Artificial Intelligence
Market, Supplier, Risk and
Competitive Intelligence

Industry Outlook & Drivers

Global AI Industry Outlook

• The worldwide AI market was valued at $36.3 billion in 2019. The market is forecasted to grow at a CAGR of about 45.7 percent between 2019 and 2022, and it is estimated to reach $112.2 billion in 2022
• ML, predictive analytics, NLP, and image recognition are the prevalent technologies in AI space

Global AI: Industry Trends

• NLP and ML are major AI technologies, which are shaping the AI market space. Robotics, vision, and speech are also contributing significantly toward the artificial intelligence industry's growth
• Many start-up companies are entering the market, with new ideas and innovations, in the field of ML, vision, speech, and autonomous cars

Regional Market Outlook

North America

• The North American artificial intelligence market size is expected to grow at a CAGR of about 41-42 percent from 2018 to 2023

• The government & defense segments contributed the largest share to the North America's AI market size in 2018, and they would continue to be a dominant market until 2022, and it is expected to grow at a CAGR of 41 percent during the  AI market forecast period

• The US AI market is highly fragmented, with a presence of a huge number of start-ups in the country, however, the market is expected to undergo consolidation in the coming years, with tech giants, such as Apple, Google, Microsoft, Intel, Amazon, IBM, etc., thrusting on inorganic expansion in the country's AI market

• Growing trend of integration of video surveillance with AI for video analysis, coupled with rising government spending on cyber security solutions, integrated with real-time analytics and AI, is expected to boost the AI market in the US over the next five years

Europe

• The European AI market is expected to grow at a CAGR of about 43 percent till 2023

• The ML segment continues to contribute the majority of the revenue share of the European AI market from 2014 to 2016. It would continue to be a dominant market until 2022 and is expected to grow at a CAGR of ~40 percent during the forecast period

• Germany has the major revenue share of the European AI market, with a Y-o-Y increase of ~40 percent

• Robotics, manufacturing, and healthcare are the major end-user industries implementing AI

Global AI: Drivers and Constraints

Drivers
Automation and accuracy

• With the technological advancement, automation is playing a major role in changing business processes, with precision while saving time.

Product innovation

•  In the current market scenario, enterprises are constantly evolving to meet the end-user expectation. Hence, various organizations are coming up with innovative product, which are technically advanced.

Strategic Assistance for Enterprises

• With AI being implemented across various business verticals, it delivers value by augmenting human skills and extending their capabilities, i.e., higher customer engagement/satisfaction, smarter and more efficient R&D, optimized production and maintenance, and more efficient & effective sales/marketing campaigns will begin to create a sustainable competitive advantage. Competitors who delay adoption may find themselves in a challenging situation.

Constraints
Lack of Technical & Functional Ambiguity

•  AI takes minimal implementation time, yet, it would be difficult for the workforce to adopt the change in technical and operating requirements for effective implementation, as it involves risk factors across multiple impact points.
• An enterprise-wide AI Implementation also increases expectation and hype levels among the workforce. As a result, they would be considered as a replacement to optimization, simple analysis, and mundane automation.This change in perception from enterprise would frame AI as a mere glorified tool to solve problems, which, in a way, is de-sensitizing the technology even before it has a chance to prove its own value.

AI: Technology Overview

Market Share by Technology

• NLP is the technology from AI, which is predominantly developed and used in the real world

• Major companies develop AI focussed on NLP and ML platforms, with a funding of $1.1 and $3.4 billion, respectively

• Tier-1 companies are also investing in budding start-ups to encourage new ideas and innovations

• Google, Apple, Microsoft, Facebook, NVIDIA, IBM, etc., are some of the companies developing NLP and ML platforms

Widely Used AI Technologies

• Enterprises are adapting to the technological advancement in their business area by implementing AI technologies 

• Voice recognition, automated responses, virtual assistants are proving to be helpful, time-saving, and cutting down on non-value services

• ML and expert systems are AI technologies, which work on algorithms, previous cause-and-effect scenarios, etc., to arrive at decisions. Enterprises are actively participating in knowledge-sharing activities with technology companies

• Predictive analytics is widely adopted by enterprise data evaluation. Because of its quick response time and accuracy,  it also helps perform functions and calculations, which were not possible to perform manually

AI: Industry Applications

• Video analytics in retail integrated with surveillance cameras provides situational awareness of business operations, delivering insights about risk, safety, and security.

• Speech recognition technologies integrated into call centers automate the identification of callers.

• Personal assistants on consumer smartphones provide guidance and services using natural language and enhanced search using individual verbal communication.

• Automated approval or credit decision. Such capabilities can deliver accurate decisions in a fraction of the time compared to manual decision making.

• In healthcare, cognitive analytics enables better treatment and analysis for patients with potential abnormalities.

• In legal research, cognitive expert systems aid in accessing millions of data sources, synthesize information and present it as a user-dashboard.

• Software tools and personal agents can understand user work patterns and thereby enhance productivity. E.g., Mailbox and Calendar sorting by user preference.

AI: Major Market Developments

Healthcare

• Patient diagnosis using their baseline health data 

• Early identification of pandemic, epidemic, and endemic diseases

• Imaging diagnostics (radiology, pathology)

• Medical insurance and claims scheduling

• Medical data-driven diagnostics and virtual drug development

• Deployment of robot doctors in patient diagnosis and treatment

Automotives

• Autonomous fleets for ride-sharing, 

• Driver assist, engine monitoring and predictive maintenance 

• Automated driver assistance systems (e.g., parking assistance, lane correction, and centering, adaptive cruise control, etc.).

• Just-in-time/on-demand parts manufacturing and maintenance

Finance

• Customized financial planning and assistance 

• Fraud detection and anti-money laundering 

• Automation of banking processes, i.e., back office, customer-facing roles, etc.

• Automated insurance underwriting

Implementation Framework for AI

• Presently, enterprises are adopting innovative approaches to their IT infrastructure for gaining maximum benefits from cognitive computing implementation.
• Enterprises are integrating their existing traditional systems/architecture into dynamic, open standard-based infrastructure with the inclusion of cloud
  (public/private/hybrid) as the fundamental component.

AI: Major Market Developments

• Artificial Intelligence market in China will gain close to $7 trillion with the aid of AI deployment