An executive’s guide to AI – McKinsey

  • One of the highest rated McKinsey articles of the year is titled, “An executive’s guide to AI.” It’s a quick overview including key elements and terminology.
  • Artificial Intelligence
    • AI is typically defined as the ability of a machine to perform cognitive functions we associate with human minds, such as perceiving, reasoning, learning, and problem solving.
    • Timeline
  • Machine Learning
    • Machine- learning algorithms detect patterns and learn how to make predictions and recommendations by processing data and experiences, rather than by receiving explicit programming instruction.

    Types of analytics

    • Descriptive, predictive, prescriptive
  • Major Types
    • Supervised, unsupervised, reinforcement

    Deep Learning

    • Deep learning is a type of machine learning that can process a wider range of data resources, requires less data preprocessing by humans, and can often produce more accurate results than traditional machine-learning approaches.
  • Major Models
    • Convolutional neural network CNN
    • Recurrent neural network

    Business Cases

      Predict Call Center Volume
    • Predict power usage in an electrical grid distribution
    • Detect fraudulent activity for credit cards
    • Simple low-cost image classification
    • Forecast product demand and inventory
    • Predict the price of cars
    • Predict probability of patient joining healthcare
    • Predict prices that will be paid for a product

    https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/an-executives-guide-to-aihttps://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/an-executives-guide-to-ai

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