Aras enters the Leader's Quadrant!

Aras enters the Leader's Quadrant!

🚨 PLM just had a major market signal. For the first time since 2008, Gartner has published a Magic Quadrant for PLM — and Aras is now positioned alongside the traditional PLM giants. In this breaking-news episode of AI Across the Product Lifecycle, I sit down with Josh Epstein, CMO of Aras, to unpack what this means for the PLM market, why digital thread has become central to enterprise software strategy, and why “governed engineering AI” may be the real battleground for the next generation of product development platforms. We discuss why PLM has become too important for analysts to ignore, how Aras positions itself differently from Siemens, Dassault Systèmes, and PTC, and why AI in engineering cannot just be another copilot bolted onto messy enterprise data. The key question: Can AI transform engineering without a governed, explainable digital thread underneath it? Josh also goes deep on Aras Innovator Edge AI, Thread RAG, product memory, context graphs, lifecycle-aware AI agents, and what the engineer’s workday could look like when PLM starts decomposing into governed micro-experiences and agent-driven workflows. If you care about PLM, digital thread, engineering AI, enterprise software, or the future of product development, this one matters. ⏱ Timeline 00:00 — Breaking news: Gartner brings back the PLM Magic Quadrant 00:36 — Why did Gartner wait so long after 2008? 02:06 — Has the PLM market fundamentally changed? 04:28 — Why PLM is more complex than ERP or CRM 06:05 — Aras vs. the “Big Three” PLM incumbents 06:37 — Why CAD-agnostic PLM may now be an advantage 07:21 — Governed engineering AI vs. generic AI hype 09:37 — Trust, governance, observability, and explainability 11:34 — Why AI needs the digital thread to be actionable 12:45 — PLM data complexity: versions, effectivity, access, context 15:05 — How to market AI in 2026 without overpromising 15:53 — Aras Innovator Edge AI, Thread RAG, and workflow agents 17:08 — Product memory, context graphs, and decision traces 19:08 — Does Gartner validation change the sales conversation? 21:17 — Is PLM still the right category name? 23:50 — Cognitive digital thread vs. product memory 26:00 — What does an engineer’s day look like in three years? 27:00 — Adaptive PLM, micro-experiences, and agent-driven work 29:30 — Why PLM AI cannot just be dumped into a data lake 31:30 — The physical-world constraint: “close enough” is not enough 32:00 — Has PLM had its OpenAI moment yet? 🎯 Subscribe for more conversations on AI, PLM, CAD, manufacturing software, digital thread, and the next generation of engineering platforms. 💬 Comment THREAD if you want more deep dives on PLM, governed AI, and the engineering software startups reshaping this market. #PLM #DigitalThread #EngineeringAI #Aras #Gartner #MagicQuadrant #ProductLifecycleManagement #AI #EnterpriseAI #Manufacturing #CAD #PDM #ProductDevelopment #IndustrialAI #AgenticAI #AIEngineering #DemystifyingPLM #ThreadMoat

The Future of PLM Is Human? AI, Trust, Community & the Share PLM Summit 2026 Debate

What happens when some of the most respected voices in PLM gather in a Spanish vineyard to discuss AI, digital transformation, trust, community, and the future of engineering? In this special Share PLM Summit 2026 edition of The Future of PLM Podcast, host Michael Finocchiaro is joined by Jos Voskuil, Oleg Shilovitsky, Rob Ferrone, Patrick Hillberg, Nina Dar, and Maria Morris for a candid, unscripted discussion about the ideas that emerged from one of the industry’s most unique events.   The conversation explores why the human side of PLM remains the hardest part of transformation, whether AI will fundamentally reshape consulting and knowledge work, how organizations build trust during digital change, and why community may be becoming more important than technology itself. From AI adoption and organizational change to conference design and the future of professional expertise, this episode offers practical insights and thought-provoking perspectives from some of the industry’s most experienced practitioners. TOPICS COVERED • The evolution of Share PLM Summit and its human-centered approach • AI’s impact on engineering, consulting, and PLM careers • Why trust may be the real ROI of conferences • Lessons from successful and unsuccessful PLM transformations • Human adoption versus technical implementation • Digital transformation beyond software deployment • The future of work in an AI-driven world • Community, collaboration, and knowledge sharing TIMELINE 00:00 Welcome & introductions 01:20 Why Share PLM Summit feels different 03:30 Breaking away from traditional PLM conferences 05:45 Why attendees travel across continents to attend 07:35 PLM as a people-centered discipline 09:50 AI, digital overload, and human connection 12:40 Measuring conference ROI beyond leads and sales 15:10 Most impactful presentations from the summit 20:05 Data, AI, and the Gentelligence perspective 22:10 Helena Haapio’s keynote and the future of work 24:50 Will AI replace consulting and expertise? 30:05 AI, critical thinking, and engineering risk 31:10 Sponsors, trust, and community building 36:00 Workshops, learning, and audience engagement 42:20 Sustainability and digital product passports 48:20 The Share Nest initiative 51:55 The future of conferences and professional development 58:20 Trust as the new business currency 01:01:00 Community, networking, and collaboration 01:03:40 The value of disagreement and debate 01:05:00 One word that defines Share PLM Summit 2026 01:07:00 Closing thoughts #PLM #AI #DigitalTransformation #Engineering #Manufacturing #Industry40 #DigitalThread #DigitalTwin #ProductLifecycleManagement #IndustrialAI #FutureOfPLM #SharePLM #EngineeringLeadership #SystemsEngineering #Innovation #TechnologyLeadership

When AI Meets Sales, Support & Supply Chain: Omnae & Bardin AI

AI in manufacturing does not fail because the demo is bad. It fails when the answer cannot be trusted. In this episode of AI Across the Product Lifecycle, Michael Finocchiaro speaks with Fay Goldstein, Co-Founder and CEO of Bardin AI, and Scott Lionello, Co-Founder and CPO of Omnae Technologies, about where industrial AI is really going: beyond chatbots, beyond copilots, and into the operational workflows that actually run manufacturing businesses. Bardin AI is building an application engineer for industrial automation sales and support teams, helping them answer complex technical questions without escalating everything to senior engineers. Omnae is building supply chain collaboration software that allows AI agents to operate safely across real suppliers, buyers, orders, invoices, and messy enterprise data.   The conversation goes straight into the hard parts of industrial AI: trust, auditability, determinism, human-in-the-loop workflows, knowledge graphs, API costs, token burn, procurement risk, sales engineering bottlenecks, and why “just add a chatbot” is not enough when mistakes touch contracts, general ledgers, supply commitments, or customer trust. Fay and Scott also discuss how AI is changing startup operations and software development, why young professionals need to show AI fluency rather than fear AI replacement, and why mid-market manufacturers may adopt practical AI faster than large enterprises waiting for top-down transformation programs. The big takeaway: the next wave of industrial AI will not be about flashy demos. It will be about operational relief. Fewer escalations. Faster quoting. Cleaner supplier collaboration. Better support workflows. Safer automation. More trust in the decisions AI helps make. This is a grounded, founder-level conversation about how AI is moving into the less glamorous but highly valuable parts of the product lifecycle: sales, support, procurement, supply chain, and the industrial back office. Topics covered: industrial AI, agentic AI, supply chain AI, procurement, pre-sales engineering, industrial automation, knowledge graphs, AI trust, human-in-the-loop workflows, manufacturing software, digital transformation, enterprise AI, startup innovation, and the future of AI across the product lifecycle.

CAD, BIM, and the AI Leap: Qonic & Raven!

What happens when AI moves beyond chatbots and starts reshaping the actual tools engineers, architects, and designers use every day? In this episode of AI Across the Product Lifecycle, Michael Finocchiaro speaks with Chloë Guidi of Qonic and Moritz Rietschel of Raven about the AI-native future of CAD, BIM, and AEC workflows. Qonic is building a modern, cloud-based BIM platform from scratch, including its own solid modeling kernel, with a mission to make BIM lighter, faster, more accessible, and more data-rich. Raven is building AI-first workflows for complex design environments like Rhino, Grasshopper, Revit, Tekla, and Archicad, helping users navigate fragmented toolchains with less friction. The conversation cuts through the hype and focuses on what is actually changing: AI-assisted software development. AI-native design workflows. Smarter BIM quality checks. More accessible CAD and AEC tools. The economics of LLM-powered software. The difference between “software built with AI” and “software that only makes sense because AI exists.” Chloë and Moritz also discuss whether engineering and BIM are heading toward their own “OpenAI moment,” why open standards and data quality matter, and what young engineers should do as AI changes the skills required to stay relevant. This is a practical, founder-level look at how AI is moving into the real workflows of design, modeling, validation, and engineering decision-making. Topics covered: AI in CAD, AI in BIM, AEC software, digital twins, Rhino, Grasshopper, Revit, engineering workflows, AI coding, MCP, open standards, startup innovation, and the future of AI-native engineering tools.

Engineering’s Spatial AI Moment - Campfire & Gravity Sketch

What happens when AI, virtual reality, and spatial computing move beyond demos and start reshaping real engineering work? In this episode of AI Across the Product Lifecycle, Michael Finocchiaro speaks with Jay Wright, Co-Founder and CEO of Campfire, and Oluwaseyi “Shay” Sosanya, Co-Founder and CEO of Gravity Sketch, about the future of immersive engineering workflows. This is not a “metaverse” conversation. It is about what spatial tools can actually do for product development, design reviews, manufacturing validation, training, collaboration, and digital transformation. Jay explains why AI is becoming a first-class user inside Campfire, acting almost like another participant in a 3D workspace. Shay breaks down why Gravity Sketch keeps humans at the center of the design process while using AI to remove friction, speed iteration, and help teams communicate better. The conversation covers the hard parts too: why LLMs still struggle with geometry, why industrial companies remain cautious about cloud and AI adoption, why employees are already using AI tools outside official policy, and why the next breakthrough in engineering may not be AI replacing CAD, but AI controlling and accelerating the tools engineers already use. For anyone working in CAD, PLM, industrial AI, digital thread, manufacturing, design, or engineering software, this is a sharp look at where spatial computing is actually useful and where the hype still needs to become workflow value. Featuring: Jay Wright, Co-Founder & CEO, Campfire Oluwaseyi “Shay” Sosanya, Co-Founder & CEO, Gravity Sketch Host: Michael Finocchiaro, AI Across the Product Lifecycle Transcript source:   TIMELINE 00:00 Welcome and guest introductions 03:05 Jay Wright on being bullish about AI after ChatGPT 04:33 Shay Sosanya on cautious optimism and the speed of AI progress 07:06 Why 3D geometry is harder for AI than language 08:42 AI capabilities are moving faster than expected 10:07 How Gravity Sketch adopted AI in software development 12:27 Campfire’s AI-assisted development workflow 13:32 AI agents in meetings, code, and product workflows 16:11 Using AI with existing 3D assets, BOMs, documents, and legacy data 18:26 Campfire’s spatial workflows for engineering, training, and sales 20:02 Where AI sits in the software stack 20:28 Campfire’s spatial agent as a first-class user 21:46 Gravity Sketch’s human-first approach to AI in spatial design 23:36 Foundation models, 3D generation, and geometry engines 25:29 AI cost, IP protection, customer data, and bring-your-own-LLM models 28:00 Has engineering had its ChatGPT moment yet? 29:05 Why physical product development will see staged AI adoption 31:17 The engineering-to-manufacturing gap 32:13 Simulating manufacturing workflows before production 34:12 AI connectors, Blender, Fusion 360, and tool control 35:18 Advice for young engineers worried about AI 39:41 Making real products, not just AI-generated concepts 40:00 Digital maturity in industrial companies 41:21 Why many manufacturers remain at low digital maturity 42:31 Headsets, cloud, InfoSec, and adoption barriers 43:39 Employees are already using AI and immersive tools informally 46:57 Can agile startups move industrial customers faster than incumbents? 48:17 Campfire on solving workflows rather than selling AI novelty 50:29 Gravity Sketch on value, workflow depth, and avoiding AI hype 53:09 Where to see Campfire and Gravity Sketch next 56:12 Closing thoughts