AI Adoption (Consumer + Enterprise)
800 million#1 weekly active users of ChatGPT, announced by Sam Altman at OpenAI DevDay on 6 October 2025, up from 300 million in December 2024.
39%#2 of US adults aged 18-64 reported using generative AI in their work or personal life in 2024.
28%#3 of US workers reported using generative AI on the job in the same NBER survey.
Source: NBER w32966, Bick et al. 2024
78%#4 of organizations reported using AI in at least one business function in 2024, up from 55% the prior year.
71%#5 of organizations reported using generative AI specifically in at least one function in 2024.
Source: McKinsey State of AI 2024
65%#6 of organizations were using generative AI regularly in 2024, nearly double the 33% reported in 2023.
Source: McKinsey State of AI 2024
Marketing & sales#7 remained the most common business function for generative AI deployment, with 34% of organizations using it there.
Source: McKinsey State of AI 2024
76%#8 of professional developers were using or planning to use AI tools in their development process in 2024, up from 70% in 2023.
62%#9 of developers said they were currently using AI in their development process, with another 14% planning to soon.
81%#10 of developers cited "increased productivity" as the top benefit of AI tools in their workflow.
25%+#11 of all new code at Google was generated by AI, then reviewed and accepted by engineers, per Sundar Pichai in October 2024 ("more than a quarter").
25%#12 of US K-12 teachers used AI tools for instructional planning or teaching in the 2023-24 school year.
API & Token Economics
$2.50#13 per million input tokens for OpenAI's GPT-4o list price as of late 2024, with $10.00 per million output tokens.
Source: OpenAI API pricing page
$0.15#14 per million input tokens for OpenAI's GPT-4o mini, roughly 1/17 the cost of GPT-4o input tokens.
Source: OpenAI API pricing page
$3.00#15 per million input tokens for Anthropic's Claude 3.5 Sonnet list price, with $15.00 per million output tokens.
Source: Anthropic API pricing page
200,000#16 token context window for Claude 3.5 Sonnet on the standard API tier.
Source: Anthropic model documentation
128,000#17 token context window standard for OpenAI's GPT-4o family.
Source: OpenAI models documentation
2 million#18 token context window on Google's Gemini 1.5 Pro, the largest among major frontier APIs in 2024.
~280x#19 drop in inference cost for GPT-3.5-level performance, from $20 to $0.07 per million tokens between November 2022 and October 2024.
Source: Stanford HAI AI Index 2025
9x to 900x#20 per year decline in LLM inference prices at constant performance, depending on the task, per Epoch AI.
50%#21 discount on OpenAI's Batch API versus standard pricing, for jobs that can wait up to 24 hours.
Source: OpenAI Batch API documentation
90%#22 discount on Anthropic prompt-cache reads versus base input price; writing to the cache costs 25% more than base input.
$3.7 billion#23 in 2024 revenue reported for OpenAI, the bulk from API and ChatGPT subscriptions.
$1 billion#24 annualized revenue run-rate disclosed by Anthropic in late 2024.
~73%#25 share of Anthropic 2024 revenue from API customers rather than direct chat subscriptions, per The Information.
$20#26 per month standard ChatGPT Plus consumer subscription price unchanged since 2023.
Source: OpenAI ChatGPT pricing page
$200#27 per month price of ChatGPT Pro when it launched in December 2024 with unlimited o1 access; Pro is now listed from $100 per month.
Frontier Model Release Cadence
51#28 notable machine-learning models released by industry in 2023 alone, per Epoch AI's tracking cited in the AI Index.
Source: Stanford HAI AI Index 2024
~3 months#29 typical interval between major frontier-model releases by the top three labs (OpenAI, Anthropic, Google DeepMind) during 2024.
o1-preview#31 launched September 12, 2024, was OpenAI's first publicly released reasoning-trained model.
Source: OpenAI o1 launch announcement
3#32 distinct Claude 3 family tiers released by Anthropic on March 4, 2024 (Haiku, Sonnet, Opus).
June 20, 2024#33 release date of Claude 3.5 Sonnet, which Anthropic positioned as outperforming Claude 3 Opus at a fraction of the price.
Gemini 1.5#34 Pro launched February 15, 2024, introducing the 1M-token context window publicly previewed by Google DeepMind.
Llama 3#35 released April 18, 2024 in 8B and 70B sizes, with the 405B Llama 3.1 released July 23, 2024.
Source: Meta AI Llama 3 announcement and Llama 3.1 announcement
15.4 trillion#36 tokens used to pretrain Llama 3, more than seven times the volume used for Llama 2.
Source: Meta AI Llama 3 model card
DeepSeek V3#37 released open-weight on December 26, 2024, claimed pretraining cost of approximately $5.6M for a 671B-parameter MoE model.
18 months#38 elapsed between OpenAI's GPT-4 release (March 2023) and the o1-preview release (September 2024), which marked the start of the reasoning-model paradigm.
Open-Source vs Closed-Source Share
1 million#39 public models on Hugging Face, a milestone crossed in late September 2024.
650 million#40 cumulative downloads of Llama models reported by Meta in December 2024.
~1.5 years#41 typical lag between a closed-source frontier capability and the first open-weight model matching it on standard benchmarks per State of AI 2024.
Source: State of AI Report 2024
Llama 3.1 405B#42 was presented by Meta as the first openly available model comparable to leading closed models on benchmarks including MMLU, GSM8K and HumanEval.
$0.27#43 per million input tokens for DeepSeek V3 hosted inference, the lowest publicly listed price for a 600B+ parameter open model in early 2025.
Mixed licences#44 govern open-weight models: Qwen2.5 is Apache 2.0 for most sizes (3B and 72B use the Qwen License), DeepSeek-V3 code is MIT with a separate model licence, Mistral mixes Apache 2.0 and research or commercial licences, and Llama uses Meta's Community License.
Enterprise AI Deployment Patterns
51%#45 of enterprise generative-AI deployments used retrieval-augmented generation (RAG) in 2024, up from 31% in 2023.
44%#46 of organizations reported a measurable cost reduction from generative AI in at least one business function.
Source: McKinsey State of AI 2024
63%#47 of organizations reported a revenue increase from generative AI deployment in at least one function.
Source: McKinsey State of AI 2024
Inaccuracy#48 was the most commonly cited risk of generative AI in McKinsey's 2024 survey.
Source: McKinsey State of AI 2024
Cybersecurity#49 and intellectual-property infringement were among the next most-cited generative-AI risks.
Source: McKinsey State of AI 2024
AI Tool Spend by Category
$235 billion#50 total worldwide AI software, hardware, and services spending in 2024 per IDC's Worldwide AI and Generative AI Spending Guide.
$632 billion#51 projected worldwide AI spending by 2028 per the same IDC guide, implying a 29% CAGR from 2024.
Source: IDC Worldwide AI Spending Guide
$13.8 billion#52 enterprise generative-AI software spending in 2024, six times the 2023 figure of $2.3 billion per Menlo Ventures.
$25.2 billion#53 private investment into generative AI startups globally in 2023, an 8x increase from 2022.
Source: Stanford HAI AI Index 2024
$33.9 billion#54 private investment in generative AI in 2024 per Stanford AI Index 2025.
Source: Stanford HAI AI Index 2025
$67.2 billion#55 US private AI investment in 2023, far ahead of China at $7.8 billion and the UK at $3.8 billion.
Source: Stanford HAI AI Index 2024
77,000+#56 organizations had adopted GitHub Copilot by mid-2024, up 180% year over year.
$10/month#57 standard GitHub Copilot Individual subscription price, unchanged since 2022.
Source: GitHub Copilot plans page
AI Labor Displacement & Productivity
14%#58 average productivity increase for customer-support agents given a generative-AI assistant, in a study of 5,179 agents.
34%#59 productivity improvement for novice and low-skilled support agents, with minimal impact on experienced agents, in the same study.
55.8%#60 faster task completion for developers given GitHub Copilot in a controlled study by GitHub Research.
40%#61 reduction in time taken on a writing task, with output quality up 18%, among professionals given ChatGPT in a randomized experiment.
Source: Noy & Zhang, Science (2023)
12.2%#62 performance improvement for management consultants on a creative-product task when given GPT-4, in a Harvard-BCG controlled study, with quality also rising 40%.
~80%#63 of the US workforce could have at least 10% of their work tasks affected by large language models.
19%#64 of US workers held jobs in which at least 50% of work tasks are highly exposed to LLM automation per the same study.
Compute & Training Costs
~$78 million#65 estimated compute cost to train GPT-4 per Stanford AI Index 2024 cost estimates.
Source: Stanford HAI AI Index 2024
~$191 million#66 estimated compute cost to train Google Gemini Ultra, the most expensive model training disclosed by the AI Index 2024.
Source: Stanford HAI AI Index 2024
~6 months#67 doubling time of training compute for notable models in the deep-learning era, a roughly ten-billion-fold increase since 2010, per Epoch AI.
15.4 trillion#68 training tokens used for Llama 3, processed on two custom-built 24,000-GPU H100 clusters operated by Meta.
Source: Meta AI Llama 3 announcement
~$5.6 million#69 compute cost claimed by DeepSeek for the V3 pretraining run, two orders of magnitude below Western frontier-lab estimates.
$30,000+#70 typical end-customer price of a single Nvidia H100 SXM GPU during the 2023-2024 supply crunch reported by The Information.