From the course: Learning AI for Business Analysis
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Experiments and hypothesis in AI business analysis work
From the course: Learning AI for Business Analysis
Experiments and hypothesis in AI business analysis work
- Remember in high school science class when you had to form hypotheses and conduct experiments to learn. Today, complex and changing technology along with customer demands are creating an environment that moves fast. We need to hypothesize and experiment. With AI capabilities, there's increased complexity and uncertainty. It requires the minds of the entire team to solve. Exact solutions and answers are not known upfront, and this requires us to work with hypotheses and experiments. (inhales) This is why hypothesis and experiments are so important. They help us learn while developing. Let's look at an example. A call center is working to make the callers experience better and the team has the following hypothesis. "We believe that using AI to route calls "to our global network "of agents will result in less wait time for customers, "more productivity for agents, "and better quality in the call outcomes. "We know we are successful "when we see our queue times decrease, "agent…
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