AI Statistics 2026: Adoption, Usage & Workforce Trends

Four years after ChatGPT's first release, it's clear that AI is impacting our daily lives and reshaping the global economy.

In this post I'll give you a very high-level overview of what the AI landscape looks like and back it up with AI statistics sourced from the highest quality surveys, reports, and research papers.

I'll cover everything from AI market size and investment trends through to workforce impact and attitudes towards AI. For each subtopic I've named and linked to my source to make it easy for you to do further research.

AI market size

The global AI market continues its steep growth trajectory, on track to more than double in the next three years.

• As of 2026, the global AI market is valued at $514.5 billion.
• Consensus expectations are for that number to continue growing with a CAGR (compound annual growth rate) of 30.6%, which would see it cross the $1 trillion mark in 2029 and reach $3.49 trillion by 2033.

AI market size by sector

Which sector of the economy is most aggressive in its adoption of AI?

• Unsurprisingly, the technology and communication sector is currently in the lead since it accounts for 32% of the market for AI.
• This is followed by the automotive and assembly (29%), financial services (28%), energy and resources (27%), and media and entertainment (22%) sectors.

AI use by business function

How are businesses actually using AI?

• The most popular enterprise application of AI is customer service, which accounts for 56% of the AI market.
• This is followed by cybersecurity management (51%), chatbots (47%), CRM (46%), inventory management (40%), and content marketing (35%).

AI market size by geography

Where are the biggest markets for AI products?

• North America is the largest regional market for AI by quite a large margin — it accounts for 37% of the global AI market.
• After North America is Europe (26%), Asia Pacific (26%), and LAMEA (12%).

Source: Resourcera, AI Market Size Report: Global & U.S. Data, 2026–2032

AI investment and funding

Global investment in AI continued to accelerate in 2025 and throughout the first half of 2026, with most of the capital coming from the private investment markets (think venture capital, private equity, and strategic investments by big companies).

• Global investment in AI hit $582 billion in 2025.‍
• The private investment markets were the source for the majority (60%) of that and grew at a rate of 127.5% year over year.
• Drilling down into that private investment number, $286 billion of it was in the US, while Europe accounted for a relatively small $21 billion. US investment in AI is greater than both Europe and Asia combined.
• The pipeline of AI-focused startups continues to expand in 2025, with the number of newly funded AI companies rising 71% and the number of funding events with a value greater than $1 billion doubling.

Source: Stanford Institute for Human-Centered AI, The 2026 AI Index Report — the AI Index's investment figures are sourced from Quid, which tracks global private AI investment.

AI startups

A wide variety of AI-native startups have emerged in the last few years, ranging from frontier AI labs like OpenAI and Anthropic to application-layer startups like Cursor, Lovable, and Synthesia.

• Frontier labs are dominating AI startup revenues: Anthropic and OpenAI's share of revenues across a group of 34 leading AI startups reached 89% in 2026.
• Together, these 34 leading AI startups generate nearly $80 billion in annualized revenue, which equates to roughly $6.6 billion per month from selling AI products.

Source: The Information, Anthropic and OpenAI's Share of AI Startup Revenues Rises to 89% — based on revenue analysis of a group of 34 leading AI startups.

AI adoption

AI adoption by geography

• As of the second half of 2025, generative AI had been adopted by 16.3% of the world's population.
• This is an increase of 15.1% compared to the first half of 2025 and equates to roughly one in six people worldwide using generative AI.
• The gap in generative AI usage between the Global North and the Global South is widening. 24.7% of the working-age population in the Global North now use AI versus 14.1% in the Global South. That represents a 10.6 percentage point gap.
• Looking at the country level, the UAE is the world leader in generative AI adoption with 64.0% of its working-age population using AI. The UAE is closely followed by Singapore (60.9%), Norway (46.4%), Ireland (44.6%), France (44.0%), and Spain (41.8%).
• Perhaps surprising is that the US ranks 24th in this global ranking of AI use, with only 28.3% of its working-age population using it, despite being the source and destination of most AI infrastructure investment and the home of a large proportion of frontier model development.
• South Korea was the country with the fastest growth in AI use in the second half of 2025 (compared to the first half of the year). The country rose seven spots from 25th to 18th and 30.7% of its working-age population now use AI (compared to 25.9% in the first half of the year).

Source: Microsoft AI Economy Institute, Global AI Adoption in 2025 — which measures AI diffusion as the share of people who used a generative AI product during the period derived from aggregated, anonymized Microsoft telemetry.

AI adoption by company size

• AI adoption is much more widespread within bigger companies as measured by number of employees, with 37% of firms with 250+ employees reporting AI use.
• Mid-sized firms (100-249 employees) reported that 32% of their employees are using AI, and small firms with less than 100 employees said only 20% of their employees are using AI.
• Taken in the aggregate, overall usage of AI by US-based businesses sat between 17% and 20% of employees between December 2025 and May 2026, with 20–23% of businesses expected to use AI within the next six months.

Source: U.S. Census Bureau, Business Trends and Outlook Survey — AI data collected December 2025 to May 2026. The BTOS samples approximately 1.2 million US businesses in biweekly panels.

AI tool usage

Andreessen Horowitz's biannual ranking of the most-used consumer AI tools shows that ChatGPT is still far ahead, but that the challengers are growing fast.

ChatGPT leads, but the race for the "default AI" is on

• ChatGPT remains the most popular consumer AI product based on web traffic with 2.7x more usage than #2 Gemini, or 2.5x when based on mobile use.
• ChatGPT's WAUs (weekly active users) grew by 500 million to reach 900 million, which means that over 10% of the global population now use the tool at least once a week.
• The challengers are catching up. Google Gemini's number of US paid subscribers grew by 258% year over year, and the same number for Anthropic's Claude grew by over 200%.
• However, ChatGPT still remains 4x larger than Gemini and 8x larger than Claude based on this metric.
• It appears that users are increasingly using multiple AI assistants. Roughly 20% of ChatGPT's weekly web users are also using Gemini in a given week.

AI is now integral to mainstream consumer apps

• Generative AI is increasingly an integral part of the user experience of many mainstream consumer-focused applications.
• For example, CapCut is a video editing application with 736 million mobile MAUs (monthly active users) and its most popular features all rely on generative AI.
• Another example of this: Notion's paid AI attached rate rose from 20% to over 50% over one year. AI features are now accounting for approximately 50% of the company's annual recurring revenues (ARR).

Source: Andreessen Horowitz, Top 100 Gen AI Consumer Apps, March 2026 — a biannual ranking of consumer generative AI products based on unique monthly visits (for web applications) and monthly active users (for mobile applications).

Consumer attitudes and AI trust

The usage-trust gap

• 66% of people now use AI regularly, and 83% believe its use will result in a wide range of benefits.
• Yet only 46% of people globally are willing to trust AI systems.

Trust issues show up at work

• 66% of people rely on AI output without evaluating its accuracy.
• 56% say they've made mistakes in their work because of AI.

A public mandate for regulation

• 70% of people believe AI regulation is needed, at both national and international levels.

Source: KPMG & The University of Melbourne, Trust, Attitudes and Use of Artificial Intelligence: A Global Study 2025 — which surveyed more than 48,000 people across 47 countries on their trust, use, and attitudes toward AI.

AI ROI and business impact

Use-case ROI is real, but enterprise-level impact is rare

• Many organizations report use-case-level cost benefits, with the biggest cost benefits coming from using AI in software engineering, manufacturing, and IT.
• Within software engineering, 7% of respondents reported cost reductions of 20% or more, 14% reported cost reductions of 11–19%, and 35% reported cost reductions of at least 10%.
• AI-driven revenue increases are most commonly driven by use cases like marketing and sales, strategy and corporate finance, and product or service development.
• Within marketing and sales, 10% of respondents reported revenue increases of 10% or more, 14% reported revenue increases of 6–10%, and 43% reported revenue increases of at least 5%.
• However, organizations are still only using AI in an average of three business functions, which still represents a minority of activity at an enterprise level.
• McKinsey tested 25 attributes and found that the redesign of workflows has the biggest effect on an organization's ability to see an AI-driven EBIT impact.
• Only 21% of organizations surveyed said that they have fundamentally redesigned at least some workflows.
• 80% of organizations set efficiency as an objective of their AI initiatives, but the companies seeing the most value also set growth or innovation as objectives.
• As a result, AI has not yet significantly impacted earnings before interest and tax (EBIT) at the enterprise level. Just 39% report any AI-driven impact on their EBIT, and only 6% of organizations reported 5% or more of their organization's EBIT being attributable to AI use.

Source: McKinsey & Company, The State of AI: How Organizations Are Rewiring to Capture Value — based on the annual McKinsey Global Survey on AI with the latest edition surveying 1,993 participants across 105 countries (conducted June–July 2025).

AI workforce impact

It's looking like AI will reshape the global labor market, but this will largely be driven by job churn rather than job losses, as 22% of jobs are set to be disrupted by 2030.

AI is expected to be a net job creator

• AI will create 170 million new roles and displace 92 million roles by 2030. This sums to a net increase of 78 million jobs.
• 50% of employers are planning on refocusing their businesses around new AI-driven opportunities.

The skills gap is the biggest barrier

• 39% of existing skill sets will become outdated between now and 2030 due to AI-driven change.
• 59% of the global workforce will need to be either upskilled or reskilled by 2030. 11% of this workforce are deemed unlikely to receive this needed retraining, so that's over 120 million workers at risk of redundancy.
• These skills gaps are cited by 63% of employers surveyed as the single biggest barrier to business transformation.

Employers are responding with training, not just restructuring

• 77% of employers surveyed plan to upskill their workers in response to AI-driven change.
• While 41% of employers anticipate workforce reductions in situations where AI has automated tasks, nearly 50% expect to transition their staff from these AI-disrupted roles to other parts of their businesses.

Source: World Economic Forum, Future of Jobs Report 2025 — which brings together the perspectives of over 1,000 leading global employers, collectively representing more than 14 million workers across 22 industry clusters and 55 economies.

AI in employee training

AI has been rapidly adopted by learning and development teams (L&D), with over 87% of them already using it. Only 2% of L&D teams have no plans to adopt AI.

Where L&D teams are today

• Most L&D teams are past the testing and experimentation phase, with 36% of them using AI in defined workflows and 9% of them beginning to scale AI across their organization.
• The current top use cases of AI in L&D are voice generation (63%), content and quiz drafting (60%), video creation (52%), and translation (38%) — mostly in the design and development stages.
• The most widely-cited benefits of AI in L&D so far are faster content production (84%) and better learner experiences (66%).

Where it's heading

• L&D teams expect the biggest future gains from more personalized learning (72%), wider internal reach (65%), and improved learner engagement (56%).
• There's clear growth in planned adoption of AI-powered assessments and simulations (36%), adaptive pathways (33%), skills mapping (32%), and AI tutors (29%).
• L&D teams are seeing the value from AI shift from time saved (88%) towards clearer business impact (55%) and easier global localization (54%).
• There's a strong interest in agentic AI (AI that can autonomously take actions) within L&D teams. 27% are excited, 39% are cautious, and 29% say they need to learn more.
• This interest in agentic AI is focused on AI tutors (49%), coaching and mentoring (43%), personalized guidance (43%), and admin automation (38%).

The gap to close

• AI budgets in L&D remain low and fragmented with 39% of L&D teams spending 5% or less of their budgets on AI. 30% of L&D teams surveyed didn't even know what their AI spend was.
• The biggest obstacles to further adoption of AI in L&D are security concerns (58%), accuracy concerns (52%), legal constraints (41%), and integration challenges (36%).
• 74% of L&D teams said that their company culture encourages experimentation with AI, but only 45% of them felt that IT is actively enabling adoption.
• Optimism for AI is still very strong despite the friction caused by these blockers. 66% of L&D teams believe AI will strengthen their department's influence, and 72% of them think the L&D function will thrive by adapting to AI-driven changes in the discipline.
• There's a strong demand within L&D teams for practical support including AI skills and design training (67%), workflow guidance (63%), impact measurement (63%), and integration help (50%).

Source: Synthesia, AI in Learning and Development Report 2026 — based on a survey of 421 L&D professionals worldwide.