60 Percent of AI Projects Could Be Abandoned by 2026. The Problem Isn’t the Model
Powerful models cannot overcome fragmented information, unclear goals, or workflows that employees do not trust.
EXPERT OPINION BY STEVE SENSING, PRESIDENT OF SUPPLY CHAIN SOLUTIONS, RYDER SYSTEM, INC.
A year ago, it seemed like every conversation about AI revolved around the same questions: Which tools should we use? Which models are the most powerful? How quickly can we deploy them?
Now, after seeing firsthand the evolution of AI from experimentation to real-world impact across an expansive and complex supply chain and transportation network, I’m convinced they’re not the questions that will determine who wins.
The wins come from foundational work, not flashy
The wins come from foundational work, not flashy tools. The organizations creating the most value from AI are the ones doing the less exciting work—building strong foundations first, improving data quality, connecting information across systems, and embedding intelligence into everyday workflows.
That may not sound revolutionary, but it’s one reason many AI initiatives struggle to scale. The more successful implementations I’ve observed, the more I’ve realized that the competitive advantage doesn’t come from implementing AI alone. It comes from aligning people, processes, and data around a desired outcome.
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The real competitive advantage isn’t AI. It’s data
AI can only be as effective as the information behind it—a humbling lesson many leaders are learning firsthand.
According to Gartner, by the end of 2026, organizations will abandon 60 percent of AI projects because they are unsupported by AI-ready data. Gartner’s research also found that many organizations either lack confidence in their data management practices or aren’t sure whether their data is adequately prepared for AI use.
This reflects a common reality across industries.
Source: www.inc.com
