significant research gaps in African contexts. The study indicates that AI is highly utilized for decision-making to foster competitiveness in manufacturing, finance, healthcare, education, and transport. Identified risks include bias, discrimination, privacy issues, and cybersecurity threats. It is highlighted that businesses need to address concerns about privacy, fairness, and transparency. Policymakers must develop ethical and legal standards besides regular monitoring and auditing of AI uses to mitigate risks.