Rootstock Software
Raj Badarinath, Rootstock’s chief marketing and product officer, speaks during Rooted-In, his company's conference March 25-27 in New Orleans.

With AI, the time is now, say manufacturing technologists, futurist, 'evangelist'

April 4, 2024
2024 is the ‘year of implementation’ when it comes to this breakthrough technology, though speakers at a recent New Orleans conference conceded they often must still explain what AI means and what it can do for most industrials who remain uninitiated.

NEW ORLEANS—Call them “technologists,” or “digital evangelists,” or even “industrial futurists.” What they’re preaching now: Application of artificial intelligence in manufacturing has arrived and, according to one leader at a conference here, 2024 is the “year of AI implementation”—otherwise he and others fear companies that make all manner of things risk falling behind.

Vala Afshar is “chief digital evangelist” for Salesforce, the customer relationship management (CRM) software provider that partners with Rootstock Software on a cloud-based enterprise resource planning (ERP) suite of tools, and his was a prominent voice at Rootstock’s Rooted-In conference for more than 2,000 industrial technology types here March 25-27.

See also: Revolutionizing manufacturing: The role of industrial AI

Afshar’s was—by far—not the only voice, however.

Also singing in the AI choir were futurist Christina “C.K.” Kerley, Rootstock’s Interim CEO Jeff Ralyea, Raj Badarinath, Rootstock’s chief marketing and product officer, Chief Information Officer Chad Wright of Boston Dynamics, and Sean O’Meara, who is a self-described “technologist” but whose formal title is CIO of Monticello, Indiana-based Girtz Industries, which designs and makes power modules and enclosures for custom generator sets, chillers, boilers, and switchgear.

Ralyea, Badarinath, and O’Meara met in separate one-on-one interviews with Smart Industry to talk about the direction of the ERP market and Rootstock and Salesforce’s team-up.

It was O’Meara who described himself as the “dreamer of his organization” and he was chief among the three to experiment personally with the capabilities of AI for manufacturing.

See also: Rootstock reveals ‘Rooties’ for excellence in ERP ecosystem

O’Meara’s “aha moment” with AI came over a holiday break in December 2022, when he got some messages about ChatGPT, the AI text chatbot made by the company OpenAI that was released as a free web-based tool late that year. He said he stumbled on ChatGPT videos on YouTube and played with the tool on his iPhone. O’Meara asked ChatGPT to write blogs about highly technical information, and the results were eye-popping, he said.

“I plugged every thought I had into ChatGPT,” O’Meara told SI. “My world of data changed that night. I told my staff that AI is coming.”

He led a business session at the Rootstock conference on harnessing the power of AI in manufacturing and in the ERP environment, on which the New Orleans meeting focused for Rootstock customers, prospective customers, and partners in its lane of the manufacturing software business.

See also: Gen-AI’s rewards are clear, but the data must be ‘clean’

O’Meara told his conference session that his biggest challenge as Girtz’s CIO is worrying about “what’s not even there yet” and to make sure his company doesn’t close any doors on technology that would aid the generator component maker that isn’t even out yet—or, like AI, that has huge potential but is just in its relative infancy and not understood easily by everyone.

Later in his one-on-one with SI, O’Meara said most of his execs at Girtz understand AI enough to “know what they don’t know,” adding that “you almost have to work behind the scenes to prepare to use AI.”

So, what should everyone know about AI? according to O’Meara.

He said AI’s clear use cases for manufacturing are generating marketing campaigns; writing understandable operations manuals, often from highly technical data that isn’t easily understood by everyone on the plant floor; building training courses; and offering design assistance.

As one example, he said, AI can take a look at uncommitted production time on a factory’s floor and design a targeted marketing campaign to create consumer or customer demand for a product that could then be produced during that hole in the manufacturing schedule, an efficiency boon and a way to maximize productivity and profit to boot.

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There is predictive AI and generative AI, or Gen-AI, he said. Predictive AI can look at historical data, from machine-installed sensors, on operational variances and predict when breakdowns are likely to occur, allowing an industrial to schedule maintenance when that machinery is most likely to need it or otherwise suffer unplanned downtime.

Gen-AI generates something completely new, O’Meara added. If predictive AI tells a company that it’s likely to see a breakdown at a certain time, Gen-AI can recommend measures, like ball-bearing replacement, that can prevent the breakdown from ever occurring.

The well-publicized hazards of AI—incomplete and disparate or “siloed” data, deepfakes, and hacking where an industrial’s competition could use its own data against them—are very real hazards of AI, O’Meara added.

Futurist predicts AI’s transformative shockwaves

C.K. Kerley kicked off Day 2 of the Rooted-In conference with much boosterism about AI’s potential to transform and help automate industry. But the futurist, who spoke overall on manufacturing megatrends, emphasized that humans’ productivity is “enhanced and focused” by AI technology—not replaced, as so many doomsayers in and out of industry fear.

On the contrary, she said, AI will not be a job-killer but a job-creator or job redistributor. “I'm looking at humans [having] more time with humans. AI moves the needle for our businesses, and it also improves the experience for ourselves and our work.”

See also: Production planning: How AI can help meet every delivery deadline

“AI is the next productivity frontier,” she added, “it’s the complexity and friction [from manufacturing and supply chain processes] it will take away” from flesh-and-blood people. We have been doing the jobs of the robots for too long.”

She said AI will restructure the amount of time workers spend on administrative tasks (now about 57%) to innovation (now only about 7%). “We need to flip that,” Kerley said, adding that AI will reshape both the tasks of work and the tools used to do that work.

Another way AI will profoundly alter manufacturing and the U.S. workforce is skills, Kerley predicted. And businesses—most especially including industry—will need to be drivers of a massive “reskilling” push, she said, citing statistics that say 85 million jobs could go unfilled by 2030 because of the skills gap.

“AI is driving a monumental skills gap,” she added. “We’ve gone to constant reskilling. By 2025, 50% of workers globally will need to be reskilled. This will put real pressure on all employers to be reskillers.”

Rootstock product chief talks ‘signal chain,’ data, and AI

As the show in The Big Easy did during almost every session, Badarinath focused on products for customers and would-be customers and partner adopters of Rootstock and Salesforce’s software. Badarinath leaned on Rootstock’s focus on what he called “signal chain” in discussing his company’s cloud-based ERP and its value in the marketplace vs. competitors.

AI, he added to SI, would be the logical extension of the Rootstock/Salesforce product, but Badarinath had insights on what artificial intelligence will do for manufacturing companies and their processes. And a key to proper use of AI, he noted, will be data quality and accessibility for any industrial company.

See also: Looking to implement AI-powered remote operations? This is what you must know

“We're not saying AI is going to take over and replace human decisions. AI will augment humans,” he observed. “AI has got to learn over time, so you need to train data. AI does really two things … [it] can either predict or it can classify.”

“So, either they're predicting, with a level of probability, or you’re classifying,” he continued. “When we look at making good decisions or having decisions that matter to the business.

“You cannot make good decisions if you don't have the data. You need signals which essentially connect all the value chain players to fill the tank of data right with different signals in real time. You need that and then, and on only then, you're ready to build AI models that will help with your decisioning.”

About the Author

Scott Achelpohl

I've come to Smart Industry after stints in business-to-business journalism covering U.S. trucking and transportation for FleetOwner, a sister website and magazine of SI’s at Endeavor Business Media, and branches of the U.S. military for Navy League of the United States. I'm a graduate of the University of Kansas and the William Allen White School of Journalism with many years of media experience inside and outside B2B journalism. I'm a wordsmith by nature, and I edit Smart Industry and report and write all kinds of news and interactive media on the digital transformation of manufacturing.