The 8 numbers that explain what’s really happening with AI adoption

The 8 numbers that explain what’s really happening with AI adoption

There is no shortage of evidence that companies are adopting Artificial Intelligence (AI). Every quarter brings another survey showing that more organizations are experimenting with generative AI, putting models into production, giving employees access to copilots, or increasing their spending on the technology. At the same time, there is a growing body of evidence suggesting that the economic impact of all this activity remains much less significant than the level of investment would imply. Both observations can be true, and when the numbers are put side by side, the apparent contradiction becomes easier to understand. Therefore, a more useful way to think about the current state of enterprise AI is not to ask whether companies are adopting it. They clearly are. The more important question is whether companies are changing their operations quickly enough to turn widespread access to AI into any meaningful business outcomes.

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Is your product actually a solution, or is it a platform?

Is your product actually a solution, or is it a platform?

The software industry loves labels. Product. Solution. Platform. Network. Offering. They're often used interchangeably, but they don't necessarily mean the same thing. There isn't a universally accepted definition for these terms, but there are some widely accepted perspectives in the software industry worth taking into consideration when you develop your go-to-market messaging. More importantly, using the right terminology helps set the right expectations with your customers.

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9 AI-Native Supply Chain Planning trends reshaping the industry

9 AI-Native Supply Chain Planning trends reshaping the industry

AI-native supply chain planning is becoming a more visible part of the technology landscape. Over the past year, Alex Pradhan has spoken with a growing number of newer supply chain planning vendors and identified a number of characteristics and trends that distinguish AI-native platforms from traditional systems being retrofitted with AI.

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Article Data quality isn’t the answer either. So what is?

Data quality isn’t the answer either. So what is?

By: Avery Source | 5 min read

There seems to be a bit of a sobering up going on in the B2B technology space, where software vendors are increasingly changing their narrative to say that data quality is what really matters. After several years of telling us what AI could do, we're now being reminded that AI will only work as well as the data behind it. And while it is indeed true that AI will work much better with clean, quality data, I think that too is an oversimplification and, more importantly, not what anyone is actually looking for. The problem is that we skipped ahead one step. We became so focused on what AI could deliver that we forgot about the data required to make it work. But even if we now take a step back, clean up our data, make it accessible, and then go full force on AI again, we still haven't necessarily solved anything worth solving. We've simply improved one of the things that can help us solve the actual problem.

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Article Is your product actually a solution, or is it a platform?

Is your product actually a solution, or is it a platform?

By: Avery Source | 4 min read

The software industry loves labels. Product. Solution. Platform. Network. Offering. They're often used interchangeably, but they don't necessarily mean the same thing. There isn't a universally accepted definition for these terms, but there are some widely accepted perspectives in the software industry worth taking into consideration when you develop your go-to-market messaging. More importantly, using the right terminology helps set the right expectations with your customers.

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Article Supply Chain Control Tower market overview

Supply Chain Control Tower market overview

By: Avery Source | 3 min read

The supply chain control tower market has evolved well beyond traditional visibility dashboards. As reflected in both the Nucleus Research Control Tower Technology Value Matrix and Gartner's Supply Chain Planning research, leading solutions now differentiate themselves by their ability to combine end-to-end visibility with real-time collaboration, AI-driven decision support, scenario planning, and increasingly autonomous execution. Consistent with the five-level maturity model described in this article, the market leaders are those that move beyond siloed monitoring to provide network-wide orchestration, intelligent exception management, and closed-loop execution across suppliers, logistics providers, and enterprise systems.

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Article Digital Supply Chain Network

What a Digital Supply Chain Network actually is

By: Avery Source | 3 min read

People talk about digital supply chain networks a lot, usually as if everyone already agrees on what they are. In reality, most organizations don’t. And if you strip away the terminology, there’s still a fair amount of confusion about what problem they’re actually trying to solve.

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Article Healthcare doesn't have an AI problem. It has a data problem.

Healthcare doesn’t have an AI problem. It has a data problem.

By: Avery Source | 3 min read

Everyone is talking about how Artificial Intelligence (AI) will transform healthcare in America. I’m not convinced that’s actually the core issue. Before AI can do anything meaningful in healthcare, there’s a much more basic problem that still hasn’t really been solved.

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Article Why operational knowledge shouldn't live in a Spreadsheet

Why operational knowledge shouldn’t live in a Spreadsheet

By: Avery Source | 3 min read

Most manufacturing companies have at least one spreadsheet they would struggle to live without. You know the one. Perhaps it schedules production. Perhaps it allocates inventory. Perhaps it helps determine which orders get prioritized when capacity becomes constrained. Whatever its purpose, someone in the organization built it years ago, and over time it became an essential part of the business. To be fair, that's not necessarily a bad thing.

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