R E S E A R C H
The State of Enterprise AI
OpenAI's 2025 report examines how artificial intelligence is transforming enterprise operations across more than 1 million business customers worldwide. This comprehensive analysis reveals the current state of AI adoption, productivity impacts, and emerging patterns that are reshaping how organizations work.
Enterprise AI: From Consumer Tool to Core Infrastructure
For much of the past three years, AI's visible impact was most apparent among consumers. However, the history of general purpose technologies—from steam engines to semiconductors—shows that significant economic value is created after firms translate underlying capabilities into scaled use cases.
Enterprise AI now appears to be entering this phase, as many of the world's largest and most complex organizations are starting to use AI as core infrastructure. More than 1 million business customers now use OpenAI's tools, marking a fundamental shift in how organizations operate.
Four Key Findings
Enterprise Usage Scaling
ChatGPT message volume grew 8x and API reasoning token consumption per organization increased 320x year-over-year, demonstrating deeper workflow integration.
Measurable Impact
Enterprise users report saving 40–60 minutes per day and completing new technical tasks such as data analysis and coding.
Global Acceleration
International adoption has surged, with the median sector growing more than 6x and technology leading at 11x growth.
Widening Gap
Frontier workers send 6x more messages and frontier firms send 2x as many messages per seat than median enterprises.
Deepening Integration: Custom GPTs and Projects
19x
Growth in Custom GPT Users
Year-to-date increase in weekly users of Custom GPTs and Projects
20%
Enterprise Messages
Processed via Custom GPT or Project, indicating deep workflow integration
4K+
GPTs at Scale
BBVA regularly uses more than 4,000 GPTs across operations
Custom GPTs and Projects are configurable interfaces that enable workers to execute repeatable, multi-step tasks. The most widely deployed GPTs either codify institutional knowledge into reusable assistants or automate workflows through integrations with internal systems, indicating that AI-driven workflows are increasingly implemented as persistent tools embedded in daily operations.
Developer Workflows Rapidly Scaling
API Consumption Surge
Companies build on the API to integrate models directly into their products and systems with a high degree of control and customization. More than 9,000 organizations have now processed over 10 billion tokens, and nearly 200 have exceeded 1 trillion tokens.
Average reasoning token consumption per organization has increased by approximately 320x in the past 12 months, suggesting that more intelligent models are being systematically integrated into expanding products and services.
Codex Adoption
Codex is gaining rapid traction as teams adopt it for end-to-end software tasks: code generation, refactoring, testing, and debugging.
2x increase in weekly active users
50% increase in weekly messages
Workers Report Measurable Value
75%
Improved Output
Report better speed or quality of work
40-60
Minutes Saved
Time saved per active day using AI
75%
New Capabilities
Complete tasks they previously couldn't perform
Operational Improvements Across Functions
IT Workers
87% report faster IT issue resolution
Marketing & Product
85% report faster campaign execution
HR Professionals
75% report improved employee engagement
Engineers
73% report faster code delivery
Technical Work Expands Beyond Traditional Roles
AI is not only accelerating existing work; it is also expanding the tasks and skills workers can perform. Several studies find that AI has an equalizing effect, disproportionately aiding lower performing workers.
The broadening of individual capabilities is particularly apparent in technical settings, where non-technical teams are increasingly engaging in coding and data-analysis work that was previously confined to specialized roles.
75%
New Task Completion
Users report being able to complete tasks they previously could not perform
36%
Coding Growth
Average increase in coding-related messages outside engineering, IT, and research
Among ChatGPT Enterprise users, coding-related messages have increased across all functions. Workers consuming the most intelligence report higher time savings, using multiple models, engaging with more tools, and using AI across a wider range of tasks.
Industry Growth and Global Expansion
Rapid Growth Across Industries
OpenAI customer growth is broad-based across industries, with the median sector expanding more than 6x year-over-year. Technology, healthcare, and manufacturing show the fastest growth, while finance and professional services operate at the largest scale.
Technology: 11x growth
Healthcare: 8x growth
Manufacturing: 7x growth
International Acceleration
While early AI adoption was primarily U.S.-based, international growth is now accelerating rapidly. Australia, Brazil, the Netherlands, and France show the fastest growth in business customers, increasing more than 143% year-over-year. International API customer growth has exceeded 70% over the last 6 months, with Japan having the largest number of corporate API customers outside the U.S.
The Growing Divide in AI Adoption
Clear differences are emerging in how AI is used across industries and among individuals within firms. Frontier workers generate 6x more messages than the median worker, and frontier firms send 2x as many messages per seat than median enterprises.
Writing & Communication
11x gap between frontier and median workers
Coding
17x gap between frontier and median workers
Analysis & Calculations
10x gap between frontier and median workers
These differences matter. Usage data matched to survey results show that users who engage across roughly seven task types report five times more time saved than those who use only about four. The benefits users realize from AI scale directly with depth of use.

Significant Headroom for Growth: Even among active ChatGPT Enterprise users, 19% have never used data analysis, 14% have never used reasoning, and 12% have never used search. This represents substantial opportunity for organizations to increase AI maturity.
Real-World Business Impact: Case Studies
Leading organizations across industries are achieving measurable business outcomes through strategic AI deployment. A 2025 Boston Consulting Group study found that AI leaders achieved 1.7x revenue growth, 3.6x greater total shareholder return, and 1.6x EBIT margin over the past three years.
Intercom: Fin Voice
48% decrease in latency, 53% of calls resolved end-to-end, saving customers hundreds of millions of dollars annually through AI-powered voice support.
Lowe's: Mylow
Nearly 1 million questions answered monthly, conversion rate more than doubles when customers engage with Mylow, 200 basis point increase in satisfaction scores.
Indeed: Career Scout
Job seekers find and apply to relevant jobs 7x faster, 38% more likely to be hired, with 20% increase in started applications through AI-powered matching.
BBVA: Legal Automation
Automates 9,000+ queries annually, equivalent of 3 FTEs redeployed, delivering 26% of Legal Services division's annual savings KPI.
Oscar Health: Member Support
Answers 58% of benefits questions instantly, handles 39% of benefits messages without human escalation, improving healthcare navigation.
Moderna: Product Development
Reduced core analytical steps from weeks to hours, accelerating Target Product Profile development and helping deliver for patients more quickly.
The Path Forward: Organizational Readiness
What Leading Firms Do Consistently
Deep System Integration
Turn on connectors to give AI secure access to company data inside core tools, enabling context-aware responses and automated actions.
Workflow Standardization
Actively promote creation, sharing, and discovery of repeatable solutions for common tasks through GPTs and API-powered assistants.
Executive Leadership
Set clear mandates, secure resources, align teams, and create space for experimentation to enable deployment at scale.
Data Readiness
Codify institutional knowledge into machine-readable routines and run continuous evaluations to track model performance on real-world outcomes.
Change Management
Build structures that speed organizational learning, combining centralized governance with distributed enablement through AI champions.
The AI landscape is evolving rapidly, with OpenAI releasing a new feature or capability roughly every three days. The primary constraints for organizations are no longer model performance or tooling, but rather organizational readiness. Enterprise AI is still in the early innings, and firms have an opportunity to catch up by adopting the patterns of frontier workers and organizations.
Organizations that succeed in bringing AI capabilities into market-facing workflows will use AI not merely as a productivity tool, but as a durable engine of revenue growth and competitive advantage.