Artificial intelligence (AI) is changing the way businesses use data. While business analytics helps organizations understand what has happened and why, AI enables them to identify patterns, generate predictions, automate analysis, and uncover opportunities that might otherwise go unnoticed. Together, AI and business analytics help organizations make faster, more informed decisions based on increasingly complex data.
As businesses generate more information than ever before, leaders need tools that can transform data into actionable insights. AI-powered analytics helps bridge that gap by allowing organizations to move beyond reporting and toward prediction, optimization, and strategic decision-making.
For students pursuing careers in analytics, consulting, finance, marketing, operations, and technology, understanding how AI enhances business analytics is becoming an increasingly important skill.
Business analytics is the practice of using data, statistical methods, and analytical tools to support business decision-making. Organizations use analytics to identify trends, measure performance, evaluate opportunities, and solve business problems.
Traditionally, business analytics has focused on questions such as:
Analytics helps organizations transform raw data into meaningful information that supports strategic decisions across departments and industries.
Artificial intelligence expands the capabilities of traditional analytics by processing large volumes of data, identifying complex relationships, and generating insights at a scale that would be difficult for humans alone.
Rather than simply reporting past performance, AI can help organizations anticipate future outcomes and recommend actions.
Key benefits include:
AI can analyze massive datasets in seconds, reducing the time required to identify trends and generate insights.
Machine learning algorithms can uncover patterns and relationships that may not be immediately visible through traditional analysis.
AI helps organizations forecast future outcomes by analyzing historical data and identifying variables that influence performance.
Businesses can use AI-powered analytics to monitor changing conditions and respond more quickly to emerging opportunities or risks.
By combining human expertise with AI-driven insights, organizations can make more informed and timely decisions.
"AI enhances business analytics by providing actionable insights through real-time predictive analysis, automation, and advanced data interpretation capabilities. Additionally, AI expands the accessibility of business analytics to a broader user base by leveraging natural language processing and large language models," says Kogod School of Business Information Technology and Analytics Department Chair, Gwanhoo Lee.
One of the biggest challenges organizations face is not collecting data—it's knowing what to do with it.
Many companies have access to vast amounts of information but struggle to translate insights into meaningful action. AI helps close that gap by identifying recommendations, highlighting risks, and prioritizing opportunities.
For example, AI-powered analytics can help organizations:
These applications allow businesses to move beyond understanding what happened and focus on what should happen next.
Decision-making has always been a core business function. AI is enhancing that process by providing leaders with more comprehensive and timely information.
Instead of relying solely on historical reports, decision-makers can use AI-powered analytics to:
The result is a more proactive approach to business management that combines data-driven insights with human judgment.
Importantly, AI does not replace decision-makers. Rather, it provides tools that help leaders make better-informed decisions in increasingly complex environments.
As AI becomes more integrated into business operations, professionals need a combination of technical, analytical, and strategic skills.
Key competencies include:
Understanding how to interpret, evaluate, and communicate data-driven insights.
Using evidence and critical reasoning to solve business problems.
Connecting analytical findings to organizational goals and decision-making.
Understanding how AI, machine learning, and analytics tools support business operations.
Translating technical findings into recommendations that business leaders can understand and act upon.
These skills are increasingly valuable across industries and functions.
Organizations across sectors are seeking professionals who can leverage data and AI to improve decision-making.
Career opportunities include:
As AI adoption continues to grow, demand for professionals who can connect data insights with business strategy is expected to increase.
At Kogod, students learn how analytics, technology, and business strategy intersect in today's data-driven economy.
Through hands-on learning experiences, applied projects, and engagement with emerging technologies, students develop the skills needed to interpret data, evaluate business challenges, and generate actionable insights.
By combining analytical expertise with real-world business application, students gain experience using data not simply to understand the past, but to inform future decisions.
This approach reflects a growing reality across industries: organizations increasingly rely on professionals who can translate complex data into meaningful action.