Artificial Intelligence (AI) – Thematic Intelligence (Executive Briefing)

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Access and explore in-depth trends and insights in ourAI Executive Briefing report:

  • An overview of generative AI, placing it in the context of the broader AI theme.
  • Competitive landscape including trends and strategies through our polls and signals data.
  • Highlights patent filings, venture financing, social media mentions, hiring, and surveys.

How is the ‘AI Executive Briefing‘ report different from other reports in the market?

  • Generative AI is likely to pose a threat to every business across every sector in the coming years.
  • The impact will expand across sectors and business functions as generative AI becomes more accurate and is able to provide reliable factual advice.
  • This report will help businesses devise a comprehensive AI strategy.
  • It provides a strategic framework that sets out what you should do, based on how generative AI could impact your business.
  • Use cases range from customer support chatbots, and news and marketing content creation, to code writing and product design.

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

  • Technology Leaders and Startups
  • Business Development and Market Intelligence
  • Investment Analysts and Portfolio Managers
  • Professional Services – Investment Banks, PE/VC firms
  • M&A/Investment, Management Consultants, and Consulting Firms

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AI Theme Executive Briefing Analysis Report Overview

Artificial Intelligence market size was valued at $81 billion in 2022 dominated by computer vision and conversational platforms. Generative AI is the fastest growing advanced AI technology and is likely to pose a threat to every business across every sector in the coming years. The impact will expand across sectors and business functions as generative AI becomes more accurate and is able to provide reliable factual advice. Consequently, the AI market is expected to grow at a CAGR of more than 34% during 2022-2030.

Artificial Intelligence Market Outlook

Artificial Intelligence Market Outlook

For more insights on the AI market, download a free report sample

Artificial Intelligence (AI) thematic report provides an overview of generative AI, placing it in the context of the broader AI theme. It also provides market forecasts and analysis of data signals, including polls, patent filings, venture financing, social media mentions, and hiring.

Market Size 2022 ($Billion) $81 billion
CAGR % (2022-2030) >34%
Value Chain Components ·       Hardware

·       Data Management

·       Foundation AI

·       Advanced AI Capabilities

·       Delivery

Generative AI Use Cases ·       Customer Support

·       Operations

·       Production

·       Management

·       Product Development

·       IT

·       Marketing

·       Sales

Leading Vendors ·       Alibaba

·       AWS

·       Baidu

·       Google

·       IBM

·       Meta

·       Microsoft

·       Open AI

·       Anthropic

·       Cohere

·       Hugging Face

·       Stability. AI

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Artificial Intelligence Market Drivers

Staving off commoditization, AI-injected apps, operational efficiency, citizen data scientists, and consumer momentum are some of the major market drivers impacting the AI theme.

Consumer Momentum: The ease with which individuals can use ChatGPT has propelled generative AI into the headlines and onto the agendas of non-technical business leaders. It has stirred up widespread public interest in the technology and driven extensive curiosity into potential business applications.

AI-injected Apps: Providers are operationalizing generative AI for use within bespoke applications. Business transformation efforts are demanding generative AI integrations to move up the development stack and enhance customers’ image, video, and audio experiences.

For more insights on the AI market drivers, download a free report sample

Artificial Intelligence – Business Use Cases

Some of the generative AI business use cases are customer support, operations, production, management, product development, IT, marketing and sales.

Customer Support: An AI solution for customer relationship management. The solution offers multilingual capabilities and sentimental analysis that can increase customer satisfaction, generate insights, save time, strengthen data integrity, and automate processes.

Generative AI Roadmap Across SectorsGenerative AI Roadmap Across Sectors

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Artificial Intelligence – Value Chain Analysis

AI value chain can be segmented into five major components such as hardware, data management, foundation AI, Advanced AI capabilities, and delivery. The hardware layer comprises of semiconductors, cameras, sensors and lasers, servers, storage devices, networking equipment, and edge equipment.

Artificial Intelligence by Value Chain

Artificial Intelligence by Value Chain

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Artificial Intelligence – Leading Competitors

Some of the leading vendors making their mark in the AI theme are Alibaba, AWS, Baidu, Google, IBM, Meta, Microsoft, Open AI, Anthropic, Cohere, Hugging Face, and Stability. AI.

Alibaba: China-based Alibaba Cloud announced its beta version of ChatGPT, called Tongyi Qianwen, a LLM which will enhance its business apps including messaging platform DingTalk initially and e-commerce apps and mapping services later. The recent move makes sense considering Alibaba’s past investment in its LLM framework and subsequent open-sourcing of the AI model technology. It also increases its competitive threat to Chinese cloud rivals including Baidu.

IBM: IBM recently announced IBM Watson, a platform that includes access to models for generating computer code and text. fm.model.code enables users to create code using natural language; fm.model. NLP provides text generation capabilities. Part of its strategy includes a new partnership with Hugging Face, whose platform hosts AI/ML models. The start-up is known for its numerous models and datasets based on open-source code and technology.

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Key Highlights

  • The mass appeal of generative AI lies in its potential to perform tasks that existing AI applications have not yet been able to master. The ability to write code, generate training data, or create natural-sounding text opens the door to a range of potential horizontal and industry-specific applications yet to be discovered.
  • Enterprises will need to decide which model will work best with their specific use case, whether they will need to use multiple LLMs depending on their applications, and how much customization will be required to make the model work for their use case(s).
  • Organizations looking to scale their use of AI to include generative AI should implement multi-disciplinary AI and Ethics teams that evaluate new AI use cases and ensure they adhere to corporate ethical standards

Table of Contents

Executive Summary

Generative AI Overview

Business Impact

Vendor Landscape

Polls and Signals

Risks, Limitations, and Other Considerations

Appendix 1: Generative AI Tech Briefing

Appendix 2: Our Thematic Research Methodology

Frequently asked questions

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