AI Software
AI Software covers the layer of the AI stack above the chip: the labs that build foundation models (OpenAI, Anthropic, Google DeepMind, xAI, Meta, Mistral, DeepSeek, Qwen), the cloud and inference platforms that serve those models at scale (Azure AI, AWS Bedrock, Vertex AI, CoreWeave, Nebius, Together, Fireworks), the data and ML platforms that connect models to enterprise data (Databricks, Snowflake, MongoDB, HuggingFace, Scale), and the application companies that turn intelligence into product (ChatGPT, Cursor, Perplexity, Glean, Harvey, Sierra, Adobe Firefly, Salesforce Agentforce, Microsoft 365 Copilot). The sector spans both the frontier-lab revenue race and the much larger pool of AI revenue embedded inside Big Tech earnings, plus a fast-growing private-company universe that includes most of the highest-valued AI startups.

AI Software at a Glance
- •OpenAI annualized run-rate hit approximately $13B by late 2025, more than tripling year-over-year, per The Information and Reuters reporting.
- •Anthropic annualized run-rate reached approximately $5B by mid-2025, up from $1B at YE 2024, driven by enterprise API growth.
- •Microsoft Azure AI services contributed approximately 13 percentage points to Azure growth in FY2025-Q4, up from 6 to 7 points in FY2024 early quarters.
- •ChatGPT reached approximately 800M weekly active users in late 2025, the largest disclosed user base for any AI product.
- •Google Cloud served approximately 480T tokens per month as disclosed at I/O 2025, up from 9.7T per month a year earlier (roughly 50x).
- •DeepSeek R1 (Jan 2025) marked the inflection point on the open-versus-closed gap; open-weights models now sit within striking distance of closed-API leaders on most benchmarks.
- •McKinsey State of AI 2024: 72% of organizations report using AI in at least one business function (up from 55% in 2023).
AI Software Supply Chain: Who Does What
Solid bars = active in this stage. Faded = notable relationship but not primary business. Compute-layer companies cross-link to the AI Chips sector for canonical coverage.
Structural Chokepoints
NVIDIA holds approximately 80% or more of AI accelerator share through 2025. AMD MI300 and MI350 plus hyperscaler custom silicon (Google TPU, AWS Trainium, Microsoft Maia, Meta MTIA) chip away at the edges, but training every frontier model in 2024 and 2025 has been dominated by NVIDIA H100/B200.
Every meaningful AI accelerator at 3nm and 2nm is manufactured by TSMC. Samsung Foundry and Intel Foundry have not closed the gap for the volumes that matter.
HBM3E and HBM4 supply is concentrated in SK Hynix and Samsung, with Micron ramping. Multi-quarter HBM allocation visibility has been a binding constraint on accelerator output through 2024 and 2025.
US export controls (BIS) on advanced compute
Successive BIS rules restrict H100, H200, B200, and equivalents to China; the AI Diffusion Framework (paused in 2025) would have tiered global cloud access. Affects Chinese frontier-lab training trajectories and reshapes global GPU flow.
Power and data center capacity
Northern Virginia, Phoenix, and Texas have become the primary AI data center clusters; grid interconnect queues stretch 4 to 7 years. Nuclear PPAs (Constellation-Microsoft, Vistra-AWS) and behind-the-meter gas (Crusoe, Stargate) are emerging as constraint releases.
Licensed training data
NYT v. OpenAI, Authors Guild, Getty, RIAA v. Suno and Udio plus licensing deals (Reddit, NewsCorp, AP) are still unresolved. Outcomes could materially raise training-data unit costs for closed-API labs.
Global AI Market Size by Analyst
McKinsey GenAI Economic Potential (not vendor revenue)
$2.6T to $4.4T per year
McKinsey's June 2023 report The Economic Potential of Generative AI: The Next Productivity Frontier estimated $2.6T to $4.4T in annual economic value across 63 use cases at full adoption. The 2024 follow-up edged the bottom of the range up. This is an addressable economic value (savings plus revenue uplift across all enterprises), NOT a vendor revenue figure. Shown here for cross-reference only; do not directly compare to the IDC, Gartner, or Bloomberg vendor-revenue figures.
Annual global AI software market size, USD billions, 2020 to 2030E. Spread reflects scope differences (IDC includes services, Gartner is software-only, BI captures GenAI broadly), not analyst disagreement on direction. Click legend pills to toggle series. Hover the points for per-row notes.
Big Tech AI Revenue Contribution (management-disclosed only)
Microsoft Azure AI Growth Contribution (disclosed)
Percentage points contributed to Azure-and-other-cloud-services growth, per Satya Nadella on each quarterly earnings call.
Other Hyperscalers: Not Disclosed by Management
Amazon (Bedrock + Q)
Bedrock and generative AI run-rate. AMZN Q4-2025 earnings call, early Feb 2026 (Andy Jassy). Continued multi-billion-dollar framing.
Alphabet (Vertex + Gemini)
Google Cloud AI mention. Alphabet Q4-2025 earnings call.
Oracle (OCI GenAI)
OCI GenAI bookings. ORCL FY2026-Q3 earnings call (typically reported mid-March).
Meta
AI not broken out. META Q4-2025 earnings call.
Apple Intelligence
Apple Intelligence not disclosed. Apple does not disclose AI revenue.
Milestone Disclosures
- 2025-01-29Microsoft. AI business at $13B annual run-rate, up 175% year over year. (MSFT FY2025-Q2 earnings call (Satya Nadella))
- 2024-10-30Microsoft. Azure AI services contributed approximately 12 points to Azure-and-other-cloud-services growth. (MSFT FY2025-Q1 earnings call)
- 2024-08-01Amazon. Generative AI cited as multi-billion-dollar revenue run-rate growing triple-digit percent year over year. (AMZN Q2-2024 earnings call (Andy Jassy))
- 2025-04-24Alphabet. Google Cloud grew 28% year over year; Vertex AI and Gemini API cited as drivers; AI Overviews scaling globally. (Alphabet Q1-2025 earnings call (Sundar Pichai))
Only management-disclosed numbers are included. Microsoft cites Azure AI as a points contribution to Azure-and-other-cloud-services growth. Amazon, Alphabet, Oracle, Meta, and Apple have not published a quarterly AI dollar figure; their rows show the latest earnings-call characterization, not zero. No third-party estimates are used in this table.
Top 20 by AI-Attributable Revenue
| # | Company | Category | 2024 AI Revenue | 2025E AI Revenue |
|---|---|---|---|---|
| 1 | NVIDIA Cross-reference to AI Chips sector. Included in this table for relative-scale context only. | Compute | $97B | $150B |
| 2 | Microsoft (Azure AI plus Copilot) | Big Tech AI | $13B | $27B |
| 3 | OpenAI | Frontier Lab | $4.0B | $13B |
| 4 | Anthropic | Frontier Lab | $800M | $5.0B |
| 5 | Google Cloud AI (Vertex plus Gemini API plus Workspace AI) | Big Tech AI | n/d | n/d |
| 6 | AWS Bedrock plus Amazon Q plus generative AI services | Big Tech AI | n/d | n/d |
| 7 | Adobe (Firefly plus AI Assistant) | Enterprise Horizontal | $400M | $700M |
| 8 | Palantir (AIP plus US Commercial) | Enterprise Horizontal | $400M | $800M |
| 9 | Salesforce (Agentforce plus Einstein) | Enterprise Horizontal | $300M | $900M |
| 10 | IBM watsonx | Big Tech AI | $300M | $600M |
| 11 | Midjourney | Consumer App | $300M | $500M |
| 12 | GitHub Copilot | Coding | $250M | $500M |
| 13 | ServiceNow (Now Assist) | Enterprise Horizontal | $200M | $500M |
| 14 | Databricks | Data Platform | n/d | n/d |
| 15 | ElevenLabs | Consumer App | $100M | $200M |
| 16 | Perplexity | Consumer App | $50M | $150M |
| 17 | Cursor (Anysphere) | Coding | $50M | $200M |
| 18 | Glean | Enterprise Horizontal | $60M | $200M |
| 19 | Mistral | Frontier Lab | n/d | n/d |
| 20 | Harvey | Vertical AI | $30M | $80M |
Top 20 entities by AI-attributable revenue, calendar 2024 actuals and 2025E. Hover the figures for per-row sourcing notes. n/d = not disclosed (Alphabet, Amazon, Meta, Apple, Databricks, Mistral). NVIDIA is included for relative-scale context; canonical coverage lives in the AI Chips sector.
AI Software Regulatory Snapshot
China Deep Synthesis Provisions
CAC Deep Synthesis Provisions require labelling of synthetic media, algorithm registration, and real-name registration of users. Together with the 2022 Algorithm Recommendation Provisions, sets the architecture for China's AI model registration regime that pre-dates the EU AI Act.
CAC Generative AI Measures take effect
Cyberspace Administration of China (CAC) issues Interim Measures for the Management of Generative AI Services. Public-facing GenAI services must complete CAC algorithm registration, security assessment, and content moderation aligned with socialist core values. Foundational to subsequent CAC enforcement against domestic LLM providers.
EU AI Act enters into force
The EU AI Act enters into force after publication in the Official Journal on 12 July 2024. The Act introduces a risk-tiered framework (prohibited, high-risk, limited-risk, minimal-risk) and a separate regime for general-purpose AI (GPAI) models. Most obligations phase in over 6 to 36 months.
EU AI Act prohibitions take effect
Article 5 prohibitions become applicable: social scoring, manipulative AI, exploitation of vulnerabilities, untargeted facial-recognition scraping, certain real-time remote biometric identification in public, emotion recognition at work or school, and predictive policing based solely on profiling.
EU AI Act GPAI obligations apply
General-purpose AI model obligations apply: technical documentation, training-data summaries, copyright policy, and systemic-risk obligations for the largest models (FLOPs threshold of 10 to the 25th). The Commission's AI Office and the GPAI Code of Practice are the primary instruments.
EU AI Office becomes operational
The EU AI Office (inside DG Connect) coordinates enforcement of the AI Act's GPAI provisions, the GPAI Code of Practice, and the AI Pact voluntary regime. Performs model evaluations and oversees the systemic-risk GPAI category.
EU AI Act high-risk obligations apply
Most high-risk AI system obligations become enforceable: conformity assessments, risk management systems, data governance, human oversight, post-market monitoring, and registration in the EU database. Covers credit scoring, hiring, education, critical infrastructure, law enforcement, and biometrics.
EU AI Act embedded high-risk obligations apply
Final phase: high-risk obligations extend to AI systems embedded as safety components in products already regulated under EU product-safety law (medical devices, machinery, toys, vehicles). Completes the multi-year AI Act compliance ramp.
UK AI Safety Institute established
Established at the Bletchley Park AI Safety Summit, the UK AI Safety Institute (AISI) became the first government-backed body to evaluate frontier model capabilities and safety. AISI has signed pre-deployment evaluation agreements with OpenAI, Anthropic, Google DeepMind, Microsoft, and Meta. Renamed AI Security Institute in early 2025.
Authors Guild v. OpenAI filed
The Authors Guild and 17 named authors (including George R.R. Martin, John Grisham, Jodi Picoult) file a class action against OpenAI in S.D.N.Y. for use of copyrighted books in training data. Consolidated with related class actions in 2024.
NYT v. OpenAI and Microsoft filed
The New York Times sues OpenAI and Microsoft in S.D.N.Y., alleging mass copyright infringement in training data and output regurgitation. Most-watched AI copyright case; OpenAI's motion to dismiss was largely denied in 2024, with discovery proceeding into 2025 and 2026.
US AI Safety Institute established
NIST established the US AI Safety Institute (US AISI) inside NIST, with voluntary pre-deployment testing agreements signed with OpenAI and Anthropic in August 2024. Mandate under review following the rescission of EO 14110 and the 2025 AI Action Plan.
RIAA v. Suno and Udio filed
The Recording Industry Association of America (Sony Music, UMG, Warner) sues Suno (D. Mass.) and Udio (S.D.N.Y.) alleging mass training-data infringement of sound recordings. First major music-industry test of generative AI training-data liability.
BIS AI Diffusion Framework published
The Bureau of Industry and Security (BIS) publishes the Interim Final Rule on AI Diffusion: tiered global access to advanced AI compute and model weights via a country-cap and Validated End User regime. Builds on October 2022 and October 2023 export-control rules targeting H100, H200, B200 sales to China. Subsequently paused for further review under the Trump administration.
Trump signs EO 14179, rescinds Biden AI EO 14110
Executive Order 14179 (Removing Barriers to American Leadership in Artificial Intelligence) rescinds Biden's EO 14110 (Oct 2023) and directs OSTP and OMB to draft a new AI Action Plan within 180 days. Centerpiece: deregulatory posture, reduced reporting requirements, focus on US competitive position versus China.
White House releases AI Action Plan
The OSTP and OMB release the AI Action Plan called for by EO 14179. Plan emphasizes federal-procurement preference for American AI, accelerated permitting for data centers, reform of NIST AI Safety Institute mandate, and limited federal preemption of state AI laws (notably Colorado AI Act).
Colorado AI Act takes effect
Colorado SB 24-205 becomes the first US comprehensive AI consumer-protection law to take effect. Imposes duty of reasonable care on developers and deployers of high-risk AI systems (used in consequential decisions: hiring, lending, housing, education, healthcare, insurance, legal services). Requires impact assessments and consumer notice and appeal rights.
Getty Images v. Stability AI
Getty Images files parallel suits in the High Court of Justice (UK) and the District of Delaware against Stability AI over Stable Diffusion training data. UK trial proceeded in mid-2025; US Delaware case advanced into discovery. Landmark test of image-training copyright liability.
Major AI software regulatory milestones, enforcement programs, and unresolved copyright suits. Click any card for the originating source. Sorted by jurisdiction then date.