Gartner Research

Hype Hurts: Steering Clear of Dangerous AI Myths

Published: 03 July 2017

ID: G00324274

Analyst(s): Tom Austin , Mike Rollings , Alexander Linden

Summary

Enterprise architecture and technology innovation leaders must walk a fine line between embracing and overplaying AI technologies' role in delivering business value for digital business. Success is almost impossible without promotion, but Hype is dangerous because it sets the wrong expectations.

Table Of Contents

Analysis

  • Framing Assumptions
    • Hype Matters; Within Limits, It Fosters Innovation, but It Hurts as Well
    • Myth 1: Buy an AI to Solve Your Problems
    • Myth 2: Everyone Needs an AI Strategy or a Chief AI Officer
    • Myth 3: Artificial Intelligence Is Real
    • Myth 4: AI Technologies Define Their Own Goals
    • Myth 5: AI Has Human Characteristics
    • Myth 6: AI Understands (or Performs Cognitive Functions)
    • Myth 7: AI Can Think and Reason
    • Myth 8: AI Learns on Its Own
    • Myth 9: It's Easy to Train Applications That Combine DNNs and NLP
    • Myth 10: AI-Based Computer Vision Sees Like we Do (Or Better)
    • Myth 11: AI Will Transform Your Industry — Jump Now and Lead
    • Myth 12: For the Best Results, Standardize on One AI-Rich Platform Now
    • Myth 13: Maximize Investment in Leading-Edge AI Technologies
    • Myth 14: AI Is an Existential Threat (or It Saves All of Humanity)
    • Myth 15: There Will Never Be Another AI Winter

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