Real-world AI use cases
Find out where AI is delivering value today
Explore nine AI use cases that companies are already using to drive results. Then apply the skills and tech to move from experimentation to execution.
Yes, I want AI use cases I can put into practice
Over 80% of AI projects will fail.1 Make sure yours don’t.
Build the expertise your teams need to turn AI opportunities into measurable outcomes.
1. Forecasting
Anticipate demand, sales trends, and business risks with greater accuracy.
2. Data synthesis
Transform disconnected data into clear, actionable insights.
3. Internal knowledge graphs
Surface the right information at the right time across your organization.
4. Content generation
Scale content creation while maintaining quality, consistency, and speed.
5. Automation
Free up teams from manual work so they can focus on higher-value initiatives.
6. Developer productivity
Accelerate coding, testing, and troubleshooting across the development lifecycle.
7. Customer service
Deliver faster, more personalized support that improves client satisfaction.
8. Cybersecurity and threat detection
Strengthen defenses by identifying threats or breaches before they escalate.
9. Personalization
Create more relevant experiences based on individual needs, behaviors, and preferences.
1RAND, The Root Causes of Failure for Artificial Intelligence Projects and How They Can Succeed (2024)
Real companies. Proven outcomes. Practical guidance.
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