Cummins' Analytics And AI Leader On The Reusable Information Fabric Driving Enterprise ROI

*All opinions expressed in this piece are those of Jim Jacob, and do not necessarily reflect the views of any organization.

Quickly 'bolting on' AI isn't possible for organizations operating in the heavy industrial sector. While AI headlines continue to contribute to the hype and exaggerated promises of overnight transformations and rapid results, industrial organizations are moving at a different pace than the digital-native enterprises dominating most of the AI conversation. Now, they must approach AI more deliberately, with product reliability, customer trust, and repeatable results taking precedence over speed.

For an expert's take, we spoke with Jim Jacob, Executive Director of Digitalization, Advanced Analytics, and Artificial Intelligence at Cummins Inc. Jacob has spent decades shaping enterprise-level AI in industrial settings, including architecting the first enterprise Digital Twin platform at 3M. For him, the question isn't if AI can transform business but how to do it reliably, repeatedly, and economically. "Living in an industrial, credible, and reliable company like Cummins, I find it difficult to bridge the AI adoption gap at the speed implied by the headlines. It's going to take time for us to bring these new AI technologies into our systems, test them, and offer them to our customers as a service."

First, Jacob aimed at a common assumption that companies can easily monetize AI by charging customers a premium. Comparing it to the environmental responsibility movement a decade ago, when the market saw customers quickly absorb new standards into their baseline expectations.

• An inconvenient truth: When discussing how AI features and functionalities are being pitched to customers and consumers, Jacob recalled that customers pushed back against environmental premiums, saying, "It's your duty to be socially and environmentally responsible. I believe the product you give me is going to cover all that. So why are you asking me for a premium?" Instead, Jacob noted, the real ROI from AI for industrial enterprises is experienced through internal efficiency gains rather than a new line item. "I think the monetization component is in the company, where efficiency and productivity can grow because of AI capability." As for charging customers more, Jacob added, "I doubt very much that that's the case today."

The market dynamic of not charging more for something that is perceived as standard informs his skepticism of the vendor market. Jacob describes the current vendor market as populated by players making baffling or simply impossible promises for where AI is today. He recounted a recent meeting where a vendor, after hearing about a thorny supply chain problem, promised a solution in "ten days." To navigate this market, Jacob uses a simple but effective tactic.

• Calling their bluff: Now, Jacob’s first question to any vendor who approaches the team is direct: "Where did you do that before, and I want to speak to the subject matter expert who lived with the problem and is able to tell me that you guys solved this for them." The response is typically "malarkey," Jacob said. In his opinion, you have to be skeptical because this is often how bad projects can get approved across enterprises, particularly when leaders are not deeply familiar with the underlying challenges.

• Pirate Land: From Jacob's perspective, with vendors promising overnight transformations and C-suite level pitches that skip over the operational realities, companies risk buying into solutions that never move beyond proof of concept. The danger, he warned, is that executives sign checks for flashy AI projects without securing proof of "sustainable enterprise level" value. The result isn’t just wasted investment, it's the fuel that further erodes credibility inside the enterprise, slows adoption, and creates skepticism that stalls more promising AI initiatives down the road. "It's unfortunate, but it's a pirate land right now," Jacob said.