AI Has Crossed a Line: The Question Is Whether You Are Doing It on Purpose

AI is no longer something companies are testing on the side. It is showing up in real work every day. People use it to write, analyze, code, plan, and organize their thoughts. The shift is not just that the tools are better. It is that usage is becoming routine and embedded in normal workflows.

That is the core takeaway SPR’s CTO Matthew Mead shares in his video after digging into two recent reports, one from Microsoft’s AI Economy Institute and another from OpenAI.

Microsoft’s AI Diffusion research estimates that global generative AI usage reached roughly one in six people worldwide in the second half of 2025, with adoption at 16.3%. That is not a “pilot” signal. That is a behavioral shift at scale.

OpenAI’s enterprise report shows the same story from inside organizations. It reports that ChatGPT message volume grew 8x and API reasoning token consumption per organization increased 320x year over year, pointing to deeper, more frequent use, not just occasional experimentation.

The big implication is this: AI is moving from a novelty tool to a core layer of how work gets done. Once that happens, the conversation changes. The question is no longer whether AI can be useful. The question becomes whether organizations are shaping their use intentionally.

Another thing to note is that not everyone is benefiting equally. Microsoft’s report notes that adoption is rising, but unevenly. In late 2025, 24.7% of the working-age population in the Global North used generative AI tools, compared to 14.1% in the Global South, and adoption in the Global North grew nearly twice as fast.

OpenAI reports a similar gap inside enterprises. “Frontier workers” are sending 6x more messages, and “frontier firms” are sending 2x as many messages per seat as the median enterprise.

In plain terms, some teams are building real momentum and compounding gains. Others are stuck debating policies, limiting access, or keeping AI usage in isolated pilots. Over time, that becomes a competitive difference you can feel in speed, decision quality, and talent attraction.

The real question for leaders is not “Should we use AI?” That debate is already over. AI is showing up in work whether leaders plan for it or not. The more useful question is: Are you intentionally building AI into how your people work, or are you leaving it to chance?

Leaving it to chance usually looks like scattered individual experimentation, inconsistent outputs, and uncertainty about what is safe or allowed. Being intentional looks like supporting repeatable workflows, practical training, and clear guardrails that help teams use AI confidently.

That is also where the biggest payoffs start to show up. OpenAI reports that enterprise users attribute 40 to 60 minutes saved per active day to AI use, and that 75% of surveyed workers report improved speed or quality. Those gains are rarely captured through ad hoc prompting alone. They tend to come from turning AI into a consistent way of working.

The next phase of adoption is less about “using AI” and more about making AI a reliable part of workflow design.

OpenAI points to organizations moving beyond one-off outputs toward repeatable patterns, including the use of Custom GPTs and Projects to codify instructions, institutional knowledge, and multi-step tasks. Their report notes weekly users of Custom GPTs and Projects increased about 19x year-to-date, and that around 20% of Enterprise messages were processed through a Custom GPT or Project.

You do not need to adopt those exact mechanisms to take the lesson. The point is that organizations that get value tend to do a few things consistently:

• They give people access and clear guidance.
• They train teams on practical use, not just tool features.
• They identify a few real workflows where speed or decision quality matters, and then make usage repeatable.
• They keep accountability human and track outcomes.

Watch Matt’s video: It’s a quick, leader-friendly synthesis of what these reports signal and why the “AI gap” is becoming a real business issue now, not later.

If you want to go deeper, the two reports he references are worth skimming:

• Microsoft AI Economy Institute, Global AI Adoption in 2025: A Widening Digital Divide
• OpenAI, The State of Enterprise AI | 2025 Report