How Big is AI Market? Depends on Your Assumptions

At the moment it is possible to generate an almost-arbitrary “market opportunity” for artificial intelligence, for a number of reasons, including notably the likelihood (virtual certainty) that AI will be embedded into most existing products and services. 

source: Business Insider 

In practice, equity analysts merge hardware, cloud infrastructure, core software, and services into what can be called the “AI technology stack.” That’s the complete infrastructure required to use AI features. Generally, those revenues are about half of total market estimates. 

The other half reflects vertical applications and functional deployments that integrate AI into specific economic sectors, industries and processes. 

Of course, we wind up double counting revenue if we tally “AI” revenues as including all apps, products and services that “use AI” in their value proposition, and then separately enumerate the value of those activities (software of all sorts, automated vehicles, search, social media, e-commerce, for example). 

Revenue Bucket	Representative Products / Activities Included	Key Analysts & Forecast Examples (2025–2035)	Share or Growth Focus by Analysts
Infrastructure Hardware	GPUs, accelerators, AI servers, high-bandwidth memory, edge AI chips, and networking equipment supporting AI compute	Goldman Sachs, Fortune Business Insights, Grand View Research	Base for most AI models; hardware CAGR ~28–30%, driven by hyperscalers (NVIDIA, AMD, Intel)
Cloud and AI-as-a-Service (AIaaS)	AI compute instances, APIs, training & inference services (AWS Bedrock, Azure OpenAI Service, Google Vertex AI)	McKinsey, Fortune Business Insights	70%+ of enterprise AI deployments run on cloud AI environments by 2030
Core Software / Platforms	Machine learning frameworks (TensorFlow, PyTorch), data labeling, MLOps tools, AI model management	IDC, Precedence Research, Grand View Research	Software accounts for ~35–48% of total revenue in 2025
Generative AI Platforms	LLMs, diffusion models, text/image/video generation tools (OpenAI GPT, Anthropic Claude, Midjourney, Runway)	Bloomberg Intelligence, Fortune Business Insights	Estimated $1.3 trillion addressable market by 2033, fastest-growing segment
Professional & Managed Services	Consulting, integration, model fine-tuning, ethical AI audits, and enterprise deployment services	McKinsey, Deloitte, PwC	Among fastest-growing components (CAGR >35%) as firms seek integration expertise
Cybersecurity & Risk AI	AI threat detection, fraud monitoring, anomaly detection, predictive risk analysis	Grand View Research, FinRofca	Included under “function” in future AI workflows; fastest CAGRs in enterprise use cases
Industry-Specific Applications (Vertical AI)	Applied AI in healthcare, BFSI, retail, automotive, manufacturing, law, agriculture	Grand View Research, Precedence Research	Analysts model vertical AI revenues separately (Healthcare, BFSI, Retail largest)
Embedded / On-device AI	Consumer and industrial IoT devices with local inference (smart glasses, phones, vehicles)	Grand View Research (Meta, Apple examples)	Growth tied to edge AI adoption; enables privacy-driven processing
AI Tools for Business Functions	HR tech, marketing, supply chain, operations, finance, customer service (chatbots, copilot-type agents)	Fortune Business Insights, Gartner	Functional AI makes up ~20–25% of total AI revenue by 2030
Quantum AI & Neuromorphic AI (emerging)	Quantum-accelerated AI algorithms, brain-like computing hardware for future models	Fortune Business Insights, McKinsey Technology Outlook	Described as post-2030 “third wave” AI enabler, with gradual commercial integration