Artificial Intelligence, 2020 Update - Thematic Research

Artificial Intelligence, 2020 Update - Thematic Research

Summary

Artificial intelligence (AI) is everywhere, and it has an impact on all our lives. However, years of bold proclamations have resulted in AI becoming overhyped, with reality often falling short of the world-altering promises. The coming years will be less about making bold statements and more about delivering tangible benefits. Practical uses of AI will be front and center, as businesses ensure they get their money’s worth by using AI to address specific use cases.

There is a raft of innovative AI start-ups with cutting-edge expertise that helps fuel growth in AI. Yet, there is no denying that companies with access to large repositories of data to power their AI models drive the development of AI. Big Tech excels in this regard, and about a dozen tech giants from the US and China set the overall tone in AI.

Scope

  • This report provides an overview of the artificial intelligence theme.
  • It identifies the key trends impacting growth of the theme over the next 12 to 24 months, split into three categories: technology trends, macroeconomic trends, and regulatory trends.
  • It includes a comprehensive industry analysis, including up-to-date forecasts for global AI platforms revenue to 2024.
  • The detailed value chain highlights seven key AI technologies: machine learning, data science, conversational platforms, computer vision, AI chips, smart robots, and context-aware computing.
Reasons to Buy
  • From self-driving vehicles to fraud detection, AI plays a role in virtually every industry, putting pressure on incumbents to adapt and innovate or face stagnation and possible elimination.
  • This report is an invaluable guide to this highly disruptive theme, including analysis of key AI technologies and assessment of the leading providers.


  • Executive summary
    • From hype to reality
    • The age of responsible AI has arrived
    • AI and COVID-19 have a symbiotic relationship
    • Winners and losers
    • Inside
    • Related reports
    • Report type
  • Players
    • Table Figure 1: Who are the leading players in the AI theme, and where do they sit in the value chain?
  • Technology briefing
    • What is AI?
      • Table Figure 2: Technologies and subsets of AI
    • The seven key AI technologies
    • Machine learning
      • Table Figure 3: Key components of machine learning
    • Data science
    • Conversational platforms
    • Computer vision
    • AI chips
      • Table Figure 4: Key components of data science
      • Table Figure 5: Object detection is a crucial ingredient in CV
    • Smart robots
    • Context-aware computing
    • What are the most talked-about areas of AI?
      • Table Figure 6: The most-tweeted keywords related to AI, Jan 2019-Sep 2020
    • AI use cases
      • Table Figure 7: AI is impacting every single vertical industry
  • Trends
    • Table Figure 8: Top AI trends of 2020
    • Technology trends
      • Table Technology trends
    • Macroeconomic trends
      • Table Macroeconomic trends
    • Regulatory trends
      • Table Regulatory trends
  • Industry analysis
    • AI investment is a priority for most companies
      • Table Figure 9: Sentiment towards AI is increasingly optimistic, but many still believe AI is over-hyped
    • What are the business benefits of AI?
      • Table Figure 10: AI is expected to improve business operations and generate new business opportunities
    • Sectors that are leading AI adopters
      • Table Figure 11: Speed of AI adoption for GlobalData's 18 vertical markets
    • Market size and growth forecasts
      • Table Figure 12: Global AI platform revenue will reach $52bn by 2024, up from $28bn in 2019
      • Table Figure 13: AI-related patent applications and mentions in company filings have surged in just a few years
      • The US leads the way, but more countries are making AI a priority
        • Table Figure 14: The US dominates the AI market Almost one-third of global AI platform revenues in 2019 came from the US
        • Table Figure 15: AI has become a global priority
      • Competitive analysis
    • Big Tech's work in AI attracts a lot of attention
      • Table Figure 16: Influencers tweet about Big Tech's efforts in AI
    • AI-related research is surging
      • Table Figure 17: US tech firms are filing a growing number of AI-related patents
    • Incumbents in every industry risk disruption by AI
      • Table Figure 18: Every industry is at risk of disruption by AI
    • AI and ethics
      • Table Figure 19: Discrimination in AI is a major concern
      • Table Figure 20: Explainable AI has emerged as a way to provide transparent decisions and add trust
    • Mergers and acquisitions
      • Table Figure 21: The number of AI-related M&A deals has boomed in the last five years
      • Table Mergers and acquisitions
    • Timeline
      • Table Figure 22: The AI story
  • Value chain
    • Table Figure 23: The AI value chain
    • Machine learning
      • Table Figure 24: Big Tech is dominating ML ML can broadly be divided into two categories
    • ML is integral to data-driven businesses
    • Amazon's cloud business is the basis for its ML offering
    • Microsoft aims to increase trust with Responsible ML
    • Google introduced AutoML in 2020
      • Table Figure 25: Bridging the skills gap
    • As of 2019, Watson goes anywhere
    • The Chinese giants are making ML a priority
    • Enterprise software players are strong in MLaaS
    • Start-ups focus on niche technology areas and verticals
      • Table Figure 26: Machine learning: leaders and disruptors
    • Data science
      • The data science platform market is booming
        • Table Figure 27: Data science is an enterprise priority
      • Big Tech dominates the cloud-based solutions segment
      • Demand for pre- and post-deployment services increase
      • Talent is scarce and in high demand
        • Table Figure 28: Data science: leaders and disruptors
    • Conversational platforms
      • Table Figure 29: Virtual assistants are now part of everyday life, and they are getting more sophisticated
      • Smart speakers and automated home solutions are increasingly popular
      • Wearable tech will help increase engagement with conversational platforms
      • COVID-19 boosts demand for virtual agents
        • Table Figure 31: The enterprise landscape look different from the consumer one
      • Which vendors are best-positioned in the conversational platform market?
        • Table Figure 32: Conversational platforms: leaders and disruptors
    • Computer vision
      • Table Figure 33: There are four key CV software technologies
      • Facial recognition (FR) is a hot topic
      • China is a leader in AI surveillance tech
        • Table Figure 34: State surveillance in China is greater than in any other country
      • Object detection is a crucial ingredient in autonomous vehicles
      • Video recognition helps curb copyright infringement
      • Machine vision will be front and center of the factory of the future
      • Computer vision as a service is driving adoption
        • Table Figure 35: Computer vision: leaders and disruptors
    • AI chips
      • Homegrown processors are putting pressure on established leaders
      • Legacy suppliers are stepping up their game
      • Non-traditional processor designs will enable new ways of creating software
      • China's influence will increase
        • Table Figure 37: AI chips: leaders and disruptors
    • Smart robots
      • Table Figure 38: Smart robots combine robotics and AI
      • Table Figure 39: 1The smart robots market is diverse
      • The co-bot market will grow sharply
      • Care robots are a small but increasingly important segment
        • Table Figure 40: Table-top robots for the elderly
      • Consumer robots support domestic tasks
        • Table Figure 41: Smart robots: leaders and disruptors
    • Context-aware computing
      • Context-aware applications are vital for automated homes and smart cities
        • Table Figure 42: Context-awareness is integral to the
      • Context-awareness will support the user experience of augmented reality
      • There are a wide range of industry-specific applications
        • Table Figure 43: Context-aware computing: leaders and disruptors
  • Companies
    • Table Figure 44: Big Tech is making its mark in AI
    • Public companies
      • Table Public companies
    • Private companies
      • Table Private companies
  • Sector scorecards
    • Application software sector scorecard
      • Who's who
        • Table Figure 45: Who does what in the application software space?
      • Thematic screen
        • Table Figure 46: Thematic screen
      • Valuation screen
        • Table Figure 47: Valuation screen
      • Risk screen
        • Table Figure 48: Risk screen
    • Semiconductor sector scorecard
      • Who's who
        • Table Figure 49: Who does what in the semiconductors space?
      • Thematic screen
        • Table Figure 50: Thematic screen - Semiconductor sector scorecard
      • Valuation screen
        • Table Figure 51: Valuation screen - Semiconductor sector scorecard
      • Risk screen
        • Table Figure 52: Risk screen - Semiconductor sector scorecard
  • Glossary
    • Table Glossary
  • Further reading
    • GlobalData reports
      • Table GlobalData reports
  • Our thematic research methodology
    • Viewing the world's data by themes makes it easier to make important decisions
    • Traditional research does a poor job of picking winners and losers
    • That is why we developed our "thematic engine"
    • How do we create our sector scorecards?
      • Table Figure 53: Our five-step approach for generating a sector scorecard
    • What is in our sector scorecards?
    • How do we score companies in our thematic screen?
    • How our research reports fit into our overall thematic research ecosystem?

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