Generative AI

Generative AI Market by Offering (Services, Software), Generative Model Type (Autoencoders, Convolutional Neural Networks, Deep Learning Models), Function, Application, End-use - Global Forecast 2024-2030

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[185 Pages Report] The Generative AI Market size was estimated at USD 14.58 billion in 2023 and expected to reach USD 19.21 billion in 2024, at a CAGR 33.24% to reach USD 108.72 billion by 2030.

Generative AI Market
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Generative AI, a part of artificial intelligence technologies, focuses on generating new content, data, and information similar to original inputs. It incorporates machine learning algorithms to produce outputs that can include text, images, music, voice, and other forms of media. These technologies have found applications across various sectors, including entertainment, automotive, and healthcare, for tasks such as content creation, drug discovery, and personalized customer experiences. The availability of more powerful and cost-effective computing resources, both in terms of hardware, including GPUs and cloud services, has made it feasible to train complex generative AI models on large datasets, fostering market growth. The exponential growth of data generated online provides ample training material for generative AI models, enabling them to learn and mimic various patterns, creating a platform for market growth. Increased interest and investment from both public and private sectors, coupled with collaborations between academia and industry, are accelerating the development and application of generative AI technologies. Data privacy and security issues with the usage of generative AI hamper the market growth. Continuous research and improvements in deep learning architectures, particularly in neural networks that enhance the capabilities of generative AI, are expected to create opportunities for market growth.

Regional Insights

In the Americas, the United States stands out as a pivotal hub for generative AI development with the rising presence of technology companies and a dynamic startup ecosystem. Canada also plays a crucial role, particularly in academic and research contributions, with its institutions being renowned for breakthroughs in AI and machine learning. South American countries are progressively embracing generative AI, with Brazil and Mexico expanding adoption across sectors such as finance, media, and retail. The APAC region exhibits a vibrant and diverse landscape for generative AI, characterized by rapid adoption and innovation. China, with its government's strategic focus on AI as a core technology for future development. The country is home to numerous AI giants and startups pioneering generative AI applications across various sectors, including entertainment, manufacturing, and healthcare. South Korea and Japan are notable for their technological prowess, with extensive research and development in robotics and AI, integrating generative models in various industrial and consumer applications. The EMEA region presents a complex picture due to its cultural, economic, and regulatory diversity. Europe is at the forefront, with several countries exhibiting strong commitments to AI research and development. The European Union's investment in AI, along with a focus on ethical standards and regulations such as the AI Act, underscores the region’s balanced approach towards fostering innovation while ensuring responsible AI deployment. The UK, Germany, and France are notable for their vibrant ecosystems comprising academia, startups, and established companies focusing on generative AI applications in finance, healthcare, and automotive sectors. In the Middle East, countries such as the UAE and Israel are investing in AI technologies, including generative AI, to drive economic diversification and innovation. The UAE, in particular, has launched several initiatives to become a global AI hub, integrating generative AI in public services, healthcare, and education. South Africa’s engagement with generative AI is in growing stages, with South Africa, Egypt, and Nigeria focusing primarily on applying AI in healthcare, agricultural, and financial inclusion projects.

Offering: Rising usage of software associated with generative AI for the creation, customization, and deployment of AI models

Managed services in the context of generative AI involve the outsourcing of certain operational aspects, such as infrastructure management, performance monitoring, and security of AI models. These services aim to offload complex, day-to-day management responsibilities, enabling organizations to focus on strategic objectives and core competencies. Professional services include specialized services that are typically consultative or project-based. Professional services leverage experts in the field to provide custom solutions, from the development of tailored AI models to integration and optimization advice. The focus is on delivering unique value based on specific client goals and challenges. Support & maintenance services ensure the continuous, efficient, and secure operation of AI systems. This includes technical support, software updates, and routine maintenance aimed at minimizing downtime and preserving the integrity and performance of AI implementations. System integration & implementation services address the challenges of integrating Generative AI technology within existing IT environments. Professionals assist in the seamless incorporation of AI solutions, ensuring compatibility, functionality, and optimal performance. The goal is to create a unified system that leverages AI capabilities without disrupting current processes. Training & consulting services play a crucial role in educating and guiding organizations. This encompasses training teams to utilize AI tools effectively, consulting on strategy and implementation, and fostering an understanding of ethical considerations and potential implications of AI technology. The software component of Generative AI offerings includes platforms and tools that enable the creation, customization, and deployment of AI models. These range from text and image generation engines to more specialized applications designed for specific industries or functions. Key characteristics include user-friendly interfaces, scalability, and integration capabilities, ensuring that even those without deep technical expertise leverage the power of Generative AI.

End-use: Increasing use of generative AI in the government & defense for cybersecurity and simulation of scenarios for strategic planning

Generative AI is making strides in fraud detection, personalized banking services, and risk management in the BFSI sector. By generating realistic financial scenarios, it aids in stress testing and decision-making processes. It also enhances customer experience through personalized financial advice and product recommendations. The building & construction industry benefits from Generative AI through the optimization of construction processes and designs. It assists in creating more efficient and sustainable building structures by exploring countless configurations, thus reducing costs and environmental impact. Generative AI plays a crucial role in predicting demand and optimizing energy distribution. It assists in generating scenarios for energy production, including renewable energy sources, to enhance grid management and reduce carbon footprints. In government & defense, generative AI is instrumental for cybersecurity, surveillance, and simulation of various scenarios for strategic planning. It also aids in public service delivery by automating and personalizing citizen services. Healthcare & life sciences see transformative applications of generative AI in drug discovery, personalized medicine, and diagnostic procedures. Generating molecular structures and simulating their interactions accelerates the development of new therapeutics. In diagnostics, it helps in the detection and interpretation of diseases from medical imagery. Generative AI advances programming assistance, network optimization, and cybersecurity in the IT & telecommunication industry. It automates code generation and testing while also optimizing network traffic and predicting infrastructure failures. The manufacturing industry utilizes Generative AI to streamline production lines, improve product design, and manage supply chains. It enables predictive maintenance, reducing downtime and operational costs. In media & entertainment, generative AI is revolutionizing content creation, including music, literature, and video games. It provides tools for creators to generate novel content, enhancing creativity and reducing production times. Generative AI enhances personalized shopping experiences, inventory management, and demand forecasting in the retail and e-commerce sectors. It generates personalized recommendations and promotional content, improving customer engagement and sales. In transportation, generative AI optimizes route planning and logistics, improving fuel efficiency and reducing delivery times. Generative AI improves efficiency in logistics by optimizing route planning, warehouse operations, and freight management. It reduces operating costs and enhances delivery times, offering significant advantages in a highly competitive market.

Market Dynamics

The market dynamics represent an ever-changing landscape of the Generative AI Market by providing actionable insights into factors, including supply and demand levels. Accounting for these factors helps design strategies, make investments, and formulate developments to capitalize on future opportunities. In addition, these factors assist in avoiding potential pitfalls related to political, geographical, technical, social, and economic conditions, highlighting consumer behaviors and influencing manufacturing costs and purchasing decisions.

Market Disruption Analysis

The market disruption analysis delves into the core elements associated with market-influencing changes, including breakthrough technological advancements that introduce novel features, integration capabilities, regulatory shifts that could drive or restrain market growth, and the emergence of innovative market players challenging traditional paradigms. This analysis facilitates a competitive advantage by preparing players in the Generative AI Market to pre-emptively adapt to these market-influencing changes, enhances risk management by early identification of threats, informs calculated investment decisions, and drives innovation toward areas with the highest demand in the Generative AI Market.

Porter’s Five Forces Analysis

The porter's five forces analysis offers a simple and powerful tool for understanding, identifying, and analyzing the position, situation, and power of the businesses in the Generative AI Market. This model is helpful for companies to understand the strength of their current competitive position and the position they are considering repositioning into. With a clear understanding of where power lies, businesses can take advantage of a situation of strength, improve weaknesses, and avoid taking wrong steps. The tool identifies whether new products, services, or companies have the potential to be profitable. In addition, it can be very informative when used to understand the balance of power in exceptional use cases.

Value Chain & Critical Path Analysis

The value chain of the Generative AI Market encompasses all intermediate value addition activities, including raw materials used, product inception, and final delivery, aiding in identifying competitive advantages and improvement areas. Critical path analysis of the <> market identifies task sequences crucial for timely project completion, aiding resource allocation and bottleneck identification. Value chain and critical path analysis methods optimize efficiency, improve quality, enhance competitiveness, and increase profitability. Value chain analysis targets production inefficiencies, and critical path analysis ensures project timeliness. These analyses facilitate businesses in making informed decisions, responding to market demands swiftly, and achieving sustainable growth by optimizing operations and maximizing resource utilization.

Pricing Analysis

The pricing analysis comprehensively evaluates how a product or service is priced within the Generative AI Market. This evaluation encompasses various factors that impact the price of a product, including production costs, competition, demand, customer value perception, and changing margins. An essential aspect of this analysis is understanding price elasticity, which measures how sensitive the market for a product is to its price change. It provides insight into competitive pricing strategies, enabling businesses to position their products advantageously in the Generative AI Market.

Technology Analysis

The technology analysis involves evaluating the current and emerging technologies relevant to a specific industry or market. This analysis includes breakthrough trends across the value chain that directly define the future course of long-term profitability and overall advancement in the Generative AI Market.

Patent Analysis

The patent analysis involves evaluating patent filing trends, assessing patent ownership, analyzing the legal status and compliance, and collecting competitive intelligence from patents within the Generative AI Market and its parent industry. Analyzing the ownership of patents, assessing their legal status, and interpreting the patents to gather insights into competitors' technology strategies assist businesses in strategizing and optimizing product positioning and investment decisions.

Trade Analysis

The trade analysis of the Generative AI Market explores the complex interplay of import and export activities, emphasizing the critical role played by key trading nations. This analysis identifies geographical discrepancies in trade flows, offering a deep insight into regional disparities to identify geographic areas suitable for market expansion. A detailed analysis of the regulatory landscape focuses on tariffs, taxes, and customs procedures that significantly determine international trade flows. This analysis is crucial for understanding the overarching legal framework that businesses must navigate.

Regulatory Framework Analysis

The regulatory framework analysis for the Generative AI Market is essential for ensuring legal compliance, managing risks, shaping business strategies, fostering innovation, protecting consumers, accessing markets, maintaining reputation, and managing stakeholder relations. Regulatory frameworks shape business strategies and expansion initiatives, guiding informed decision-making processes. Furthermore, this analysis uncovers avenues for innovation within existing regulations or by advocating for regulatory changes to foster innovation.

FPNV Positioning Matrix

The FPNV positioning matrix is essential in evaluating the market positioning of the vendors in the Generative AI Market. This matrix offers a comprehensive assessment of vendors, examining critical metrics related to business strategy and product satisfaction. This in-depth assessment empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success, namely Forefront (F), Pathfinder (P), Niche (N), or Vital (V).

Market Share Analysis

The market share analysis is a comprehensive tool that provides an insightful and in-depth assessment of the current state of vendors in the Generative AI Market. By meticulously comparing and analyzing vendor contributions, companies are offered a greater understanding of their performance and the challenges they face when competing for market share. These contributions include overall revenue, customer base, and other vital metrics. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With these illustrative details, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.

Recent Developments
  • Strategic Acquisition of Clipdrop by Jasper Amplifies Multimodal Marketing Capabilities for Enterprises

    Jasper acquired Clipdrop from Stability AI, marking a monumental leap in Jasper's journey towards delivering an all-encompassing, multimodal support system specifically tailored for enterprise marketing teams. The fusion of Clipdrop's technology with Jasper's AI-driven marketing solutions is anticipated to revolutionize personalized marketing strategies, offering unparalleled automation and optimization capabilities. The acquisition underscores Jasper's expansion into the European market and its commitment to nurturing the AI ecosystem in Paris. [Published On: 2024-02-22]

  • Visa Ventures into Generative Artificial Intelligence with a USD 100 Million Investment Fund

    Visa announced the initiation of a substantial USD 100 million venture fund dedicated to nurturing startups in the generative artificial intelligence (AI) domain, marking a significant endorsement of the field alongside technology giants. This move underscores the burgeoning interest in AI technologies, particularly following the widespread acclaim of the chatbot ChatGPT. Visa aims to explore and understand the transformative potential of generative AI beyond its current applications in tasks and content creation, particularly its impact on commerce. [Published On: 2023-10-03]

  • Infosys and Microsoft Embark on a Pioneering AI-Driven Collaboration

    Infosys announced its strategic collaboration with Microsoft to craft solutions by harnessing the power of Infosys Topaz, together with Azure OpenAI Service and Azure Cognitive Services. Uniting their AI expertise, both corporations aspire to revolutionize enterprise operations by offering AI-enhanced solutions across various sectors. The synergy with Microsoft enhances Infosys Topaz's capabilities, propelling businesses towards adopting AI-centric solutions, thereby strengthening operational efficiency, reducing processing times, safeguarding investments, and paving the way for innovative business models. [Published On: 2023-09-26]

Strategy Analysis & Recommendation

The strategic analysis is essential for organizations seeking a solid foothold in the global marketplace. Companies are better positioned to make informed decisions that align with their long-term aspirations by thoroughly evaluating their current standing in the Generative AI Market. This critical assessment involves a thorough analysis of the organization’s resources, capabilities, and overall performance to identify its core strengths and areas for improvement.

Key Company Profiles

The report delves into recent significant developments in the Generative AI Market, highlighting leading vendors and their innovative profiles. These include Accenture PLC, AI21 Labs Ltd., Amazon Web Services, Inc., Anthropic PBC, AssemblyAI, Inc., Clarifai, Inc., Databricks, Inc., DeepL SE, Dialpad, Inc., Genie AI Ltd., Google LLC by Alphabet Inc., Infosys Limited, International Business Machines Corporation, Lighttricks, Markovate, Inc., Meta Platforms, Inc., Microsoft Corporation, Midjourney, Inc., Mostly AI Solutions MP GmbH, OpenAI OpCo, LLC, Paige AI, Inc., Persado, Inc., Revery AI Inc., and Theai, Inc..

Generative AI Market - Global Forecast 2024-2030
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Market Segmentation & Coverage

This research report categorizes the Generative AI Market to forecast the revenues and analyze trends in each of the following sub-markets:

  • Offering
    • Services
      • Managed Services
      • Professional Services
        • Support & Maintenance Services
        • System Integration & Implementation Services
        • Training & Consulting Services
    • Software
  • Generative Model Type
    • Autoencoders
      • Denoising Autoencoders
      • Variational Autoencoders
    • Convolutional Neural Networks
    • Deep Learning Models
      • Feedforward Neural Networks
      • Gated Recurrent Units
      • Long Short-Term Memory Neural Networks
      • Recurrent Neural Networks
    • Generative Adversarial Networks
      • Conditional GANs
      • Cycle GANs
      • Style GANs
    • Rule-based Models
      • Expert Systems
      • Knowledge-based Models
      • Script-based Models
    • Statistical Models
      • Conditional Random Fields
      • Gaussian Mixture Models
      • Hidden Markov Models
      • Markov Models
    • Transformer-based Large Language Models
  • Function
    • Creative AI
    • Interactive AI
    • Predictive Models
  • Application
    • Application Development & API Integration
    • Customer Experience
    • Data Visualization
    • Digital Marketing
    • Fraud Detection/Risk Management
    • General Search & Insight Generation
    • Media Editing
    • Predictive Maintenance
    • Sales Intelligence
    • Synthetic Data Training
  • End-use
    • Banking, Financial Services & Insurance
    • Building & Construction
    • Energy & Utilities
    • Government & Defense
    • Healthcare & Life Sciences
    • IT & Telecommunication
    • Manufacturing
    • Media & Entertainment
    • Retail & eCommerce
    • Transportation & Logistics

  • Region
    • Americas
      • Argentina
      • Brazil
      • Canada
      • Mexico
      • United States
        • California
        • Florida
        • Illinois
        • New York
        • Ohio
        • Pennsylvania
        • Texas
    • Asia-Pacific
      • Australia
      • China
      • India
      • Indonesia
      • Japan
      • Malaysia
      • Philippines
      • Singapore
      • South Korea
      • Taiwan
      • Thailand
      • Vietnam
    • Europe, Middle East & Africa
      • Denmark
      • Egypt
      • Finland
      • France
      • Germany
      • Israel
      • Italy
      • Netherlands
      • Nigeria
      • Norway
      • Poland
      • Qatar
      • Russia
      • Saudi Arabia
      • South Africa
      • Spain
      • Sweden
      • Switzerland
      • Turkey
      • United Arab Emirates
      • United Kingdom

This research report offers invaluable insights into various crucial aspects of the Generative AI Market:

  1. Market Penetration: This section thoroughly overviews the current market landscape, incorporating detailed data from key industry players.
  2. Market Development: The report examines potential growth prospects in emerging markets and assesses expansion opportunities in mature segments.
  3. Market Diversification: This includes detailed information on recent product launches, untapped geographic regions, recent industry developments, and strategic investments.
  4. Competitive Assessment & Intelligence: An in-depth analysis of the competitive landscape is conducted, covering market share, strategic approaches, product range, certifications, regulatory approvals, patent analysis, technology developments, and advancements in the manufacturing capabilities of leading market players.
  5. Product Development & Innovation: This section offers insights into upcoming technologies, research and development efforts, and notable advancements in product innovation.

Additionally, the report addresses key questions to assist stakeholders in making informed decisions:

  1. What is the current market size and projected growth?
  2. Which products, segments, applications, and regions offer promising investment opportunities?
  3. What are the prevailing technology trends and regulatory frameworks?
  4. What is the market share and positioning of the leading vendors?
  5. What revenue sources and strategic opportunities do vendors in the market consider when deciding to enter or exit?

Table of Contents
  1. Preface
  2. Research Methodology
  3. Executive Summary
  4. Market Overview
  5. Market Insights
  6. Generative AI Market, by Offering
  7. Generative AI Market, by Generative Model Type
  8. Generative AI Market, by Function
  9. Generative AI Market, by Application
  10. Generative AI Market, by End-use
  11. Americas Generative AI Market
  12. Asia-Pacific Generative AI Market
  13. Europe, Middle East & Africa Generative AI Market
  14. Competitive Landscape
  15. Competitive Portfolio
  16. List of Figures [Total: 26]
  17. List of Tables [Total: 1130]
  18. List of Companies Mentioned [Total: 24]
The Emergence of Fully Automated Generative AI: Understanding the Scope
July 3, 2023
BLOG
The Emergence of Fully Automated Generative AI: Understanding the Scope
By now, most people are familiar with artificial intelligence (AI) and what it can do. Over the years, staggering developments have been observed in this field, with AI being used to solve complex problems in almost every industry. One area where AI is making significant headway is generative AI. This type of AI uses algorithms to generate new content, whether art, music or even entire websites. Generative AI has existed for some time, but people are on the verge of something entirely new – fully automated generative AI. This blog post explores what fully automated generative AI entails, its potential uses, and how it could impact the future of AI.

Generative AI is an exciting and rapidly evolving field, but also complicated. A breakdown of the various components that make it up is required to understand fully automated generative AI. Unlike traditional generative AI, which relies on human intervention to fine-tune the output, fully automated generative AI uses algorithms and machine learning to complete the entire process from start to finish. This means that it can generate entirely new content without human input. The potential uses for fully automated generative AI are vast and varied. For instance, it could speed up the content creation process for businesses, create original pieces of art or music, and even generate unique designs for architectural projects.

One area where fully automated generative AI could have a significant impact is the gaming industry. News reports suggest that some video game companies already use generative AI to create new content, but the process still needs to be faster and requires human oversight. With fully automated generative AI, game developers could create entire games faster without the time-consuming process of creating and designing the game world and characters from scratch.

However, with every new technological development comes potential downsides, and fully automated generative AI is no different. Some are concerned that fully automated generative AI could lead to job displacement, particularly in the creative industries. If this technology becomes sophisticated enough to replace human creativity entirely, it could have significant implications for people who work in fields such as writing, graphic design, and music. There are also concerns about the potential misuse of this technology, such as creating fake news or other forms of misinformation.

The emergence of fully automated generative AI is an exciting development with many potential uses. However, as with any new technology, there are potential downsides. As a society, it will be up to people to navigate these issues and ensure they use generative AI responsibly and ethically.

Frequently Asked Questions
  1. How big is the Generative AI Market?
    Ans. The Global Generative AI Market size was estimated at USD 14.58 billion in 2023 and expected to reach USD 19.21 billion in 2024.
  2. What is the Generative AI Market growth?
    Ans. The Global Generative AI Market to grow USD 108.72 billion by 2030, at a CAGR of 33.24%
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