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 SSOT vs. SVOT: The critical difference companies get wrong

SSOT vs. SVOT: The critical difference companies get wrong

By: Suhas Sreedhar and Peter Nilsson | 8 min read

How do you establish and maintain a single version of truth across our enterprise and our suppliers when the underlying systems, ownership, and data change? That question tends to reveal much more about whether you’re buying a system of record versus a functioning network.

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Article Why People, Process, and Technology isn’t fixing your problems

Why “People, Process, and Technology” isn’t fixing your problems

By: Suhas Sreedhar | 5 min read

If you’ve spent any amount of time around digital transformation, change management, consulting, or enterprise software, you’ve probably heard the phrase “people, process, and technology” more times than you can count. The framework has become so common that it is often treated as a checklist. Need to improve performance? Buy a new technology. Then adjust the process and train the people. The problem is that it rarely works that way. In fact, I would argue that one of the reasons so many transformation initiatives struggle is because people have misunderstood what “people, process, and technology” was supposed to mean in the first place. The framework is often presented as three separate buckets that need to be addressed. The reality is that they are interconnected. Change one, and you inevitably impact the others.

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