Uploaded March 2026 | Updated September 2026, 2 weeks ago
“The ability to turn raw data into better decisions is a superpower,” says Professor Mohsen Bayati. In his course Business Intelligence from Big Data, he teaches how to lead effectively in an AI-driven world.
1. Guide your decisions by data
Human intuition can be powerful, but it’s often flawed. “By grounding your decisions in diverse data,” Bayati says, “you can tease out the true signal from the noise.”
2. Invest in technical capabilities
You can’t just read about AI — you have to use it. “The best way to learn is by doing,” Bayati says. In his class, students write code using APIs, which “demystifies the technology and empowers you to build quick proof of concepts.”
3. Formulate the right questions
It doesn’t matter how sophisticated your AI model is if it’s solving the wrong problem. “The hardest part of using data for decisions is asking the right questions,” Bayati says. “Ask yourself: What exactly are we trying to solve?”
4. Augment with expert human judgment
Bayati warns against the extremes of avoiding AI or over-relying on it. “Your goal shouldn’t be cognitive offloading,” he says. “Use your expert judgment to verify the output and layer your reasoning on top of the technology.”
5. Lead through collaboration
Decision-making with data is a team sport. “As a leader, your competitive advantage comes from bridging the gap” between technical and business teams, Bayati explains. “Don’t just consume the analysis, actively shape it.”
“The ability to turn raw data into better decisions is a superpower,” says Professor Mohsen Bayati. In his course Business Intelligence from Big Data, he teaches how to lead effectively in an AI-driven world.
1. Guide your decisions by data
Human intuition can be powerful, but it’s often flawed. “By grounding your decisions in diverse data,” Bayati says, “you can tease out the true signal from the noise.”
2. Invest in technical capabilities
You can’t just read about AI — you have to use it. “The best way to learn is by doing,” Bayati says. In his class, students write code using APIs, which “demystifies the technology and empowers you to build quick proof of concepts.”
3. Formulate the right questions
It doesn’t matter how sophisticated your AI model is if it’s solving the wrong problem. “The hardest part of using data for decisions is asking the right questions,” Bayati says. “Ask yourself: What exactly are we trying to solve?”
4. Augment with expert human judgment
Bayati warns against the extremes of avoiding AI or over-relying on it. “Your goal shouldn’t be cognitive offloading,” he says. “Use your expert judgment to verify the output and layer your reasoning on top of the technology.”
5. Lead through collaboration
Decision-making with data is a team sport. “As a leader, your competitive advantage comes from bridging the gap” between technical and business teams, Bayati explains. “Don’t just consume the analysis, actively shape it.”
