As AI adoption accelerates across engineering organizations, the conversation is evolving. The question is no longer "What AI tools are available?" but rather "What problem are we trying to solve?"
At IBM AI Next: Build with Bob, we heard an insightful perspective from Ajay Jagtap, CIO of Sunshield Chemicals, on what makes AI adoption successful at scale.
His message was simple yet powerful: organizations should avoid starting with tools and instead begin by identifying the business or engineering challenge that needs to be addressed. Once the problem is clearly defined, the appropriate AI capabilities can be applied to create meaningful, measurable, and scalable outcomes.
This approach helps teams move beyond experimentation and focus on delivering real value. Whether the goal is improving developer productivity, accelerating modernization, enhancing testing, or streamlining operations, success depends on matching the right AI solution to the right challenge.
For technology leaders, the key question remains:
Are we selecting AI tools first, or are we defining the problem first?
The answer often determines whether AI becomes another tool in the stack or a true driver of transformation.
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