How Is AI Affecting Infrastructure Pros?

IT staffers are supporting AI initiatives, but they often don’t have the hardware resources those projects really need.

A little over a year ago, Network Computing examined some of the predictions about how artificial intelligence (AI) would affect IT infrastructure pros. In the months since then, AI and machine learning have invaded the enterprise.

Marianne Daquila, a research manager at IDC, noted in September that AI “has moved beyond the early adopters to mainstream industry-wide use case implementation.” She added, “Early adopters in banking, retail, and manufacturing have successfully leveraged cognitive/AI systems as part of their digital transformation strategies. These strategies have helped companies personalize their relationship with customers, thwart fraudulent losses, and keep factories running. Increasingly, we are seeing more local governments keeping people safe with cognitive/AI systems. There is no doubt that the predicted double-digit year-over-year growth will be driven by even more decision makers, across all industries, who do not want to be left behind.”

Given the tremendous growth in the AI and machine learning markets, now seemed like an ideal time to revisit those predictions and look at the impact AI is actually having on infrastructure professionals today. Current research shows that AI is affecting enterprise IT staff in five key ways:

1. IT teams are currently supporting AI initiatives

If your enterprise isn’t doing anything AI-related, you’re in the minority. A report titled Cognitive Diversity: AI and the Future of Work, based on a survey conducted by vendor Tata Communications and Ken Goldberg, professor of engineering at the University of California, Berkeley, found that 80 percent of organizations were using AI.

However, quite a few of those AI projects are still in the experimental stages. A separate study, the Interop ITX 2018 State of AI, revealed that about two-thirds of its respondents had AI initiatives underway, but only 12 percent of organizations were actually using AI in production.

2. Enterprises don’t have adequate IT infrastructure to support AI plans

Why aren’t more enterprises using AI in their production systems?

A big part of the problem is their existing infrastructure.