As we hurtle our way into the 2025 holiday season, the Aras marketing team is laying the groundwork for our 2026 community event program beginning with our annual ACE user conference running April 13-16 in Miami, FL.

It was just three weeks ago that we finished our 2025 Aras Connect series, welcoming over 1500 community members to events in UK, Germany, France, Sweden, and Japan. Last year, our theme for community events was Connected Intelligence—a call to think more broadly about the fundamental importance of a digital thread strategy to modern PLM. We explored the potential of activating digital threads in order to streamline collaboration, accelerate decision making, and realize the potential of advanced analytics and AI.

Our ACE 2025 program in Boston was a special celebration of the 25th anniversary of Aras’ founding. We brought together leading industry thinkers to reflect on how PLM has evolved and where it must go next. These voices have continued to shape industry narrative throughout the past year.

  • Gartner’s Sudip Pattanayak spoke on the evolution of the digital thread concept and continues to explore its relationship with PLM (see Implement Digital Threads for Long-Term Flexible Access to Critical Data).
  • Martin Eigner spoke on an ACE panel and called on the industry to think more broadly about digital threads, PLM, and PDM. He continues to write on the potential for unlocking the potential for AI-driven value creation in the context of a Digital Thread as a Service (DTaaS).
  • Peter Bilello and the CIMdata team were in attendance at ACE. In this engineering.com article, Peter reflects on conversations at their annual PLM Roadmap and PDT North America meeting and calls for a “Rethink” of how to manage the digital complexity that has emerged in PLM and digital engineering.
  • Oleg Shilovitsky was in attendance and wrote this reflection on Rob McAveney’s keynote for BeyondPLM.com. Oleg continues to blog extensively on the intersection of AI and modern PLM.
  • Michael Finocchiaro ran a series of podcast interviews with ACE. He continues to podcast, post, and blog on agentic AI, PLM and the rapidly evolving digital engineering landscape – recently launching a new podcast series: AI across the Product Lifecycle
  • Lionel Grealou attended ACE, covering a keynote presentation from David Widegreen from CERN in engineering.com: Managing the world’s most complicated machine. I continue to follow Lio’s work and liked this recent piece on the impact of AI on jobs where he states, “The future of work is not about replacing people with AI. It is about designing a productive coexistence where human creativity, ethics, and contextual awareness guide machine execution.”
  • Aras CTO Rob McAveney led a discussion asking as series of “What ifs” around the potential for AI and PLM: What if you could talk to your Requirements Documents? What if Change Management was easy? What if you could simplify variant management?
  • I had the honor of opening the session with my colleague – Aras’ former head of global sales, Leon Lauritsen. We were excited to see Leon appointed as the new CEO of Aras a few months back and looking forward to his keynote in 2026.

It was at ACE 2025 that we introduced Aras InnovatorEdge, a low-code API framework that extends and integrates digital threads built on Aras Innovator. Aras InnovatorEdge opens new approaches for integrating the digital engineering ecosystem with PLM; enables secure connections to value chain partners operating outside your firewalls; creates a new paradigm for building applications and workflow; and provides a platform for governed data exchange with AI services.

Connected Intelligence laid the groundwork for our discussion. Next year’s theme—Adaptive Intelligence—raises the stakes.

The truth is, the world has changed faster than the systems designed to support product development organizations. Complexity is compounding. Decisions can no longer wait. And most PLM architectures remain rooted in a model built for when data moved slowly and change felt manageable. Organizations need systems that can interpret, anticipate, and respond.

I really liked this series of LinkedIn posts by Benedict Smith that reflected on the root of the problem behind the world’s struggles with PLM.  What I took from it was this: For decades, PLM has played a crucial role in controlling change and maintaining a single source of truth. But it has always been a system you interrogate, not one that helps you think. Teams spend too much time searching, reconciling, and manually stitching together the impact of every decision.

Adaptive Intelligence represents the idea that PLM software needs to do more than just store information. It should help identify the signal in the noise, illustrate impacts before issues cascade, and align working groups in real time. For years PLM has been a system of record.  We’d like to see it become a system of guidance. It is about shortening decision cycles, lowering coordination friction, and enabling PLM itself to evolve at the pace of business.

Compressing the “sense → decide → act” loop

Adaptable organizations detect change early, decide fast, and move together. AI-native PLM should continuously monitor the digital thread and turn weak signals into clear guidance. Instead of waiting for weekly design reviews or firefighting after an issue hits manufacturing, AI can surface potential issues to human operators (e.g. requirements drift, design instability, test anomalies, supplier risk, etc…) while there’s still time to pivot.

When the system is always sensing and interpreting, teams stop reacting late and start steering early.

Reducing the cost of coordination

Most organizations aren’t slow because people are slow. They’re slow because coordination is expensive. Every change forces meetings, emails, reconciliations, and “did everyone see the latest?” moments. AI can reduce this cost by orchestrating informed collaboration between human users and agentic counterparts in engineering, quality, manufacturing, supply chain, and service.

The more AI can clarify “what changed, why it matters, who it affects, and what to do next,” the less the organization depends on manual alignment. When alignment is cheap, adaptation can be fast.

PLM software should evolve with the business

This is the true next-gen leap. Adaptability isn’t just about executing change efficiently—it’s about not being trapped by yesterday’s data schema. AI-native PLM helps organizations re-shape their processes and digital thread as the business changes. With AI-assisted modeling, rule generation, and low-code extensibility, new workflows and capabilities can be delivered in days instead of months.

Adaptive Intelligence is not just about managing product change better.  It is about enabling PLM and digital threads to adapt as strategy, products, and operating models evolve.

From Connected to Adaptive

Connected Intelligence establishes a living product digital thread. Adaptive Intelligence is about activating it.

At ACE 2026, we’ll show how AI-native PLM and intelligent digital threads move PLM from a system of record to a system of guidance where AI and human users can collaborate and learn from every interaction, adapt to every change, and guide every decision. This isn’t an incremental evolution. It’s the beginning of a new era for product development. Join us at ACE 2026.

Agenda and registration information at aras.com/ace.

Category:
ACE Aras Insights Artificial Intelligence Digital Thread