Many organizations say they have an AI strategy. In practice, what they often have is an AI access policy. Tools are available, licenses are purchased, and usage is technically allowed. But value creation remains uneven.
Recent data from OpenAI’s State of Enterprise AI report reinforces what many executives are starting to notice internally. A small group of employees are capturing most of the benefits. These frontier workers use AI across more tasks, more deeply embedded in workflows, and with far greater impact. The gap between them and the rest of the organization is growing fast.
This is not a tooling problem. It is a leadership and operating model problem.
TL;DR
- Most companies confuse AI strategy with AI access.
- A small group of frontier workers drive the majority of AI value.
- The real challenge is scaling frontier behavior, not deploying more tools.
- Leaders should focus on closing the gap between advanced users and everyone else.
Why AI Strategy Is Not the Same as AI Adoption
An AI strategy should define how intelligence changes work, decisions, and outcomes. What many organizations implement instead is access.
Access means employees can use ChatGPT or internal AI tools if they want. Strategy means the organization deliberately redesigns workflows so AI is integral to how work gets done.
The difference shows up clearly in usage patterns. Frontier workers do not just ask AI questions. They delegate tasks, automate steps, analyze data, draft outputs, and iterate continuously. Others use AI like a better search engine.
Until leaders recognize this gap, AI investments will continue to underperform expectations.
Who Are Frontier Workers
Frontier workers are not defined by title or seniority. They are defined by behavior.
They use AI across writing, analysis, coding, planning, and decision support.
They experiment with advanced features, not just basic prompts.
They embed AI into daily workflows rather than treating it as a side tool.
According to OpenAI’s enterprise research, frontier workers generate many times more AI interactions than median users and save significantly more time per week. More importantly, they unlock work that was previously impossible or impractical at scale.
This creates a compounding advantage at both the individual and firm level.
The Organizational Cost of the Frontier Gap
When only a small group operates at the frontier, three problems emerge.
First, productivity gains stay isolated. The organization never captures system-level impact.
Second, innovation becomes fragile. If frontier workers leave, the workflows often leave with them.
Third, leadership underestimates AI’s potential because most employees are not seeing meaningful benefits.
This is why many executives feel disappointed by AI results despite strong early pilots.
Moving From AI Access to AI Strategy
Shifting from access to strategy requires leaders to ask different questions.
Not “how many people are using AI”
But “who is using it deeply and why”
Not “what tools should we roll out”
But “which workflows should change”
Not “how do we encourage experimentation”
But “how do we standardize what works”
The goal is not universal experimentation. The goal is deliberate diffusion of frontier practices.
How Leaders Can Scale Frontier Behavior
There are several practical steps leaders can take today.
Identify frontier workers explicitly. Treat them as a strategic asset, not just power users.
Study their workflows. What tasks are they delegating to AI? Where are they saving time? What decisions are they improving?
Codify successful patterns. Turn individual workflows into shared playbooks, templates, or internal tools.
Redesign roles and expectations. Make AI usage part of how work is done, not optional enrichment.
Invest in enablement, not just licenses. Training should focus on workflow redesign, not prompt tricks.
McKinsey has highlighted that companies capturing the most AI value focus heavily on operating model change, not just technology deployment. This reinforces the idea that strategy lives between people, processes, and systems.
Why This Gap Will Get Bigger Before It Gets Smaller
AI tools are improving faster than organizations are adapting. Frontier users naturally absorb new capabilities first. Without intentional leadership intervention, the gap widens.
This mirrors previous technology shifts. Spreadsheets, ERP systems, and analytics all followed similar patterns. Early power users defined advantage. The rest caught up only after processes were redesigned.
AI is moving faster, which means the window for catching up is shorter.
Rethinking What an AI Strategy Really Is
A real AI strategy answers a simple question. How does intelligence flow through the organization?
It defines who builds, who uses, who reviews, and who decides.
It clarifies which tasks should be automated, augmented, or reimagined.
It treats AI as infrastructure, not software.
Most importantly, it recognizes that value comes from people who know how to operationalize intelligence, not just access it.
Conclusion
The biggest risk in enterprise AI today is not falling behind on tools. It is failing to scale frontier behavior.
A small group of employees is already showing what is possible. The strategic challenge for leaders is to move everyone else closer to that frontier.
AI access gets you started.
AI strategy determines whether you win.
The organizations that recognize this difference early will define the next phase of enterprise productivity and competitive advantage.
Related content you might also like:
- Is AI at Work Stalled?
- Generative AI Labor Market: Impacts on Jobs and Young Workers
- Show me the money might not hold for Gen Z
- Digital Safety Nets: When our Devices Know More about Us then we Know about Ourselves
- McDonald’s Q2 2025 Earnings: Lessons in Consumer Value
