How Artificial Intelligence Is Revolutionizing The Events Industry

How Artificial Intelligence Is Revolutionizing The Events Industry

Building Operating-Model Resilience

  • Autor: Pereira, Mario
  • Editor: Lantia
  • Colección: Caligrama
  • ISBN: 9788418787102
  • eISBN Epub: 9788418787614
  • Lugar de publicación:  Sevilla , España
  • Año de publicación digital: 2021
  • Mes: Junio
  • Idioma: Ingles

Building Operating-Model Resilience

Are you into events management and often wonder whether it is possible to adopt cutting edge technology like artificial intelligence (AI) to enhance efficiency and give your customers and their guests experiences like no other? or are you someone that hosts events frequently and wish to take them to the next level by adopting artificial intelligence? If you’ve answered YES, Let This Book Usher You Into The World Of Tech-Driven Artificial Intelligence Where You Will Learn How AI Can Solve Problems You May Have Experienced Holding Events In Ways You Never Thought Was Possible!While the mention of AI evokes images of complex computer algorithms andfuturistic robots as seen in Sci Fi films, the truth is that you can adopt artificial intelligence in your everyday life, whether you are an events manager, student or a business executive looking to leverage the power of technology to make your events better, enhance the experience, set yourself apart and more!When you are done reading this book you will have gained a lifetime of experience in just a few short hours. The stories are interesting to follow and the tough concepts have been made easy to understand. So get ready to broaden your horizons and adjust your expectations because you are in for one hell of a ride! Are you ready?

  • Introduction
  • Chapter 1Understanding the Weaknesses of Traditional Event Management Strategies
    • So What Is Event Management?
    • The History of Event Management
    • So Why do People Hold Events?
    • Setting Myself Up For Success
    • Problems With Traditional Event Management Strategies
    • Key Event Management Statistics (Both Virtual and In-Person Events)
    • Covid-19 Outbreak
  • Chapter 2How Integrating AI Has Made Me a Better Event Manager
    • A Tough Day
      • The Solution
    • What is Artificial Intelligence
    • The History of AI
    • Key AI Concepts
      • Computer Vision
    • Turing Test
    • How AI Has Been Instrumental In Transforming the Events Industry
    • AI and Security
    • The Numbers vs. Available Space/Amenities
    • Event Analytics
    • Targeted Marketing
    • AI-Powered Event Promotion
    • Venue Finding Through AI
    • Ticketing
    • Payment Processing
    • Automated Banquet Event Order (BEO)
      • Weaknesses of BEO
      • So how can artificial intelligence make a BEO better?
    • Mise en Place (MEP) and AI
      • How AI Can Transform MEP
    • Making Catering More Efficient Through AI
    • AI Backed Gastronomy
    • Robots In The Kitchen Plus Advanced Kitchen Accessories
    • AI-Powered Robots In Serving Food
    • Staff Training Through AI
    • AI-Powered Decorations And Scenography
    • Getting Customer Feedback
  • Chapter 3How AI Improves Guest’s Experiences at Events
    • What Is Customer Experience And Why Does It Matter?
    • Factors To Keep In Mind When Choosing A Technology
      • From the organizer’s perspective
      • From the guests perspective
    • How I Map A Customer’s Journey
    • Improving Customer Experience Through AI Analytics
    • How AI Concepts Apply To The Real World
    • AI Breaking The Language Barrier
    • Creating Adaptive Interactive Event Experiences
    • Matching Guests With Their Preferred Entertainment Options
    • Helping Guests Network On Business Opportunities
    • Staying In Touch With Fashion At Events
  • Chapter 4How To Incorporate AI Into Event Management
    • Preparation Of A Virtual Event
    • Preparation For Physical Events
  • Chapter 5How AI Adoption Takes Place
    • AI Design Thinking
      • Empathize
      • Defining The Problem And Conducting Research
      • Ideate And Research
      • Build and roll out a Prototype
      • Deployment
    • Artificial Intelligence Methodology
  • Chapter 6Problems to Expect And How To Navigate Them
    • AI Bias Problem
    • Data Scarcity
    • Slow Response to Technology
    • Data Privacy and Security Concerns
    • The Interpretation Problem
    • Sustainable Artificial Intelligence and Technology Goals
  • Conclusion

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