A 263-page report on the enterprise Generative AI market, incl. market sizing & forecast, competitive landscape, end user adoption, trends, challenges, and more.
The "Generative AI Market Report 2025-2030" is part of IoT Analytics' ongoing coverage of enterprise technology markets. The information presented in this report is based on the results of secondary research and qualitative research, i.e., interviews with experts with experts in the field. The main purpose of this document is to help our readers understand the current Generative AI (GenAI) landscape and potential use cases.
What is Generative AI?
GenAI is a deep-learning technique based on variational autoencoders, generative adversarial networks, and transformer-based models.
SAMPLE VIEW
What is a Data Center GPU?
The market segment for data center GPUs refers to specialized graphics processing units designed to handle the extensive computational demands of modern data centers. These GPUs are engineered to accelerate a variety of complex workloads, including high-performance computing, DL, ML, and large-scale graphics processing tasks. The market does not include spending on CPUs, consumer-grade GPUs, or application-specific integrated circuits (ASICs). It includes GPU systems such as specialized GPU server racks. The market only includes external spending but not spending on developing own chips e.g., Google's TPUs or AWS' Trainium or Inferentium.
SAMPLE VIEW
What are foundational models and model management platforms?
This market segment includes both foundational models and model management platforms.
1. Foundational models are large-scale, pre-trained models that can be adapted to a wide variety of tasks without the need for training from scratch, such as language processing, image recognition, and decision-making algorithms.
2. Model management platforms are software platforms that enable users to deploy, fine-tune, and call GenAI models. Model management platforms allow the use of different GenAI models and are not limited to one single model vendor. The market does not include chatbots and applications such as ChatGPT.
SAMPLE VIEW
What are Gen AI services?
GenAI services represent a specialized market segment dedicated to consulting, integration, and implementation support for organizations aiming to integrate GenAI capabilities. These services are tailored to help businesses conceptualize, develop, and execute strategies that leverage GenAI technologies for enhanced innovation, efficiency, and value creation. Services includes consulting, integration, and managed services.
Five building blocks make up the Generative AI stack
4. Critical backend infrastructure such as data processing and GPUs
5. Governance frameworks for security and compliance
The report includes a structured repository of 530 generative AI projects.*
Database structure
Column name
Description
Company
Name of the company that implemented the project.
Industry (ISIC classification)
Industry classification (ISIC code) of the customer
Project description
A brief description of the project
Country
Country that the project took place in
Region
Region that the project took place in
Vendor
Name of the vendor that has published the case study/project on their website
Year
Year that the project was implemented
Link
Unique identifier of each case study/project
Key department and activities that are improved by each project
Each project is grouped into one or more of the follogin departments: Sales, Marketing, Operations/mfg, Maintenance/field service, Finance and account, Human resources, IT/technology, Research and development, Customer service/support, Legal and compliance, Procurement, Logistics and supply chain, Corporate strategy/business development, Facility management. A project can touch mulitple departments. Each department is broken down into key activities.
The database is suited for:
AI strategy/business case development
Sector scan+Customer/vendor selection
Competitive analysis
Go-to-market/market entry strategy
And more
Questions answered:
What is GenAI, and what are its technological components?
Which GenAI use cases and applications are being prioritized by enterprises right now?
What is the current market size for GenAI, and what are the market shares of key players ?
Who is leading the market for GenAI models and platforms?
Which companies offer AI accelerators beyond NVIDIA?
Which consulting and professional services companies are selling the most GenAI projects?
How do the leading GenAI models compare?
What are some of the important implementation considerations for GenAI?
What are the current and next trends and challenges around GenAI?
Companies mentioned:
A selection of companies mentioned in the report.
AMD
AWS
Accenture
Alibaba
Anthropic
Baidu
Capgemini
Cerebras
Cognizant
Cohere
Google
Groq
Huawei
Hugging Face
IBM
Infosys
Microsoft
Nvidia
OpenAI
Table of Contents
1. Executive Summary
2. Introduction
Chapter overview: Introduction
Starting point: Understanding GenAI and its relationship with AI, ML, and DL
The history of GenAI
Interest in GenAI
Investments in GenAI start-ups
AI advances: (Gen)AI surpasses human capabilities in many tasks
GenAI models
GenAI adoption by industry
GenAI adoption by business function
Negative consequences of GenAI adoption
GenAI model building/integration approaches
Case study: AI at Thomson Reuters
Beneficiaries of GenAI tech spending
3. Technology overview
Chapter overview: Technology Overview
The GenAI tech stack: 5 main blocks
Foundation models: The transformer architecture
Foundation models: What are foundation models?
Foundation models: Type - Language models
Foundation models: Type - Vision models
Foundation models: Type - Speech/audio models
Foundation models: Type - Multimodal models
Foundation models: Type - Industry-specific models
Foundation models: Optimization techniques
Foundation models: Comparing GenAI models
Foundation models: Best-performing models
Foundation models: Open models
GenAI software ecosystem: The five main types of platforms
GenAI software ecosystem: The foundation model value chain