Crystal Ball 2026: Great Question podcast—AI and everything else
What you'll learn:
- Our SMEs said AI will come out of pilot programs in 2026 and into real production processes but that it has major obstacles to overcome like data limitations and threat actors' own AI that these cyberattackers are increasingly weaponizing.
- Rushed or poorly conceived AI initiatives tried but failed in the past, they quietly underperformed, and are getting shelved.
- In 2026, digital transformation will “no longer be optional” for manufacturers.
- See everything in the Crystal Ball Report.
Three weeks, the holidays, 10 stories, happy new year, a podcast, countless great predictions for one brand-new year. Welcome to the Crystal Ball Series 2026, and we do conclude the project with this podcast. Oh, and did we mention we’d be talking about AI—a lot?
We did talk about AI a lot during the series, because artificial intelligence in manufacturing is being talked about … a lot. And the point of much of the advice from the collection of SMEs this year was AI in worldwide industry is here to stay, or we should say getting more integrating into real production processes and not just pilot programs, as more than one of our experts wrote.
See also: Why AI is quickly becoming essential manufacturing infrastructure
Other of our SMEs also told us that AI has major obstacles to overcome—for one, itself. AI is increasingly being weaponized into a constantly morphing cybersecurity threat that is a danger to manufacturing IT and OT systems and networks that are still “legacy” and that still have a distance to go to catch up to the threats.
Another obstacle for AI: data. Not every manufacturer’s data is the same, but it matters to the success of an implementation.
Indeed, Nate Powrie of Maine Pointe wrote for us Jan. 7 that governance of said data “will emerge as the new bottleneck breaker” in 2026 and that “AI ‘accountability’ will hit full stride” this year and that “manufacturers won’t tolerate AI that’s not tied to hard metrics,” in short they won’t tolerate AI investments that can’t quickly be tied to improved ROI. Point is, you need “clean” data.
About the Podcast
Great Question: A Manufacturing Podcast offers news and information for the people who make, store, and move things and those who manage and maintain the facilities where that work gets done. Manufacturers from chemical producers to automakers to machine shops can listen for critical insights into the technologies, economic conditions, and best practices that can influence how to best run facilities to reach operational excellence.
Just like our podcast, here are a few of the highlights from the series:
Tim Gaus of Deloitte wrote how AI would in 2026 move “from promise to production,” out of the pilot stage, and that the human workforce transformation, as a result of AI adoption for real production, would shift to the forefront of organizations’ strategic planning.
Tim also wrote that digital transformation, of which AI is often a part, is “no longer optional” for manufacturers.
Frank Balonis of Kiteworks delved into an interesting notion that AI copilots will recommend—and sometimes enforce—cybersecurity policies. Frank predicted 75% of organizations moderately or extensively use AI and that 39% are adopting internal copilots.
See also: Roadmap to physically intelligent industrial operations
Christopher “CJ” Combs of Columbus kept it going with a lesson on why iterative AI is the path for enterprise success. Iterative is the “continuous, cyclical process of building, testing, and refining AI models or outputs, involving rapid feedback loops to improve performance, much like creating drafts of a document, but with AI.”
CJ writes that, though AI has been on boardroom agendas since 2022, a lot of those rushed AI initiatives tried then are quietly underperforming or getting shelved.
David Vitak, also of Columbus, also checked in with a snapshot of how the human-machine factory could look by upskilling employees and deploying AI at scale. He wrote of the absolute necessity of training programs combined with “smart” software.
He also wrote that by upskilling workers, measurable payoffs emerge from that such as faster AI adoption, fewer implementation struggles and higher employee retention.
Chaz Spahn of Adaptiva had useful advice on how manufacturers, given their heavy reliance on vulnerable legacy systems, can prepare for when AI is weaponized—when bad actors use this technology to make cyberattacks more efficient.
Podcast: Additive succeeds when 'no one cares the part they're holding is 3D printed'
He also goes into great detail about how AI can “supercharge” cyberattacks. He really gets into the weeds, which is helpful, including how threat actors are leveraging AI models to instantly develop exploit scripts tailored to their desired targets and vulnerabilities.
We pivoted to Ross Meyercord of Propel Software, who took on B2A’s use of generative AI in vendor selection for manufacturers. Not pilot programs but real production deployments that are changing how buyers are researching and evaluating vendors.
There was more in four Crystal Ball roundups with predictions from experts at Kiteworks, Configit, Gurucul, Nordlayer, Maine Pointe, CTERA, Smartcat, Emerson’s Aspen Technology, Operant, Leaseweb, and HighByte.
We hope you enjoyed the Crystal Ball Series and we look forward to bringing it to you in 2027. Happy new year from Smart Industry!
About the Author
Scott Achelpohl
Head of Content
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.