The Intelligence Revolution: Transforming Your Business with AI (Bernard Marr, 2020)

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  • If there is no explanation on an AI reaching its decision, it is a blackbox problem and should be fixed.
  • Data is crucial for AI to work, if your organisation does not have data, the AI will not be effective.
  • Types of AI
    • Narrow or applied AI: simulating humans to carry out specific tasks.
    • Generalised AI: intelligent machines that can perform any task.
  • What can AI do?
    • Read
    • Write: natural language processing (NLP), natural-language generation (NLG)
    • See
    • Hear
    • Speak
    • Smell
    • Move
    • Create
    • Understand emotions
  • How AI improve your business
    • Reducing costs
    • Automating and streamlining core business activities
    • Freeing up valuable employees to focus on more creative activities that drive business success, as opposed to mundane, repetitive activities
    • Improving customer satisfaction
    • Driving increased sales and revenue
    • Wasting less time on meetings
    • Enhancing sales and marketing process
    • Assessing and improving customer service
    • Improving product development processes
    • Automating content generation
    • Improving the manufacturing process
    • Enhancing recruitment and other HR processes
    • Automating IT processes
    • Detecting fraud with AI
    • Making transport and logistics more efficient
    • Improving retail operations
    • Automating fast food industry
    • Picking fruits with robots
    • Making construction safer
    • Making product more intelligent
    • Developing more intelligent services
    • Building a deeper understanding of customers
    • Making business processes more intelligent
    • Automating core business functions
    • Automating time-consumer, repetitive or mundane tasks
  • AI opportunity in your business
    1. Identifying the use cases
      1. Link to strategic goal
      2. AI objective
      3. Measures of success (KPIs)
      4. Use case owner
      5. AI approach and data required
      6. Ethical and legal issues
      7. Technology and infrastructure
      8. Skills and capacity
      9. Implementation
      10. Change management
    2. Working out your AI priorities
      • Common data strategy issues
      • Common ethical and legal issues
      • Common technology and infrastructure issues
      • Common skills and capacity issues
      • Common implementation issues
      • Common change management issues
  • Preparing the data
    • Data cleaning
    • Metadata creation
    • Data transformation
    • Data standardisation
    • Data augmentation
  • Example of applications
    • Smart washing machine
    • Intelligent refrigerators
    • Smart toilets
    • AI in toothbrushes
    • Smart home thermostats
    • Intelligent light switches
    • Smart home security
    • Smart products for mobility and transport
    • Intelligent cars
    • AI-powered bicycle
    • Autonomous delivery robots
    • Smart, autonomous drones
    • Autonomous ships
    • Smart weapons
    • Smart glasses
    • Smart industrial machinery
    • Intelligent manufacturing robots
    • Smart elevators
    • Smart surfaces
    • Intelligent power plant equipment
    • Smart products for sports and exercise
    • Wearable technology
    • The sensor-enhanced basketball game
    • Smart boxing gloves
    • Smart products for the health sector
    • Smart pee sticks
    • Intelligent contact lenses
    • Smart medical imaging equipment
    • Internet of medical things
    • Ecommerce personalised recommendations
    • Personalised news and video feeds
    • Personalised streaming content and music
    • AI as a service
    • Intelligent insurance
    • Intelligent financial service
    • Intelligent maintenance
    • Intelligent transport services
    • Intelligent fashion and retail
    • Intelligent fan engagement
    • Intelligent healthcare
    • Intelligent education
    • Intelligent matchmaking
  • Robotic process automation (RPA)
    • Call centre operations and customer queries
    • Transferring paper records to digital
    • Inputting and processing insurance claims
    • Automating help desk responses
    • Credit card application
    • HR onboarding
    • Sales and marketing


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