AI pilot era crosses a threshold

Don’t ask me how old I am, but let’s just say I remember the days when my co-workers and I sat around conference rooms wondering if we should invest time and energy into developing a strategy for “the Internet thing.” I wonder now how we could have ever questioned it. But innovation, especially technological, often comes down to the early adopters and then the masses. The masses caught on, and even grizzled veterans have trouble remembering how we were even productive without it.

This is where we are when it comes to digital transition in industry. We’re long past the “should we” stage, and well into the “why didn’t we do this sooner” stage. And, artificial intelligence (AI), while still the subject of those early adoption meetings, only serves to accelerate the transition for everyone.

For example, Rockwell Automation just released its “2026 State of Smart Manufacturing Report,” which tracks the pulse of global manufacturing. This year, the headline is that digital transition is no longer optional, and AI is what’s making it happen. Its data suggests that industry has left the pilot era of AI transformation behind.

Drawing on 1,560 decision-makers across 17 countries, the report reveals that companies are no longer gathering in those conference rooms—or video chats—to debate the transformation, but are executing it. In fact, 90% of respondents said digital transformation is essential for staying competitive, which Rockwell adds is the first year the industry has labeled it as a business requirement, not a strategic ambition. 

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As usually happens with game-changing innovations, the divide over AI adoption has moved from early adopters and those waiting for more maturity from the technology before acting to users and organizations that can operationalize it at scale, and those that are stalling under the weight of their own complexity. 

Of the respondents to the survey, 59% are already using smart manufacturing technologies at scale, up from a field dominated by pilots just one year ago (56% were piloting in 2025; only 18% remain in pilot mode today).

In addition, 34% of operations are AI-augmented right now, and projected to reach 54% by 2030, with AI and machine learning (ML) ranked as the top outcome driver by 48% of respondents. 

Meanwhile, 46% experienced a cyber-incident in the past year, and operational resilience plays a significant role in sustaining performance and continuity. And 43% of collected operational data is used effectively. For organizations racing to scale AI, that's not a data problem—it's an execution problem. 

The best execution will be the result of the abilities of an organization’s workforce.

Back in those early days of the Internet, I sat in training sessions to learn what is today just part of my workday, every day. Rockwell’s survey indicates 40% of the manufacturing workforce was reskilled last year as organizations restructured roles around intelligent systems. 

Rockwell calls this the the “execution era” for digital transformation and AI. I tend to agree. We’re in the stage where the winners aren't the companies with the most advanced technology, but those who have built the systems, architecture and workforce to act on intelligence in real time. 

Tomorrow may be a new day, but it’s already here.