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- تاريخ الإنشاء 10 نوفمبر 2026
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Turning AI Hype into Business Value
Turning AI Hype into Business Value: A Practical Guide to Identifying, Prioritizing, and Scaling AI Use Cases
Artificial intelligence (AI) adoption is accelerating across nearly every industry. What remains difficult is turning that adoption into measurable business value.
Over the past two years, several major industry studies have reported similar findings. AI usage inside organizations keeps climbing: one recent global survey found that 88% of companies now use AI regularly in at least one business function, up from 78% a year earlier. Yet only a relatively small share
can point to meaningful financial outcomes: just 39% reported an actual EBIT impact (earnings before interest and taxes), and for most of them it came to less than 5% of EBIT [9]. Many organizations launch pilots, experiment with new tools, and train employees on AI platforms, but far fewer translate
those activities into revenue growth, cost reduction, productivity gains, improved customer experience, or new business models.
The difference rarely comes down to model selection.
The organizations that consistently generate value from AI tend to focus on business problems before
technology decisions. They identify opportunities carefully, prioritize them systematically, redesign
workflows where necessary, and actively involve business leaders in governance and implementation. In
contrast, less successful initiatives often begin with technology and then search for a problem to solve.
This guideline "Turning AI Hype into Business Value: A Practical Guide to Identifying, Prioritizing, and Scaling AI Use Cases" brings together insights from public research and practitioner frameworks on how organizations identify, prioritize, and scale AI use cases.
The goal is not to explain how AI works. Instead, it focuses on a more important question for business
leaders:
How do you identify AI use cases that are worth pursuing and likely to create measurable value?
The paper provides a practical framework for:
- Understanding what constitutes a strong AI use case
- Assessing organizational readiness
- Discovering opportunities across the business
- Evaluating and prioritizing use cases
- Establishing governance and stakeholder involvement
- Avoiding common failure patterns
- Moving from idea to pilot and ultimately to production
For organizations that are still early in their AI journey, it also proposes a practical 90-day roadmap to help move from experimentation toward repeatable value creation.
Click on the "Download" button to receive the free guideline.