# Corporate America is moving too slow on AI

> While AI safety debates dominate headlines, most companies are stuck in early adoption phases and risk falling behind competitors who are already scaling.
- Title: Corporate America is moving too slow on AI · Fortune
- Summary: While AI safety debates dominate headlines, most companies are stuck in early adoption phases and risk falling behind competitors who are already scaling…
- Keywords: artificial intelligence, corporate adoption, ai strategy, talent shortage, board oversight, ford, ai deployment, business transformation, workforce reskilling, competitive advantage, Corporate, America
- Source: Fortune — https://fortune.com/2026/09/18/secret-truth-corporate-america-moving-too-slow-on-ai
- Author: Ryan McManus
- Read time: 2 min
- Topics: artificial intelligence, corporate adoption, ai strategy, talent shortage, board oversight, ford, ai deployment, business transformation, workforce reskilling, competitive advantage
## AI safety debate misses the real risk
While Anthropic, Sam Altman, and Elon Musk call for slowing AI development, most companies face a different problem: moving too slowly to adopt it and falling behind competitors.
## The talent gap is real but not the whole story
A small pool of AI experts explains some slowness, but caution and self-protection also hold companies back. Competitors won't wait for the cautious ones to catch up.
## Boards are unprepared for AI decisions
Only 22% of S&P 500 companies have board oversight of AI, and just 29% of leaders say they have the right expertise. Without federal guardrails, boardrooms are making the big AI calls alone.
## Ford's costly AI misstep offers a lesson
Ford installed 900 AI inspection cameras to replace veteran engineers, but the systems failed. They recovered by rehiring experienced engineers to train the AI and mentor younger workers.

> mistakenly, we thought that by just introducing artificial intelligence and ingesting the design requirements that we had, that would produce a high-quality product.
## Start with strategy, not technology
The first phase is setting vision and running quick-win pilots. Focus on making humans more productive, not replacing them, because today's AI has real limitations.
## The crawl-walk-run framework
Crawl: develop strategy and pilots. Walk: build complex use cases and track ROI while reskilling workers. Run: scale across the business and create entirely new products and value.
## Most companies are stuck in crawl phase
While competitors plan how to run, most organizations haven't moved past early pilots. The risk is falling behind in a market where AI capabilities are advancing rapidly.
## Deployment matters more than development
The debate focuses on who builds AI, but the real impact comes from who deploys it across the economy. Boardrooms, not Congress, will decide how most companies use these tools.
## Key takeaway

Companies need a deliberate crawl-walk-run strategy focused on making humans more productive first, not replacing them, while building the expertise to deploy AI responsibly.