How AI Stacks are Rewriting the Rules of Business

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Breaking Analysis with Dave Vellante 1h 0m 2 speakers 7 chapters transcribed 1 month ago

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How did the shift from on‑prem to SaaS change enterprise technology and operating models?

Dave Vellante 0:00

The shift from on-prem to SaaS changed the technology, business, and operating models for IT, but it largely stopped there. Enterprises, they gained the ability, uh or they gained agility and and they had less friction coming from their IT departments. But how companies actually made money in the way they operated day to day, that really didn't change. I mean it stayed fundamentally intact. Now SaaS companies, you know, themselves uh are the were the obvious exception, but the big changes really only affected technology vendors, not the buyers. AI will be completely different in this regard in our view. So this isn't just a technology change. The way organizations operate, the way they allocate capital, and the way they generate revenue is being altered in ways that will permanently reshape how business works.

Dave Vellante 0:53

The core problem today is one that most executives can probably describe, but few have solved. This is the fact that organizations are running in silos. And you think about it, each department has its own applications, its own data models, its business logic is trapped inside of those applications. And, you know, most of these work reasonably well for that department, but that's in isolation. What remains elusive is a single version of the truth across the enterprise. Let's face it, people still spend enormous amounts of time reconciling data, chasing down tribal knowledge, and manually translating insight into action. That's not an IT problem. That is an organizational tax. AI's promise is to eliminate much, if not most, of that tax and deliver dramatically higher productivity and the ability to scale without proportional labor growth.

Dave Vellante 1:49

But unlike SaaS, the effect won't be contained to just the technology department or technology vendors. These changes will permeate permeate the entire organization. for the technology buyers across all industries, across all departments. So our view is that The enterprises that get this right will become significantly more efficient, yet they'll also become platform companies. They're generating network effects that create winner-take most dynamics and much more sustainable economic advantage. In this breaking analysis, we preview the mental model that George Gilbert has developed to describe exactly how this transformation unfolds, and we set up for a deeper dive, a network. Next week's breaking analysis, George Gilbert, welcome.

Dave Vellante 2:36

Good to see you, Dave. Okay. Alex, please bring up the the first slide. We're we talk a lot about bringing together the worlds of determinism, deterministic software, and probabilistic software, you know, generative AI is probabilistic, bringing those two worlds together so that agents can act confidently. The fact is today's deterministic software, as we show in this slide that was developed by David Floyer on the left hand side, it's a jungle of applications. You see the ERP systems, the CRM, the the Salesforce, the the A the HCM, et cetera. And of course importantly the historical system of analytics, which is just that. It's it's it's a separated system. And we spend a lot of time as we set up front.

Dave Vellante 3:25

Just reconciling that with humans, just the human glue here, this the sort of expert interpretation, the tribal knowledge. There are a number of sort of terms for that. And this all results in in problems for the business. You've got conflicting rules. You've got different you know, guidance from different managers, you got a delayed truth. It takes a long time for for for corporate edicts to trickle down throughout the organization. a lot of the recovery tends to be manual. So, so so George, pick it up from there. This is the fundamental myth of determinism. And what we want to get to is a truly deterministic system that also has intelligence. Your thoughts.

George Gilbert 4:06

Yeah, you know, this platform um um or this this slide that David Floyer put together about how we have um about how we have These islands of applications, it's really profound because, like you and I have talked a lot in the past about these islands of operational activity that the applications correspond to.