There’s no shortage of AI survey reports these days, yet they keep coming. You decide whether that’s just eagerness to promote the current hype wave or actual importance. Not to mention, we all need to decide whether the data being offered is actually valid. Cisco just released “Cisco State of Industrial AI Report”, and we’ll get to that in a minute. Before we do I want to point out some of the barriers we face in assessing any such document.
A survey of any kind can be valid if the right people are asked the right questions, they understand the questions, and the analysis of the results isn’t biased in any way. There’s no way for me to judge Cisco’s bias here, so we have to look at the other points. Who are “the right people” and what are “the right questions”, then can the former understand the latter.
Almost everyone has an opinion on AI. Many, including almost anyone in tech, have at least used AI. However, most of these are not the “right people” for any survey of AI because they are casual users of a free-service AI model. In Cisco’s case in particular, they have nothing whatsoever to do with “industrial AI”, and probably don’t know what it is. The first Cisco-specific question is whether the people who contributed are among the few qualified.
Cisco’s introduction says “We spoke to decision-makers at firms in 19 countries, operating in 21 industrial sectors including manufacturing, utilities and transportation.” How many? I don’t know. What kind of decisions are they making, meaning do they have any direct understanding of what Cisco is calling “industrial AI”, and is their understanding consistent across the base, and with Cisco’s use of the term in analyzing their responses? I don’t know that either.
Based on this so far, I’d be justified in saying that this report’s value could not be assessed at all, and so my continuing it is a waste of my time, and reading it a waste of yours. OK, feel free to act on that. However, I do have enterprise views on AI to draw on, and I can compare the report to what those views reveal, so let’s do that and simply point out the potential reasons for difference where there is one.
I’m going to draw from a group of 181 enterprises who offered me comments on real-time edge computing applications, because 1) “Industrial AI” would seem to necessarily focus on direct process control and 2) process control missions already involve premises-hosted edge computing. Within that group is a smaller group of 48 who said that they believed it likely that their real-time applications would involve edge hosting away from the process points, which means that something other than local-area telemetry would be involved. However, I have over 500 comments on AI that I can reference if we need to look at broader attitudes. Finally, the report is long, so to do my analysis in a blog of reasonable length I need to focus on the executive summary, with some comment on the broad insights of the rest. OK? Let’s go.
Cisco’s Executive Summary starts with “Industrial AI demands network modernization”, and says that 51% of their survey base expected that AI implementation would require “significant increases in connectivity and reliability requirements”. In my 181-real-time group, this view was held by only 27%, and in the larger 500-plus group by 39%. It also says that 96% of those responding think that wireless networks are vital, which only around 5% of my groups of 500 and 181, and a bit over ten percent of my group of 48 believed. However, the Cisco comment that 44% of their base said greater edge compute capacity was needed and 42% that greater bandwidth was needed seems consistent with what I hear from the 181 group, but the broader group would have little or no qualification to offer a view on this.
The comments on security are interesting; Cisco finds 40% saying cybersecurity was a top obstacle to AI adoption. In my 500 group, three-quarters say that, but in the 181 group only about five percent did. The reason is that to both of my groups, the presumption is that AI would have to process business-critical data, subject to governance. It’s not clear that simple process telemetry data would have that requirement. The last security point, which is that 85% expect AI to improve their security posture, doesn’t align at all with what I hear from any of my groups. It also makes me wonder whether Cisco is asking people knowledgeable about industrial AI missions, because nobody I chat with sees AI’s application to industrial automation playing a security role at all.
Next, we have to look at the views of enterprises on just how real-time industrial computing, AI or otherwise, would actually develop. What they tell me is that they’d evolve out of the expansion of current missions of “local edge” computing, shifting in some cases to self-hosting of expanding real-time applications where multiple sites in the same metro permitted, and finally to edge services. Recall that only about a quarter of the 181 group had experienced any of this, and they were confined to a few verticals. In addition, the applications were not said to have an AI component.
The final point in the executive summary is that IT/OT cooperation is critical to “AI at scale”. They say 43% operate today with limited or no such cooperation, and 90% claim wireless instability with siloed IT/OT teams but only 61% with collaboration. They also say that without IT/OT collaboration, only 72% are confident of scaling AI, while with it 83% are confident. Here, “OT” means “Operations Technology”, meaning the process control elements themselves (the report doesn’t seem to define this, and I wonder if the people surveyed interpreted it correctly).
There’s some interesting data in this report, in the details that follow the executive summary, but also some that are troubling given the industrial-AI focus. For example, on page 13 the report shows that 22% of those who responded said they were already seeing favorable outcomes for AI, which my contacts indicate cannot be the case given that industrial AI adoption is in single digits.
What I think is true here is that Cisco is looking at an at-some-future-point vision of real-time process control, one in which wireless has a much greater role than it does today (today, most process/OT elements are hard-wired, and there is no significant view that this would change except to accommodate control of moving devices. Further, they are getting comments that conflate the evolution of real-time process control and the evolution of AI as a part of that. There is a potential role for AI in the future of real-time process control, both as a means of building the digital twins or world models needed, and as an element of such models. However, I can’t find a significant number of enterprises who have confidently-held views on either.
I wish the data gathering here was better focused; I think there could be a lot of value. However, it seems clear to me based on what I hear that the survey wasn’t able to maintain the tight focus on qualified targets and on-topic responses that was needed. AI is a technology; industrial AI is a mission, and if you’re reporting on the latter you keep that in mind.
