Organizations are swiftly adopting artificial intelligence (AI) as an essential decision-making tool. Its capacity to analyze huge, complex datasets in near real time enables leaders to set policy more quickly and with greater degrees of certainty. The emergence of generative AI has further revolutionized this process, offering the potential to provide instant decision support for solutions to complicated questions. With advanced analytics and deep data, CEOs leverage generative AI to gain valuable insights and guidance, but it is not foolproof.
The human factor is the wild card. One study, for instance, found that business leaders often make dramatically different decisions based on identical AI outcomes; some executives invested up to 18% more in strategic initiatives based on the same AI advice. No single decision-making model, therefore, fits all situations.
While AI can quickly identify patterns, trends and anomalies, human intuition and experience remain vital to the data-driven decision-making process: AI-driven analytics inform strategies, but humans have the final word. “The interaction between humans and AI, as well as the ability to choose which decisions to delegate to AI, will be among the most important skills for decision-makers,” according to a World Economic Forum analysis.
The value employers place on that skill is creating demand that exceeds the supply of management analysts with expertise in making decisions supported by advanced analytics, according to the U.S. Bureau of Labor Statistics (BLS). It predicts employers will add 95,700 positions annually through 2032 (a much higher rate of growth than the average of all professions) at a median annual compensation of $99,410.
How Do Management Professionals Gain Expertise in Data-driven Decision-Making?
The Southern Illinois University Edwardsville (SIUE) online Master of Science in Management Information Systems with a Specialization in Business Analytics program is an ideal way to future-proof your career. The program’s curriculum equips graduates with the skills and insights to become innovative problem-solvers and data-driven leaders.
The hands-on program encourages students to write complex queries to identify patterns in data. Combining theory and practice, it also prepares graduates for the Amazon Web Services (AWS) exam. The credential demonstrates mastery of advanced computing services and is a decisive advantage in the competition for high-demand, well-paying roles.
Understanding AI in Business
Simply put, AI refers to computer systems designed to perform tasks that typically require human intelligence, such as learning, reasoning and problem-solving. Upwork notes this represents a revolution in data-driven decision-making. These decision-support tools provide:
- precision and objectivity through the use of sophisticated algorithms that analyze data consistently and accurately
- speed in processing massive datasets and enabling real-time analytics that streamline decision-making processes
- enhanced risk management that identifies potential problems in multiple scenarios, enabling decision-makers to develop proactive mitigation strategies
“The purpose of integrating AI in decision making is not complete automation. Rather, the goal is to help humans make quicker and better decisions through streamlined processes and effective use of data,” Upwork explains.
The Value of Advanced Technology in Specific Business Sectors?
Data Ideology describes enhanced decision support as a way to model data and simulate outcomes. This predictive-analytics approach enables companies to choose the option most likely to produce the desired result before deciding, thus minimizing risk and maximizing performance. Specific business sectors leading the adoption of guided decision-making include:
- Finance. Machine learning (ML) technology is central to modern fraud detection. Using historical transaction data to train ML, it can analyze new data on the fly to identify anomalies that indicate potentially illegal activity or compliance violations.
- Healthcare. Predictive analytics transform how healthcare providers analyze vast amounts of data from patient records, clinical trials and medical imaging. Transforming data into intelligence supports decisions that reduce costs and produce better outcomes.
- Retail. Models can accurately forecast demand, enabling retailers to manage inventory levels more effectively. This reduces costs, streamlines the supply chain and improves operational efficiency. Moreover, subsequent insights drive customer satisfaction and brand loyalty.
“Now is not the time to sit still — but it’s also not the time to go crazy,” Digital Adoption advises. “Now’s the time to prepare, listen, adapt, and implement when appropriate.”
Technology Is Revolutionizing Data-driven Decision-Making
Technology is revolutionizing data-driven decision-making by enhancing analysis, enabling real-time insights and automating routine tasks. However, the human factor remains essential, as human oversight ensures ethical considerations and contextual understanding. Companies that harness the decision support of technically savvy leaders are cutting costs, reducing risk, driving revenue and gaining competitive advantage. With an online MS in MIS – Business Analytics from SIUE, graduates are positioned to support their organizations with decision-making guided and backed by data.
Learn more about SIUE’s online Master of Science in Management Information Systems with a Specialization in Business Analytics program.
