In Stay Sharp Episode 117, Looking Ahead in Digital Engineering for 2026, co-hosts Jonathan Scott and Juliann Grant take a moment at the start of 2026 to discuss what they expect to see in digital engineering over the next year.
New PLM Offerings
Jonathan kicks things off with his expectation that Autodesk will capitalize on their expertise in architecture, engineering, and construction (AEC), as well as the capabilities they have in their Forge cloud development platform, to enter the PLM market. He explains, “I think they’re going to bring stuff together in a way that gives us something new and something interesting to look at and think about and recognize.”
Another vendor offering he thinks we might see in the near future—though he isn’t sure what vendor might deliver it—is a digital twin offering from an ERP vendor. His suspicion is some of those larger vendors, like SAP or Microsoft, may be watching digital twin and digital thread conversations and recognizing that they already hold a lot of that information. “I wonder if we’re not going to see somebody jump in and say, Hey, I’m going to build out my portfolio to add some of that PLM capability and have it be a full digital twin platform,” he says.
Talking About AI
Juliann shares a tidbit from a Gartner webinar about 2026 predictions—the idea that in the coming year for B2B organizations, AI will handle at least 80% of all customer-facing processes, from procurement to service and more. “How they’re interacting with companies, how they’re engaging, how they buy, how they get serviced, how the ongoing relationship happens with a customer. AI will be handling 80% of that,” she reports. “I don’t know how many companies are really prepared for that.” Gartner also predicted multi-agent layering ahead. That means AI agents talking to AI agents, such as Jonathan telling his AI agent he’s hungry and wants a pizza, and that agent dealing with the pizza delivery shop’s agent to order and get one delivered.
Jonathan’s thoughts on AI start with using it to enrich existing data and then stacking AI tools to analyze or interpret the enhanced data. Extracting insights is also a driver for another potential development: facilitating smart manufacturing. AI could be widely employed to collect the huge volume of manufacturing data that exists and parse it to find relationships, thereby helping manufacturers see connections they’d never have thought to look for. Of course, Jonathan cautions, AI will still need to be checked by a human who can agree with the conclusions. “I am worried that AI will make mistakes, and if we don’t check it will make bad relationships, bad inferences that lead to bad products and problems and failures and really bad stuff” he says. “I really worry about that if people make too many assumptions and let AI do it.”
The Curve Balls
That concern over AI laziness leads to the biggest curve ball Jonathan and Juliann believe will appear in 2026—legal questions or challenges around the technology. They agree it’ll be time to address many of the questions about what happens when AI is involved and accidents occur or life/safety are at risk. At the very least, Juliann suspects AI may get some basic guardrails, such as regulations or compliance mandates, because while there’s a need for AI, there’s also a need to define where AI will operate and where it won’t.
Other curve balls the duo speculates on include additive manufacturing and supply chain volatility making comebacks. Jonathan also mentions the so-far-unknown impact of quantum computing developments, as well as new players in digital engineering that are vertically integrated. As an example of the latter, Jonathan mentions Czinger Automotive, which uses their own software and their own 3D printing to make, design, and assemble parts for their high-performance electric car. “They’re doing it all. Requirements came in and parts came out and it was flexible. It was mind blowing that they could scale it,” he says. Juliann agrees, marveling, “You don’t need the supply chain. It’s all right there.” One thing is for sure about 2026: the disruption could be real.
Learn More About What 2026 Could Bring
The full podcast contains more discussion and details on a variety of topics, including how combining multiple AI inputs might improve accuracy and save time, why Jonathan and Juliann are skeptical about collaborative robots (or “cobots”) becoming a trend anytime soon, why quantum belongs on the list of predictions even if they don’t know how it might impact digital engineering, and more.
Be sure to check out Stay Sharp Episode 117: Looking Ahead in Digital Engineering for 2026 and join us each week for a new podcast.
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