Three enterprise giants, 48 hours, one admission: the AI model is no longer the product.

In this EdgeBytes, Mark Vigoroso decodes back-to-back announcements from SAP, Infor, and Workday through one stubborn number: 40% of large companies are now scaling AI agents, up from 27% a year ago, yet the share seeing any profit impact is stuck near 37%. More push, same speed, so where's the drag?

• SAP is replacing its own screens before a rival can, growing cloud ERP 25% while its stock trades at roughly half of Morningstar's fair value.
• Infor took the consumption meter off the wall.
• Workday found that demand for basic prompting skills has already dropped 25%.

In fifteen minutes you get a prognosis for each vendor and a playbook for CEOs, CFOs, and CIOs. The models are equal now; what your systems know, who answers for the outcome, and how little you drag along will decide who gets paid. Stream this vlog now and be sure to LIKE, SHARE and COMMENT!

Those things we swore we'd never do again after the cloud computing migration? Fact is, we are repeating some of those same missteps now in the agentic AI era.

In this episode of the Enterprise Edge® Podcast, Mark Vigoroso sits down with Sujata Joshi, Director of SolutionDelivery at Cisco, and Sridhar Balasubramanian, VP of Data and AI at CloudPaths, to name mistakes like lift-and-shift, reborn as AI agents bolted onto broken processes.

The stakes are real, with a Barclays survey showing 86% of CIOs plan to pull workloads back off the public cloud and Gartner predicting 40% of enterprises will cancel or demote autonomous agents by 2027. The two enterprise tech veterans in our studio lay out what to do instead:

• Pilot on your ugliest data, not your happy path.
• Stop driving a Ferrari through rush-hour traffic when plain automation will do.
• Keep agents out of requirements discovery until the tribal knowledge is written down.
• Replace the change advisory board (CAB), already dead at 50 changes an hour, with automated guardrails.

Our guests’ verdict: the bottleneck is no longer capability but governance, and the payoff is revenue, not just productivity. The one cloud-era move worth copying outright is a shared responsibility model put in writing before the incident, "so that when something burns, there is an artifact to point to instead of an argument."

Stream this practical episode now - before your next AI agent goes live - and be sure to LIKE, SHARE, and COMMENT!

Most AI stories end at the pilot. This one is unfolding on a P&L. On this special episode of The Enterprise Edge® podcast - produced in partnership with QAD | Redzone - Mark Vigoroso sits down with Kevin Davis, VP of Finance at AmSafe - the 500-person TransDigm company whose restraints are onvirtually every major airline on earth.

Davis applies a much-needed and well-timed evidentiary standard to enterprise AI. He explains the hard bar AmSafe set - no project advances unless it strips 40–60% of the transactional activity out of a process - then produces the receipts: sales order entry now absorbs the same volume with 20–30% fewer people, daily cash posting fell from 3-4 hours to under one, and not one agent has been given access to the bank account.

You'll hear exactly how he funded it with CapEx approved with committed savings attached, released in phases against fixed-firm bids, and how he walked internal and external auditors through agentic workflows before go-live under AS9100, FAA Part 145, and SOX. Davis also leaves us with the one thing he'd do differently, and it has nothing to do with technology!

Stream this episode now and be sure to LIKE, SHARE and COMMENT! And grab Kevin for a 1:1 deep dive at QAD's Champions of Manufacturing, Chicago, September 21–23!

How much room does finance actually have for AI to be wrong? That question sits at the center of this Enterprise Edge podcast conversation with Georg Glantschnig, Corporate Vice President for Agentic ERP at Microsoft Dynamics 365. (Spoiler: answer is “little to none.”)

The Enterprise Edge CEO and Founder, Mark Vigoroso leads a discussion that digs into a sharp asymmetry: people forgive a colleague's mistake but not an algorithm's - and in finance, where the numbers are binary and every posting needs a trace, that asymmetry drives real architecture decisions.

You'll hear how guardrails get built from deterministic business logic and company policy rather than left to chance, why accountability never actually shifts onto the agent itself, and how a move from code-first to model-first design is reshaping what an ERP system even is.

There's also a clear-eyed look at the messy economics of consumption-based pricing replacing seat licenses, why month-end close could be the proving ground for continuous-close finance, and what emerging roles like "finance agentorchestrator" suggest about where accounting work is headed.

For anyone trying to separate real operational leverage from AI hype in enterprise systems, stream this episode now and be sure to LIKE, SHARE and COMMENT!

"Three years ago... our success metric was OTIF. Andtoday it's the in-stock. It was a metric known by probably one or two people - I didn't know about it. And today we had our monthly tissue sector reunion, and we mentioned that our in-stock improved by 2%. Everybody was applauding. It's the first time anybody applauded for in-stock results." -- Xavier Duprat, VP, Supply Chain Planning & Fulfillment, Cascades.

Full podcast episode, "Autonomous Decisions at Scale:Making AI Work in the Real World" - https://open.spotify.com/episode/2PmaO3Swf84UXAWSj8yXaE?si=eab7ad0af0e940aa

A DEMO of Supply Chain Planning Reimagined in action!: https://events.sap.com/tee-supply-chain-planning-reimagined/en_us/home.html

Every enterprise leader is chasing their first AI win - but almost nobody is asking what it costs to run that win at scale, every day, forever.

On this episode of The Enterprise Edge podcast, Red Hat Chief Product Officer, Ashesh Badani joins us a month removed from Red Hat Summit 2026 in Atlanta to make the case that "token economics" isn't a buzzword - it's the next architectural decision CIOs can't afford to make too late.

Badani, who watched Sun Microsystems lose its biggest bet to the very open-source wave Red Hat later rode to the top, brings two decades of pattern recognition to a conversation that ranges from...

-- why Red Hat acquired Neural Magic and bet on vLLM for inference efficiency...

-- to the honest tradeoffs between proprietary frontier models and open infrastructure...

-- to the one question from a customer that still catches him off guard.

It's a rare, unscripted look at how the company that helped define open source for the last era is now trying to define what governable, economically sustainable AI looks like for this one - straight from the product chief writing the playbook.

Stream it now and be sure to LIKE, SHARE and COMMENT!

“If you build enough confidence that you say, 99% of the time, this is right - and you want to say, let's just have it go automatically - that's the goal. People will build that trust over time and you will become more autonomous...” -- Joel Beal, CEO & Co-Founder at Alloy.ai. Full podcast episode, "Autonomous Decisions at Scale: Making AI Work in the Real World"GET A DEMO of Supply Chain Planning Reimagined in action!: https://lnkd.in/eXqZBrFh

What happens when the autopilot turns on, and a supply chain planner can't explain why it made the call it just made? In this episode of Supply Chain Planning Reimagined – brought to you by The Enterprise Edge® in partnership with SAP - Xavier Duprat, VP of Supply Chain Planning at Cascades, and Joel Beal, CEO of Alloy AI, get brutally honest about where autonomous supply chain decisions actually stand today: not in a sandbox, but across 10 North American tissue paper plants, 10,000 retail store locations, and a freshly launched replenishment agent that went live the week of this recording.

They unpack…

• why "on-time and in full (OTIF)" is the wrong metric to optimize for

• how a single in-stock KPI nobody knew three years ago is now getting a standing ovation in monthly leadership reviews

• why 15% forecast accuracy improvements are table stakes compared to what agentic AI is about to unlock

• why the real architectural question isn't monolithic vs. multi-agent - it's whether your organization has built enough trust to let go of the wheel.

If you're a supply chain leader navigating the gap between proof-of-concept and production-scale autonomy, this conversation is your roadmap.

Stream it now, and be sure to LIKE, SHARE, and COMMENT!

Get a demo of Supply Chain Planning Reimagined in action: https://events.sap.com/tee-supply-chain-planning-reimagined/en_us/home.html