GenAI, Supply Chains and All of the Hype

If you follow Gartner research, you probably have read or seen the Hype Cycles. 

They cover a wide range of emerging technologies, methodologies and strategies. These follow an arc beginning with an Innovation Trigger, leading to the Peak of Inflated Expectations and then falling into the Trough of Disillusionment. After this roller coaster ride, if the trend survives, it will slowly climb the Slope of Enlightenment and finally reach the Plateau of Productivity.

These journeys can last a few years to more than 10.

Not only do chief supply chain officers face the challenge of picking the most appropriate technologies and strategies, but they also need to get the timing right. This becomes increasingly important when dealing with an emerging innovation such as generative AI.

Many technologies that burst on the scene make a huge splash in the media. CSCOs are intrigued, and boards want to know how this new stuff can bring positive financial outcomes to the enterprise, and they want it now.

Remember blockchains?

They represented a groundbreaking technology that underpins cryptocurrencies and was forecasted to revolutionize parts of the supply chain. The technology was launched in January 2009 (aka a long time ago), and I was writing about its potential transformative impact in early 2017. Back then, Gartner predicted (using a Hype Cycle) that it was more than 10 years away from being widely adopted. As of 17 July, the newly published Hype Cycle for Supply Chain Strategy, 2024 (subscription required) places the technology in the Trough of Disillusionment with another five to 10 years before reaching productivity. 

Today, CSCOs are looking for valuable use cases from across industries where GenAI can increase productivity and profits. So, what is the timing for this, according to that new supply chain strategy Hype Cycle, which also covers AI? Overall, the technology is at the Peak of Inflated Expectations. But here is where the story changes. Reaching productivity in supply chain is forecasted five to 10 years out. But, more generally, it’s closer to two to five years away from the Plateau of Productivity.

We should remind ourselves that the first widely used GenAI model was ChatGPT 3.5, released in November 2022, nearly two years ago. The cycle seems much faster from the Innovation Trigger to the Peak. But the hard work begins as we slide into the Trough of Disillusionment.

My colleague and Distinguished VP Analyst Noha Tohamy, who produced this new Hype Cycle, has a few things to point out:

• Hype and unrealistic expectations of GenAI far surpass its track record of generating scalable benefits. Supply chain leaders, for example, are super eager for GenAI to contribute directly to headcount reduction in the next two years, a use case that is unlikely to materialize.
• Supply chain is often at a disadvantage in competing with other enterprise functions and technology companies for AI experts and data scientists.
• There is a lack of clarity on how GenAI solutions will fit in the current technology footprint.
• Data security, intellectual property (IP) leakage and ethical use concerns, while not top of mind in the piloting phases, will invariably slow down broader adoption — especially in use cases that extend to external trading partners.

In our 2025 CSCO outlook survey, we asked our community for their thoughts on GenAI and their optimism about next year. Of those respondents, 80% say they are optimistic overall. And when it comes to GenAI, most say that we haven’t yet reached the Peak of Hype. About 60% say they have identified valuable use cases for the technology. But here comes the sticky part. The majority say they are more than half a year away from delivering significant value, and it won’t impact a substantial portion of the cost of goods sold.

It may seem like there's some skepticism around the use of GenAI in the supply chain, but that's not entirely true. It's important to remember that the adoption and effective utilization of most new technologies often take longer than initially expected. While the journey to achieving widespread, productive use of GenAI might progress relatively quickly, it's still a process that will span years, not just months.

Wade L. McDaniel
VP Distinguished Advisor
Gartner Supply Chain
Wade.Mcdaniel@gartner.com

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