AIYING CaseLab #01
More AI. More Spending. But Where Is the Value?
THE CASE
An organization has spent the past year encouraging AI adoption.
Employees have access to AI tools.
Teams are experimenting.
Training sessions have been conducted.
Several AI pilots are running.
Management is now considering increasing the AI budget for the coming year.
But at the leadership meeting, the CFO asks a simple question:
“What measurable value have we actually created?”
The room becomes quiet.
Teams can show:
• number of AI users
• number of licenses
• number of pilots
• training participation
• examples of AI-generated work
But they struggle to show:
What became better because of AI?
This is not merely a hypothetical concern.
Gartner reported on September 1, 2026 that only 22% of organizations surveyed had successfully scaled AI across multiple business units or adopted an AI-first approach, even as 85% of functional leaders planned to increase AI spending in 2026.
So imagine you are advising this organization.
THE QUESTION
What should leadership do next?
A. Buy more powerful AI tools
B. Conduct more AI training
C. Require every employee to use AI
D. Stop measuring AI usage and start identifying specific workflows where AI can create measurable value
E. Something else?
What would you recommend — and why?
Share your answer in the comments.
Tomorrow: The AIYING Approach
AIYING CaseLab
Current Challenge → Judgment → Action → Value
AIYING — Accomplishing with AI
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Why this is a solid Case #1
The underlying challenge is strongly supported by multiple independent sources. Gartner's September 2026 research provides the freshest signal. (Gartner) ISACA's 2026 survey of more than 3,400 digital-trust professionals found that only 22% said AI ROI had met or exceeded expectations, while 23% said it was too early to tell and 22% didn't know the ROI. (ISACA)
Thomson Reuters adds another dimension: 74% of professionals now use AI several times a week, yet among professionals whose organization has a named AI strategy, 35% say everyday practice doesn't match that strategy. It also found a major value difference between organizations with and without an active AI strategy. (Thomson Reuters)
Even today's news reinforces the theme: reporting on India's 2026 enterprise AI maturity data says AI investment rose 119%, while only 22% of organizations surveyed had AI testing, auditing and risk-assessment processes in place. (Express Computer)
So the case is fictionalized/generalized, but the problem is real and current. I would keep it that way rather than inventing a named company or claiming the hypothetical numbers came from a real organization.
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