I devoted three days in April to attend the Aras Community Event (ACE 2026) in Miami, FL. Even though I am not a specialized market analyst in that market, I’ve been involved with the application of product lifecycle management ever since I was “The Kid in Engineering” at a manufacturing company back when, well, I was just a bit older than a “kid.”
Our company (another company that designed and built automated assembly equipment) transitioned to computer-aided design (CAD) while I was in management. Later, I became involved with AutoCAD.
So, there are memories of the great advances in the technology and capabilities.
My first summary of my three days with the Aras community in Miami was recorded on my podcast and YouTube channels. As I wrote at the time, “These PLM events always return me to the time when I did this sort of work–manually. Then my first taste of computers digitizing the bill of materials as a first step in our data management journey.”
Aras product managers showed how LLMs trained on the data within the app along with proper governance worked with agents to perform a number of tasks. Tasks in many cases that would require days of pain-staking work from a human.
While I heard from an analyst in the market that they thought this was all painfully slow, I’d offer the thought that a company does not want to outpace its customers. Most will not want to jump into the deep end immediately.
Chatting with CTO Rob McAveney, I heard how the company is taking a balanced approach to introducing these new technologies assuring that they are bringing their customer base along laying out the progression of “agentification of PLM.” The vision includes turning Aras Innovator into an “enterprise nervous system.”
The pressure of digitalization and the so-called digital transformation of companies drives these developers and suppliers into trying to find solutions to the immense data problems they face. Aras’ core technology lies in the digital thread, a topic often referred to.
Ironically, my discussions with Aras and some customers and prospects during the conference revealed an unhealthy fact that I’ve often heard in another software application market—MES. It seems that few users use the full complement of solutions offered by the vendors. This means that what could be a mature market is actually open for new solutions—meaning an innovative upstart like Aras has opportunity for market growth.
I researched the market using my favorite search engine—Claude.ai. The global PLM & Engineering software market reached $31.1 billion in 2024, growing 9.7% year-over-year, and is projected to hit $41.6 billion by 2029 at a ~6% CAGR. The top 10 vendors account for roughly 85% of the total market.
The leading suppliers include Siemens Digital Industries, Dassault Systèms, PTC, and Autodesk. Analysts report Aras Innovator is built for adaptability, offering a platform designed to evolve quickly with a low-code development environment and strong Digital Thread capabilities.
The four key development points for Aras agentic AI and LLMs, which were repeated often are:
- Trust
- Governance
- Observability
- Explainability
Shortly following the Aras event, I attended virtually the Siemens press conference from Hannover Fair.
Further research between the two revealed these thoughts from a variety of analysts.
Siemens Teamcenter Copilot is powerful but bounded. Siemens’ approach includes Teamcenter Copilot and AI Chat for natural language queries, RapidMiner for spotting quality issues, and AI extraction of procedures from static PDFs. Siemens describes it as “training AI in the language of engineering and manufacturing” — embedding domain-specific intelligence aligned with physics, lifecycle context, and operational constraints.
However, what Siemens is doing is focused, practical, and grounded in helping users navigate data Siemens already manages well. The copilots do not attempt to extend beyond Teamcenter — they do not ingest data from other PLM tools or external systems that influence product decisions, and the improvements remain confined to the boundaries of one platform.
Aras’s approach is architecturally more open. InnovatorEdge is designed so that product data, processes, and digital thread remain governed inside the core platform, while Edge services make them consumable everywhere else — enabling agents to link data across PLM, ERP, IoT, and documents.
One independent analyst commentary summarized the broader landscape bluntly: all four major PLM vendors — Siemens, Dassault, PTC, and Aras — are adding AI inside their products, but none of them are rethinking PLM architecture for an agent-native future. They are embedding assistants inside old systems rather than redesigning systems around the needs of agents. That said, Aras’s open, low-code, API-first architecture puts it structurally closer to an agent-ready foundation than Siemens’s more monolithic platform.
ACE attendees noted that while AI’s transformative potential was clear, discussions also centered on the need for human oversight, data governance, and addressing concerns about traceability and the dynamic nature of LLMs — suggesting customers are excited but appropriately cautious about full autonomy.
