Last month, Angel Ribo asked an operations executive at a global industrial company how teams had taken the corporate ERP rollout from a decade earlier. The executive shrugged. Half the organization was unhappy, he said. The other half, less happy.
Not really a complaint. A diagnosis.
These systems work when you are making a thousand identical widgets a day. They do not work when every job is one of a kind, routing across dozens of work cells, across multiple plants, with the real state of the operation living in human memory.
And that is where discrete manufacturing finds itself in 2026. It is also why AI-enabled PLM modernization for discrete manufacturers has quietly become the defining shift of Industry 4.0.
The shift is not about replacement
Most CTOs in discrete manufacturing will not say it out loud, but their PLM stack is strained. Strained in the slow, expensive, invisible way. BOM revisions that take four days when they should take four hours. Handoffs between mechanical and electrical that live in three different tools and one very tired program manager. A digital thread that is more aspiration than reality.
Ribo has been inside this industry for more than two decades. That includes time within two of the global leaders in PLM software. The last fifteen years, his work has focused on the Americas. Close to 1,500 companies. Thirty-three countries. Every discrete manufacturing vertical you can name.
And the pattern, he says, is unmistakable. Manufacturers are not buying new PLM. They are rebuilding what they have around AI.
The names are familiar. Siemens Teamcenter. PTC Windchill. Dassault Systèmes 3DEXPERIENCE. Autodesk Fusion Manage / Fusion Industry Cloud. Aras Innovator. Deeply embedded. Rip-and-replace is off the table. What is happening instead is a new agentic AI layer wrapped around them, reading their data, surfacing intelligence, and executing decisions the original platforms were never designed for.
The workflows being compressed are specific. Engineering Change Orders propagating across BOMs, tooling, and suppliers in minutes. EBOM-to-MBOM reconciliation without a war room. Supplier qualification and part substitution happening in real time. Natural-language access to decades of engineering data. Generative design at a scale no human team could match. Voice-first shop floor capture turning operator knowledge into structured data.
Defining the problem first
In a separate conversation, Ribo sat with the IT leader of a mid-sized North American manufacturer. The challenge came out clean. Real inefficiencies across the operation. Production scheduling chaos across machine cells. No CRM connected to the customer side. An ERP managing inventory in isolation from sales.
And yet, this IT leader had deliberately chosen not to apply AI to any of it. He needed to know what each broken workflow actually cost the company before he picked a tool to fix it.
The reasoning was simple. You cannot solve a problem that has not been defined. Ribo has cited it since. The discipline of 2026, he argues, is not picking AI tools faster. It is defining the workflow first, in measurable terms, and only then bringing AI to bear.
A viewpoint that cuts against the consensus
Ribo has gone on record with a contrarian position on the talent question. In his view, AI-enabled PLM work for North American manufacturers is poorly served by offshore delivery from locations separated by twelve-hour time zones and three cultural layers from the engineering organization. Too many of those engagements quietly stall. The work calls for senior engineers embedded inside the engineering team, operating in the same time zones. An unpopular position. One he continues to defend.
Where it is heading
Manufacturing CTOs who move in the next eighteen months will build cycle-time advantages that compound for a decade. The rest will spend that decade catching up.
Follow Angel Ribo II on LinkedIn.
*AI-enabled PLM modernization is the practice of wrapping AI capabilities around existing PLM systems — Siemens Teamcenter, PTC Windchill, Dassault 3DEXPERIENCE, Autodesk Fusion, Aras Innovator — rather than replacing them.
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