Companies have used "Machine Learning" for decades. But Wall Street didn't care until it could talk back.
The "Digital Divide" is back. But this time, it is hitting the boardroom.
According to the latest September 2025 Pew Research Center study, we are seeing a familiar pattern. There are distinct "haves" and "have-nots" in AI adoption, mirroring the early curves of the Internet in the 90s and Social Media in the 2010s.
The data shows a public split by education and exposure. But the corporate story is even more fascinating. The "OpenAI Moment" didn't just democratize access; it forced a massive, often frantic, strategic pivot in the enterprise.
The Invisible Era: Machine Learning
Before November 2022, AI was already ubiquitous. We just called it Machine Learning. It lived in the basement of the enterprise—boring, profitable, and invisible.
It was the engine behind medical research, eCommerce recommendations, programmatic advertising, and Google Search. It powered customer experience routing and fraud detection. It was "Utility AI."
The "OpenAI Shock"
When OpenAI opened their models to consumers, they changed the metric of success. This created two distinct challenges for established companies:
1. The Wall Street Punishment
Suddenly, "Utility AI" wasn't enough. The market perception shifted overnight: if your AI wasn't accessible to the public via a chat interface, you were viewed as "behind."
Stock prices were punished not based on revenue, but on perceived AI capability. This forced CIOs to pivot resources from high-value backend optimization to high-visibility frontend chatbots.
2. The Big Tech Divergence
The response from the tech giants illustrated the split:
- The Scramble: Google, whose moat is consumer search, was forced to scramble. They had to release consumer-facing models (Gemini) rapidly to prove they hadn't lost their edge.
- The Steady Hand: Amazon and Anthropic took a different path. They continued to target the enterprise. They understood that while consumer bots generate headlines, enterprise infrastructure generates recurring revenue.
The Strategy Paradox
The most ironic casualty of this shift was the mature enterprise. Companies that had been using AI for a decade were suddenly bombarded with board-level questions: "What is your AI strategy?"
They had to stop doing the work to explain that they had been doing the work all along. They were forced to rebrand their "Machine Learning" as "AI" just to keep the market happy.
Sources
- Pew Research Center. "How Americans View AI and Its Impact on People and Society." Pew Research, Sept. 17, 2025, View Report.
Disclaimer: This blog post reflects my personal views only. AI tools may have been used for brevity, structure, or research support. Please independently verify any information before relying on it. This content does not represent the views of my employer, Infotech.com.
Comments