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Software licensing used to be one of the most predictable parts of an engineering organization's technology budget. You bought licenses, planned annual maintenance, and forecasted costs years in advance. But as AI assistants, cloud platforms, token-based licensing, and API-driven workflows become the norm, that predictability is disappearing.
In this episode of Stay Sharp in Digital Engineering, co-hosts Juliann Grant and Jonathan Scott welcome back Paul Empringham, VP of CAD, Simulation, and PLM at NYBS Consulting, to explore how software licensing is evolving—and why engineering leaders need to start thinking differently about budgeting, governance, and AI consumption before costs spiral out of control.
Building on their previous discussion about traditional licensing models, Paul explains why the industry's move to cloud platforms and tokenized licensing creates both opportunities and new financial risks. As AI becomes embedded directly into CAD, PLM, and engineering applications, organizations will need better visibility into software usage, stronger governance, and new strategies for managing unpredictable consumption-based costs.
In this episode you'll learn:
Key Discussion Topics
The shift to cloud-first engineering software
Software vendors are rapidly moving customers away from on-premises installations and toward cloud platforms. While this simplifies upgrades and accelerates feature delivery, it also reduces customer visibility into actual software usage.
Understanding tokenization
Paul explains the growing trend toward token pools, where engineering teams consume tokens for advanced capabilities across multiple software products instead of purchasing individual specialty licenses. This provides greater flexibility—but also introduces new complexity.
AI changes everything
As AI assistants become embedded inside CAD, PLM, and simulation tools, companies may soon be paying for both software licenses and AI consumption. Unlike traditional licensing, AI usage can fluctuate dramatically, making annual budgeting far less predictable.
Managing the unknown
Engineering organizations need better data than ever before. Understanding who uses which tools, how often they use them, and where AI is being adopted will become essential for controlling costs and preparing for future licensing changes.
Memorable Quote
"For the first time in our lives, I don't think we can predict what our software is going to cost us."
Featured Guest
Paul Empringham
Vice President of CAD, Simulation & PLM
NYBS Consulting
Paul specializes in engineering software licensing, optimization, and governance for global manufacturing organizations. He has helped companies maximize software investments while navigating increasingly complex licensing models across the CAD, PLM, and simulation landscape.
Music is considered “royalty-free” and discovered on Story Blocks.
Technical Podcast Support by Jon Keur at Wayfare Recording Co.
© 2026 Razorleaf Corp. All Rights Reserved.
By Razorleaf Corp.Software licensing used to be one of the most predictable parts of an engineering organization's technology budget. You bought licenses, planned annual maintenance, and forecasted costs years in advance. But as AI assistants, cloud platforms, token-based licensing, and API-driven workflows become the norm, that predictability is disappearing.
In this episode of Stay Sharp in Digital Engineering, co-hosts Juliann Grant and Jonathan Scott welcome back Paul Empringham, VP of CAD, Simulation, and PLM at NYBS Consulting, to explore how software licensing is evolving—and why engineering leaders need to start thinking differently about budgeting, governance, and AI consumption before costs spiral out of control.
Building on their previous discussion about traditional licensing models, Paul explains why the industry's move to cloud platforms and tokenized licensing creates both opportunities and new financial risks. As AI becomes embedded directly into CAD, PLM, and engineering applications, organizations will need better visibility into software usage, stronger governance, and new strategies for managing unpredictable consumption-based costs.
In this episode you'll learn:
Key Discussion Topics
The shift to cloud-first engineering software
Software vendors are rapidly moving customers away from on-premises installations and toward cloud platforms. While this simplifies upgrades and accelerates feature delivery, it also reduces customer visibility into actual software usage.
Understanding tokenization
Paul explains the growing trend toward token pools, where engineering teams consume tokens for advanced capabilities across multiple software products instead of purchasing individual specialty licenses. This provides greater flexibility—but also introduces new complexity.
AI changes everything
As AI assistants become embedded inside CAD, PLM, and simulation tools, companies may soon be paying for both software licenses and AI consumption. Unlike traditional licensing, AI usage can fluctuate dramatically, making annual budgeting far less predictable.
Managing the unknown
Engineering organizations need better data than ever before. Understanding who uses which tools, how often they use them, and where AI is being adopted will become essential for controlling costs and preparing for future licensing changes.
Memorable Quote
"For the first time in our lives, I don't think we can predict what our software is going to cost us."
Featured Guest
Paul Empringham
Vice President of CAD, Simulation & PLM
NYBS Consulting
Paul specializes in engineering software licensing, optimization, and governance for global manufacturing organizations. He has helped companies maximize software investments while navigating increasingly complex licensing models across the CAD, PLM, and simulation landscape.
Music is considered “royalty-free” and discovered on Story Blocks.
Technical Podcast Support by Jon Keur at Wayfare Recording Co.
© 2026 Razorleaf Corp. All Rights Reserved.