The Place of Management in an AI Curriculum
Academic degrees in Artificial Intelligence focus too often on Data Science per se than its transformative impact in organizations and markets.
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Most academic programs specializing in Artificial Intelligence today focus on understanding data preparation, statistics, modeling, and algorithms while leaving AI’s impact on business to a footnote. This technocentric vision of Data Science may help explain both why Gartner suggests that businesses will invest $383 billion in AI this year, and why the largest majority of these AI projects will produce no real-world applications.[i]
As artificial intelligence gains a foothold in all aspects of business, what do students need to learn about Management and AI in engineering and business schools? In this three-part series*, we will examine and illustrate challenges ranging from aligning AI with corporate strategy, to developing co-intelligence between human and machine agents, to AI’s paradoxical role in innovation. In this first contribution, let’s focus on the need to understand how AI can influence strategy, the concept of “AI readiness” and AI project management.
AI and Corporate Strategy
Although several authors have explored the notion of digital strategy[i], a more important question is how artificial intelligence influences the way we think about business. We can begin with an organization’s business model, i.e. how AI will modify how a company segments its market, develops processes and networks to address customer needs, and measures the results. The application of AI to business process improvement also needs to be addressed, focusing on how machine learning can improve an organization’s understanding of customer behavior, the cost of producing products or services, and the pertinence of the metrics used to evaluate the processes themselves.
The data needed to improve AI models is often produced by the organization’s suppliers, business partners, and customers requiring management to rethink the boundaries between the organization and its ecosystem. Because the data needed to train AI models is largely unstructured, management needs to take a new look at how data is captured, interpreted…
