Artificial Intelligence (AI) Market

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Global Artificial Intelligence (AI) Market
Outlook 2024 Global Opportunity Growth
Analysis, 2016-2024
Report Code AFT 1078
2016-2024
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Executive Summary
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Global Artificial Intelligence (AI) Market
Share (), By Region-2016-2024
Global Artificial Intelligence (AI) Market Size
USD (Billion). 2016-2024
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In 2016, Machine Learning accounted for the
highest market share XX in Global Artificial
Intelligence (AI) Market
With XX share in 2016, North America region
dominated the Global Artificial Intelligence (AI)
Market
Global Artificial Intelligence (AI) Market Share
(), By Vertical Industry-2016
Global Artificial Intelligence (AI) Market
Share (), By Technology-2016
Global Artificial Intelligence (AI) Market Share
(), By Use Case-2016
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Major Players Presence-Regional Analysis
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Major Players/ Industries APAC North America Europe Latin America Middle East Africa
Google Inc.
Microsoft Corporation
IBM Corp.
IPsoft
Rocket Fuel Inc.
Qlik Technologies Inc.
MicroStrategy, Inc.
Brighterion, Inc.
24/7 Customer, Inc.
Low Penetration
High Penetration
Medium Penetration
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Global Artificial Intelligence (AI) Market Size
(USD Billion) Y-O-Y Growth Analysis
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Global Artificial Intelligence (AI) Market Size
(USD Billion)-2016-2024
Global Artificial Intelligence (AI) Y-O-Y Growth
() Analysis-2016-2024
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Market Dynamics
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Growth Drivers
Growth Barriers
General Trend
Highly Complex
Moderately Complex
Waived
Artificial Intelligence (AI)
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Growth Drivers
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Penetration Rate () of AI in Various Verticals,
2016

• Firms And Industries Already On The Digital
  Frontier Are Adopting AI
• Investors are pouring billions of dollars into AI
  companies based on the hope that a market of AI
  adopters will develop fairly quickly and will be
  willing to pay for AI infrastructure, platforms,
  and services
• Clearly, Amazon, Google, and other digital
  natives are investing for their own applications,
  such as optimizing searches and personalizing
  marketing
• Independently of sectors, large companies tend to
  invest in AI faster at scale. This again is
  typical of digital adoption, in which, for
  instance, small and midsized businesses have
  typically lagged behind in their decision to
  invest in new technologies
• Early adopters are not specializing in one type
  of technology. They go broader as they adopt
  multiple AI tools addressing a number of
  different use cases at the same time
• Automotive and assembly is also highly ranked. It
  was one of the first sectors that implemented
  advanced robotics at scale for manufacturing, and
  today is also using AI technologies to develop
  self-driving cars

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• Impact Analysis-
• Autonomous transportation will soon be
  commonplace and, as most peoples first
  experience with physically embodied AI systems,
  will strongly influence the publics perception
  of AI. As cars become better drivers than people,
  city-dwellers will own fewer cars, live further
  from work, and spend time differently, leading to
  an entirely new urban organization
• Healthcare is one of the largest and most rapidly
  growing segments of AI, driven predominantly by
  innovation in clinical research, robotic personal
  assistants and big data analytics. Healthcare is
  poised to accelerate investments in AI over the
  next few years

Future Drivers of Artificial Intelligence
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Adoption of Artificial Intelligence Technology
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Investment (Billion USD) In AI Technology by BSFI
Industry and Number of Deals (2011-2017)
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Impact Analysis of Artificial Intelligence (AI)
on End-User Industry

• Factors Impacting Global Artificial Intelligence
  (AI) Industry
• Robots have long been popular educational
  devices, starting with the early Lego Mindstorms
  kits developed with the MIT Media Lab in the
  1980s. Intelligent Tutoring Systems (ITS) for
  science, math, language, and other disciplines
  match students with interactive machine tutors.
  Natural Language Processing, especially when
  combined with machine learning and crowdsourcing,
  has boosted online learning and enabled teachers
  to multiply the size of their classrooms while
  simultaneously addressing individual students
  learning needs and styles
• One might have expected more and more
  sophisticated use of AI technologies in schools,
  colleges, and universities by now. Much of its
  absence can be explained by the lack of financial
  resources of these institutions as well as the
  lack of data establishing the technologies
  effectiveness. These problems are being
  addressed, albeit slowly, by private foundations
  and by numerous programs to train primarily
  secondary school teachers in summer programs
• To date, evidence-driven analytics on healthcare
  have relied on traditional healthcare datamainly
  the electronic medical records discussed above.
  In the clinical setting, there are hopeful trends
  towards bringing new data to bear. For example,
  TeleLanguage enables a human clinician to conduct
  language therapy sessions with multiple patients
  simultaneously with the aid of an AI agent
  trained by the clinician.

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Our mission is simple to develop insightful
business solutions, help our clients make
powerful future decisions to keep them well ahead
of the game which is the market, and leave a mark
across businesses and communities through our
well-defined ideas and clear cut forecasts.
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