Why Business and Academia Often View AI Differently

From working in both academic research and industry, one observation is that artificial intelligence (AI) is often viewed very differently in these two environments. In academic research for business, AI is rarely the starting point of the study. When submitting research papers to journals, reviewers typically expect the research to begin with a clearly defined project problem, such as improving forecasting accuracy, identifying risk patterns, or optimizing decision-making. The researcher then uses theory and historical studies to evaluate analytical approaches to address that problem, and AI may be one of the methods considered. AI-based methods must withstand the rigour of comparison with other techniques, such as regression analysis, statistical models, or optimization methods. In other words, the research question comes first and the analytical process comes second.

In business, however, the mindset is often quite different. Executives tend to view AI less as one analytical method among many and more as a strategic opportunity. AI has the potential to improve productivity, automate complex tasks, analyze large volumes of data, and generate insights faster than traditional approaches. Because of this, many organizations feel pressure to adopt AI quickly to avoid falling behind competitors. In practice, this leads to a very different starting point. Rather than asking, “What is the best analytical method for this problem?” business leaders often begin with the question, “How can we use AI to improve results?”

This difference does not mean one perspective is right and the other is wrong. Academia emphasizes rigour, comparison, and methodological clarity. Business emphasizes speed, opportunity, and competitive advantage. The most productive path forward may lie somewhere between the two. Organizations benefit when they adopt AI thoughtfully, understanding both its potential and its limitations. At the same time, researchers can ensure their work remains relevant by studying real organizational challenges where AI is being deployed.

Artificial intelligence is both a powerful tool and a strategic capability. Bridging the gap between academic research and business urgency may ultimately lead to better decisions in both worlds.