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.

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.