This research evaluates the artificial general intelligence market including leading companies, services potential, technology integration, and application ecosystem. The report also analyzes the AI agent market and the relationship between general purpose AI with other technologies including edge computing, 5G networks, and blockchain.
The report provides forecasts from 2020 through 2025 for the artificial general intelligence market by application and industry verticals, globally and regionally. The report also estimates the AI agent driven market for software and platform globally and regionally along with AI embedded deployment forecasts for IoT devices, semiconductors, and software.
The productivity gain potential for business use of AI represents approximately $1.8T in economic value by 2027, which will be nine times more with the use of general-purpose AI solutions market as compared to today's silo AI approach. Productivity gains will be achieved by transactions conducted by AI autonomous agents or “bots”. It is estimated that more than 8% of the global economic activity in 2027 will be done autonomously by some kind of AI solution whereas this amounts to less than one percent today. This represents a dramatic rise in use of AI for enterprise, industrial, and government automation.
Currently, less than 20% of enterprise and industrial organizations are deploying AI-embedded smart machines. This will grow to nearly 70% of growth companies by 2027. More than 75% of business analytics software will use AI capabilities by 2027, but much of it will continue to require human intervention of some type. The primary productivity gains for general-purpose AI will be those systems and processes that may act autonomously with minimal errors and virtually no threat to human health and wealthfare.
The evolution of public policy governing AI remains an impediment to general purpose AI and will remain the case through 2027. The critical area of concern will continue to be security and privacy, but other areas include innovation policy, revenue recognition and taxation. Second only to concerns for general privacy/security concerns are the need for laws and policies governing civil and criminal liability. For example, when an AI-enabled machine causes damage (physical and/or cyber), there needs to be a basis of determining fault and liability for all parties including user, operator, owner, manufacturers, etc.
Also known as Artificial General Intelligence (AGI), General Purpose Artificial Intelligence represents silicon-based Artificial Intelligence (AI) that mimics human-like cognition to perform a wide variety of tasks that span beyond mere number crunching. Whereas most current AI solutions are limited in terms of the type and variety of problems that may be solved, AGI may be employed to solve many different problems including machine translation, natural language processing, logical reasoning, knowledge representation, social intelligence, and numerous others.
Unlike many early AI solutions that were designed and implemented with a narrow focus, AGI will be leveraged to solve problems in many different domains and across many different industry verticals including 3D design, transforming customer service, securing enterprise data, securing public facility and personnel, financial trading, healthcare solution, highly personalized target marketing, detecting fraud, recommendation engines, autonomous vehicles and smart mobility, online search, and many other areas. AGI is rapidly evolving in many areas. However, scalability and other issues remain as challenges, which will likely not be fully resolved until the 2025 to 2030 timeframe.
Target Audience:
Select Report Findings:
Report Benefits:
Companies in Report:
The report provides forecasts from 2020 through 2025 for the artificial general intelligence market by application and industry verticals, globally and regionally. The report also estimates the AI agent driven market for software and platform globally and regionally along with AI embedded deployment forecasts for IoT devices, semiconductors, and software.
The productivity gain potential for business use of AI represents approximately $1.8T in economic value by 2027, which will be nine times more with the use of general-purpose AI solutions market as compared to today's silo AI approach. Productivity gains will be achieved by transactions conducted by AI autonomous agents or “bots”. It is estimated that more than 8% of the global economic activity in 2027 will be done autonomously by some kind of AI solution whereas this amounts to less than one percent today. This represents a dramatic rise in use of AI for enterprise, industrial, and government automation.
Currently, less than 20% of enterprise and industrial organizations are deploying AI-embedded smart machines. This will grow to nearly 70% of growth companies by 2027. More than 75% of business analytics software will use AI capabilities by 2027, but much of it will continue to require human intervention of some type. The primary productivity gains for general-purpose AI will be those systems and processes that may act autonomously with minimal errors and virtually no threat to human health and wealthfare.
The evolution of public policy governing AI remains an impediment to general purpose AI and will remain the case through 2027. The critical area of concern will continue to be security and privacy, but other areas include innovation policy, revenue recognition and taxation. Second only to concerns for general privacy/security concerns are the need for laws and policies governing civil and criminal liability. For example, when an AI-enabled machine causes damage (physical and/or cyber), there needs to be a basis of determining fault and liability for all parties including user, operator, owner, manufacturers, etc.
Also known as Artificial General Intelligence (AGI), General Purpose Artificial Intelligence represents silicon-based Artificial Intelligence (AI) that mimics human-like cognition to perform a wide variety of tasks that span beyond mere number crunching. Whereas most current AI solutions are limited in terms of the type and variety of problems that may be solved, AGI may be employed to solve many different problems including machine translation, natural language processing, logical reasoning, knowledge representation, social intelligence, and numerous others.
Unlike many early AI solutions that were designed and implemented with a narrow focus, AGI will be leveraged to solve problems in many different domains and across many different industry verticals including 3D design, transforming customer service, securing enterprise data, securing public facility and personnel, financial trading, healthcare solution, highly personalized target marketing, detecting fraud, recommendation engines, autonomous vehicles and smart mobility, online search, and many other areas. AGI is rapidly evolving in many areas. However, scalability and other issues remain as challenges, which will likely not be fully resolved until the 2025 to 2030 timeframe.
Target Audience:
- AI companies
- Robotics companies
- Investment organizations
- Data management vendors
- Industrial automation companies
- Enterprise across all industry verticals
Select Report Findings:
- Embedded AI in building infrastructure and equipment will reach $16.7B globally by 2025
- The general-purpose AI market will reach $3.83B globally by 2025 for enterprise apps and solutions
- The global market for general-purpose AI support of big data and prescriptive analytics will reach $1.18B
- Over 35% of enterprise value will be directly or indirectly attributable to general-purpose AI solutions by 2027
Report Benefits:
- General AI market forecasts for global and regional 2020 to 2025
- Understand the technology and application stack for general purpose AI
- Identify leading AGI solution providers, strategies, and market positioning
- Identify leading applications and industry verticals for general AI solutions
- Understand the relationship between AI and 5G, edge computing, and blockchain
Companies in Report:
- Agent.ai
- AIBrian Inc.
- Amazon Inc.
- API.AI
- Apple Inc.
- AT&T Speech API
- Ayasdi
- Baidu Inc.
- Bigml Inc.
- Brighterion Inc.
- CloudMinds
- Diffbot
- Digital Reasoning Systems Inc.
- DigitalGenius
- Facebook Inc.
- Fair Isaac Corporation
- General Electric (GE)
- General Vision Inc.
- GoodAI
- Google Inc.
- H2O.ai
- Hewlett Packard Enterprise (HPE)
- IBM Corporation
- Infosys Nia
- Intel Corporation
- InteliWISE
- KAI
- LG Electronics
- Meya
- Microsoft Corporation
- MindMeld
- motion.ai
- Nuance Communications Inc.
- PointGrab Ltd.
- PredictionIO
- Premonition
- Rainbird
- Receptiviti
- Salesforce
- SAS Institute Inc.
- Sentient Technologies Holdings Limited
- SK Telecom
- SparkCognition Inc.
- Tellmeplus
- Tend.ai
- TensorFlow
- Vicarious
- Vital AI
- Wipro HOLMES
- Wit.ai
- X.ai
- Zebra Medical Vision Inc.