Beyond the Hype: 5 Things We Just Learned About How Enterprises Really Use AI

By Melverick Ng | Published 02 Jun 2025 | Updated 25 May 2026 | 8 min read

Introduction

The conversation around artificial intelligence in the business world is constant, a mix of bold predictions, speculative hype, and genuine anxiety. It's often difficult to distinguish the signal from the noise. How are companies actually using these powerful new tools? Is AI transforming work as we know it, or is it just another productivity hack?

A new "State of Enterprise AI" report from OpenAI provides a rare, data-driven look behind the curtain. Based on aggregated and de-identified data from over 1 million business customers, the report cuts through the speculation to offer a grounded view of AI deployment inside organizations today. It reveals a landscape that is more complex and nuanced than the public narrative suggests.

This post will distill the report's extensive findings into the five most surprising and impactful takeaways. From the emergence of a new class of coder to a deep, widening gap between leading firms and laggards, these insights show how AI is truly reshaping the modern enterprise right now.

The Five Key Takeaways

1.AI Isn't Just Making Us Faster—It's Creating a New Class of Coder

One of the most significant impacts of AI is not just task acceleration but genuine skill expansion. The more profound shift is in what employees are now capable of doing. The report found that 75% of surveyed workers are able to complete tasks they previously could not perform, such as programming support, spreadsheet analysis, and technical tool development.

This trend is democratizing technical skills across organizations. The report highlights a surprising increase in non-technical roles engaging in technical work. Over the past six months, coding-related messages have grown by an average of 36% outside of traditional engineering, IT, and research functions.

This "equalizing effect" suggests AI's true power lies in broadening individual capabilities. This democratizing effect is consistent with several external studies, which find that AI disproportionately aids lower-performing workers, leveling the playing field across the organization. It's creating a new class of semi-technical worker — precisely the kind of professional that an AI workshop for business professionals is designed to upskill — empowering employees in every department to solve problems that were once the exclusive domain of specialists.

2.A Deep "AI Divide" Is Separating the Leaders from the Laggards

On average, enterprise users report saving 40-60 minutes per day with AI—a significant productivity gain. But while access to these tools is becoming widespread, a major performance gap is emerging between casual users and highly engaged "frontier" users. The data reveals a stark divide in the intensity of AI adoption, both at the individual and organizational levels.

The key data points illustrating this divide are striking:

• At the individual level: "Frontier workers," representing the top 5% of users, send 6 times more messages than the median worker. For a specialized task like coding, that gap widens to 17 times as many messages.
• At the firm level: "Frontier firms" generate approximately 2 times more messages per seat and 7 times more messages to Custom GPTs than the median enterprise, indicating a much deeper integration of AI into standardized workflows.

This gap has a direct impact on results. Users who leverage AI across a wider variety of tasks—from coding and data analysis to writing and creative generation—report saving five times more time than those who use it for only a few. This confirms a critical insight: simply having access to AI is not the same as extracting meaningful value from it.

3.Even Active Users Are Barely Scratching the Surface

Perhaps one of the most surprising findings is the significant underutilization of advanced AI features, even among people who use the tools regularly. A large portion of monthly active ChatGPT Enterprise users have never touched some of its most powerful capabilities.

Consider these statistics for monthly active users:

• 19% have never used data analysis.
• 14% have never used reasoning.
• 12% have never used search.

This reveals a massive amount of untapped potential. The primary bottleneck for enterprise AI is no longer the performance of the models themselves. Instead, the report suggests the main constraint has shifted to "organizational readiness"—the ability of a company to train its workforce and adapt its processes. This is exactly why structured AI training Singapore companies need — including SkillsFuture AI courses — has become essential for closing the readiness gap.

So how are leading firms closing this readiness gap? The report highlights several consistent practices:

• Deep system integration: They connect AI to core tools and company data, enabling context-aware responses and automated actions.
• Workflow standardization: They actively promote the creation and sharing of repeatable AI solutions, like Custom GPTs, for common tasks.
• Executive leadership: They set clear mandates, secure resources, and create space for experimentation to enable deployment at scale.
• Deliberate change management: They build structures that speed up organizational learning, combining centralized training with distributed enablement through local AI champions.

4.The Fastest AI Growth Isn't Where You Think

It's easy to assume that the AI revolution is being led and dominated by the technology sector. While sectors like professional services and finance continue to lead in absolute scale of AI usage, the report reveals that other industries are catching up at a remarkable pace.

The fastest-growing sectors by year-over-year customer growth are:

• Technology: 11x
• Healthcare: 8x
• Manufacturing: 7x

Furthermore, this growth is a global phenomenon. Enterprise adoption is accelerating worldwide, with countries like Australia, Brazil, the Netherlands, and France showing faster customer growth than the global average. AI is not a Silicon Valley-centric trend; it is rapidly becoming a foundational, cross-industry tool for businesses across the globe.

5.AI Is Quietly Becoming Core Infrastructure, Not Just a Tool

The most mature organizations are moving beyond using AI for simple, one-off queries. They are integrating it deeply into standardized, repeatable workflows, transforming it from a peripheral productivity tool into a piece of core organizational infrastructure.

The evidence for this shift is compelling. The report notes a 19x year-to-date increase in the weekly users of Custom GPTs and Projects—configurable interfaces that allow teams to automate multi-step tasks. These custom applications have become so integral that they now process approximately 20% of all Enterprise messages.

To illustrate how deeply embedded these workflows can become, the report cites the example of the financial institution BBVA, which regularly uses more than 4,000 GPTs in its daily operations. This trend of building repeatable, custom AI solutions marks a critical evolution in how companies view and use the technology.

Conclusion: The Real Work Begins Now

The OpenAI report makes one thing exceptionally clear: the business impact of AI is determined not by access, but by the depth and intensity of its use. As the technology matures, the dividing line between success and failure will be an organization's ability to move beyond experimentation and embed AI into its core operations.

The stakes are high, as the report's conclusion emphasizes:

The initial wave of AI adoption is over, and the data reveals a clear gap between the early leaders and the rest of the pack. The real work of AI skills training for SMEs — including hands-on agentic AI courses and no-code AI automation training — is just beginning. The data shows a clear divide between casual users and frontier organizations. Which side of that gap will you and your company be on?