To evaluate whether the strategy or approach you’re evaluating requires artificial intelligence, let’s turn back to our definition of AI as any computer-based system that observes, analyzes, and learns.
Thus, a true AI system is able to sense its own environment and augment its base of knowledge in close to real time.
A Tesla’s onboard computers analyze the images, blips, and other data it collects to make sense of its surroundings, allowing for the automation of several driving decisions.
Using this data, companies and sales professionals are able to arrive at many counterintuitive insights — for instance, calls with more positive sentiment are actually associated with lower closing rates than calls with less positive sentiment.
The ability to test, learn, and improve is only available to the most advanced machine learning systems today.
It does this by observing and analyzing the data from hundreds of thousands of Tesla cars and then learning from this data to improve the autonomous driving capabilities.
AI can be very useful for solving challenging business problems, yet the actual percentage of use cases where AI is significantly better than simple data science, or human insight, is quite low.
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