Bridging the hidden gap between data and decisions in the age of AI
Why strong data operations unlock real AI outcomes
· TechRadarOpinion By Justin Rice published 21 December 2025
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Everywhere you turn, the conversation about AI includes the same message: success depends on good data. It’s become the mantra of every boardroom and conference stage.
Companies invest millions in cleaning, tagging, and organizing data with the belief that once it’s right, AI transformation will follow.
But that belief is incomplete. Cleaning and collecting data is step zero. Without the engineering, architecture, and operational readiness to use it, even the cleanest data set won’t move the business forward.
Most companies are trying to cross the finish line without actually building the car.
Justin Rice
Chief Product & Technology Officer, CBTS.
A Gartner survey found that 63% of organizations either don’t have or are unsure if they have the right data management practices for AI.
But even if companies don’t know where to start to get from data to AI transformation, there’s a straightforward strategy that any organization can use to produce business outcomes.
Why progress stalls at step zero
Progress stalls when there’s a gap between any of the layers between data and activation — strategy, engineering, modernization, visualization, and readiness. Some organizations write an ambitious data strategy that never links to measurable business outcomes.
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