Artificial Intelligence (AI) – Thematic Intelligence

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All the vital news, analysis, and commentary curated by our industry experts.

Accessing in-depth insights from the ‘Artificial Intelligence’ report will give you:

  • An understanding of key trends impacting the growth of the theme over the next 12 to 24 months.
  • A comprehensive industry analysis, including market size and growth forecasts for AI hardware, AI platforms, AI consulting and support services, and specialized AI applications.
  • Detailed value chain breaks down artificial intelligence into five segments: hardware, data management, foundational AI, advanced AI capabilities, and delivery.

How is the ‘Artificial Intelligence’ report different from other reports in the market?

  • From self-driving vehicles to fraud detection, AI plays a role virtually in 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 an analysis of the key AI technologies and an assessment of the leading providers.

We recommend this valuable source of information to anyone involved in:

  • ​AI Hardware Manufacturers
  • ​AI Application Development Company
  • ​AI Services Company
  • ​AI Chips Manufacturers
  • ​Smart Robots Manufacturers
  • ​Machine Learning Vendors
  • ​Conversational Platform Vendors
  • ​Start-ups and Seed Companies
  • ​Investment Banks and Venture Capitalists

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Artificial Intelligence Market Analysis Trend Overview

For decades artificial intelligence (AI) has primarily been the territory of the university and corporate R&D labs. Recent progress in machine learning (ML) on the back of improved algorithms (e.g., Google’s AlphaGo, OpenAI’s GPT-3, Tesla’s AutoPilot) and increasing computing power have made it possible for AI to solve real-life problems. In the coming decade, the country that emerges on top in AI will lead the Fourth Industrial Revolution

The AI thematic intelligence report identifies the key trends impacting the growth of the theme over the next 12 to 24 months. It also includes a comprehensive industry analysis, including market size and growth forecasts for AI hardware, AI platforms, AI consulting and support services, and specialized AI applications.

AI – Industry Analysis

The AI industry was worth $81.3 billion in 2022. The market is expected to achieve a CAGR of more than 21% between 2022 and 2030. The specialized applications category in the AI market is currently the largest market segment yet AI platforms are anticipated to be the fastest-growing segment. Thus, a significant proportion of AI hardware revenues and sales of consulting and support services are driven by the sale of specialized AI applications, such as CV and conversational platforms.

The AI industry analysis also covers:

  • Mergers and acquisitions
  • Venture Financing
  • Patent Trends
  • Company filings trends
  • Hiring trends
  • Social media trends
  • Timeline

AI Revenue by Product 2019-2030

AI Revenue by Product 2019-2030

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AI - Trends

The AI trends consist of technology trends, macroeconomic trends, and regulatory trends.

Technology Trends: The main technology trends shaping the AI theme are AI accelerators, the AGI debate, quantum neural networks, and neuromorphic computing among others.

AI accelerators are basically chips designed to perform AI tasks more efficiently, thereby reducing the time taken, for instance, processing the large data sets associated with machine learning. Using neural networks for real-life use cases has put significant pressure on the capabilities of existing hardware. However, AI accelerators are emerging as the solution to this problem. This, in turn, will drive the artificial intelligence market trends growth during the forecast period.

Macroeconomic Trends: The main macroeconomic trends shaping the AI theme are AI talent, the tech war between China and the US, and trade wars among big powers among others.

Regulatory Trends: The main regulatory trends shaping the AI theme are regulatory divergence to monitor the usage of AI, the resurgence in industrial protectionism, and concerns regarding AI ethics among others.

AI – Value Chain

The value chain for artificial intelligence (AI) is segmented into hardware, data management, foundational AI, advanced AI capabilities, and delivery.

Delivery: AI delivery models are similar to an IT system, although the AI specificities lead to a preference for either AI as a service (AIaaS) or hardware appliances. Moreover, the key layers of delivery are hardware appliances, licensed software, and AIaaS.

AI Value Chain

AI Value Chain

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AI – Competitive Landscape

Some of the leading public companies making their mark within the AI theme are:

  • Alibaba: It is a global technology leader because of its massive ecosystem, which spans entertainment, e-commerce, financial services, cloud services, and social media. The company has been front and center in China’s drive to become the world leader in AI. Furthermore, Alibaba is a major backer of facial recognition leader SenseTime and neural network star Cambricon as it is working closely with the government.
  • Alphabet (parent company of Google, Waymo, and DeepMind): One of the biggest assets of Alphabet is its wealth of customer data provided by its search business and YouTube. The tech giant has been heavily involved in AI-related M&A activity, with its 2014 acquisition of ML pioneer DeepMind the most well-known.
  • Amazon: It has been pushing AI, with a particular focus on CV technology, in different areas of its business for several years. The tech giant has been under pressure from civil liberties groups to stop selling its Rekognition software to police forces due to the potential for abuse by the authorities. However, Amazon’s investment in ML and sensors (for use in its Go stores) and its advanced cloud operations illustrate its leadership in key technologies to enable AI.

Some of the leading private companies making their mark within the AI theme are:

  • Brain Corp: It is a US start-up developing core technology for the robotics industry across industries and applications The company’s core product is BrainOS, an AI software platform for autonomous mobile robots (AMRs) operating in indoor public spaces. It allows them to navigate autonomously, avoid obstacles, adapt to changing environments, manage data, and seamlessly interact with end-users.
  • Cerebras Systems: Cerebras Systems is an AI company that builds computer systems for complex deep-learning applications, including semiconductor components.
  • Graphcore: It is a semiconductor company that develops AI accelerators, which it calls intelligence processing units (IPUs). They are designed to provide massive parallelism and to hold the complete machine-learning model inside the processor.

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Application Software Sector Scorecard

At GlobalData, we use a scorecard approach to predict tomorrow’s leading companies within each sector. Our Retail and apparel sector scorecard has three screens: a thematic screen, a valuation screen, and a risk screen.

  • The thematic screen ranks companies based on overall leadership in the 10 themes that matter most to their industry, generating a leading indicator of future performance.
  • The valuation screen ranks our universe of companies within a sector based on selected valuation metrics.
  • The risk screen ranks companies within a particular sector based on overall investment risk.

Application Software Sector Scorecard – Thematic Screen

Application Software Sector Scorecard – Thematic Screen

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AI Market Report Overview

Report Pages 90
Regions Covered Global
Market Size (2022) $81.3 billion
CAGR (2022-2030) >21%
Forecast Period 2022-2030
Key Trends Technology Trends, Macroeconomic Trends, and Regulatory Trends
Key Public Companies Alibaba, Alphabet (parent company of Google, Waymo, and DeepMind), Amazon, and AMD
Key Private Companies Brain Corp, Cerebras Systems, Graphcore, H2O.ai, and Hive

Key Highlights

  • Despite the hype, artificial general intelligence (AGI), or the ability of machines to do anything that a human can and possess consciousness, is still decades away. However, ‘good enough’ AI is already here, capable of interacting with humans, motion, and making decisions. For example, OpenAI’s GPT-3 and ChatGPT models can write original prose and chat with human fluency, DeepMind’s algorithms can beat the best human chess players, and Boston Dynamics’ Atlas robots can somersault. If this evolution continues, it could upend the labor-based capitalist economic model.
  • Driven by ethical and political concerns, using AI for facial recognition will lead to conflict in standards and regulatory approaches. This will lead to the break-up of the global supply chain in the AI segment, as is already underway in semiconductors. Ultimately stricter ethical regulation will break the global AI market into geopolitical silos, in isolation from one another.

Ab Initio
ABB
Advantech
AEye
Algorithmia
Alibaba
Alphabet
Alteryx
Amazon
Ambarella
AMD
ANYbotics
Apple
Aptiv
Ataccama
Attivio
Aurora
Autodesk
BAE Systems
Baidu
Basler
Beijing Academy of Artificial Intelligence (Wu Dao)
BigML
BMC Software
Boomi
Brain Corp
C3.ai
Cambricon
Celigo
Cerebras
Clarifai
Cloud Software Group
Cloudera
CloudWalk
Cognex
CognitiveScale
Cohesity
Continental
Couchbase
Cyclr
Data Virtuality
Dataiku
DataStax
DeepAI
Denso
Epic Games
Exasol
Facewatch
Festo
Fetch Robotics
GM (Cruise)
Graphcore
Groq
H2O.ai
Hahn Group (Rethink Robotics)
Hawk-Eye Innovations
HCL Technologies
Hikvision
Hitachi
Hive
Horizon Robotics
HPE
Huawei
Hugging Face
Hyundai (Boston Dynamics)
IBM
iFlytek
ImmersiveTouch
Infineon
Informatica
Intel
iRobot
Jasper Art
Keras
Kernel
Keyence
Khronos Group (OpenCL)
Lockheed Martin
Lumentum
Luminar Technologies
Magna
MakeML
MarkLogic
MathWorks
Megvii (Face++)
Merative
Meta
Microsoft
Midea (KUKA)
Midjourney
Mindmaze
MindsEye
Mobileye
MongoDB
Nauto
NEC
Neurala
Neuralia
Neuralink
Neuroelectrics
NightCafe
Nippon Ceramic
Northop Grumman
Nvidia
Okta
Omron
OpenAI
OpenNN
Oracle
Palantir
Panasonic
Panoply
PayPal (Simility)
Pony.ai
Precisely
Profisee
Prophesee
Qualcomm
RapidMiner
Renesas
Restb.ai
Rockwell Automation
Rohm
ROS-Industrial
Samsung Electronics
SAP
SAS
SenseTime
Sherpa.ai
SiLC
Snowflake
Software AG
SoundHound
SparkCognition
Splunk
Stemmer Imaging
StreamSets
Talend
TE Connectivity
Teledyne
Tencent
Teradata
Teradyne
Tesla
Texas Instruments
Toshiba
Tung Thih
Unity Technologies
Velodyne
Veritas
Visteon
VoltDB
Voyant Photonics
Wolfram
Workato
World Wide Web Consortium (Semantic Web)

Table of Contents

  • 1. Executive Summary
  • 2. Players
  • 3. Technology Briefing

    • 3.1. What is AI?
    • 3.2. Branches of AI
    • 3.3. The AI roadmap
    • 3.4. Advanced AI capabilities

  • 4. Trends

    • 4.1. Technology trends
    • 4.2. Macroeconomic trends
    • 4.3. Regulatory trends

  • 5. Industry Analysis

    • 5.1. Market size and growth forecasts
    • 5.2. Mergers and acquisitions
    • 5.3. Venture financing
    • 5.4. Patent trends
    • 5.5. Company filings trends
    • 5.6. Hiring trends
    • 5.7. Social media trends
    • 5.8. Use cases
    • 5.9. Timeline

  • 6. Value Chain

    • 6.1. Hardware
    • 6.2. Data management
    • 6.3. Foundational AI
    • 6.4. Advanced AI capabilities
    • 6.5. Delivery

  • 7. Companies

    • 7.1. Public companies
    • 7.2. Private companies

  • 8. Sector Scorecards

    • 8.1. Application software sector scorecard
    • 8.2. Semiconductor sector scorecard
    • 8.3. Consumer electronics sector scorecard

  • 9. Glossary
  • 10. Further Reading
  • 11. Our Thematic Research Methodology
  • 12. About GlobalData
  • 13. Contact Us

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