Scaling AI skills across global enterprises with AWS
The challenge:
AI is transforming industries at speed. For global enterprises, the real hurdle isn’t understanding its potential – it’s scaling practical skills across diverse teams without slowing innovation. Organisations needed more than theory. They wanted hands-on expertise to design and deploy AI solutions confidently, from technical specialists to strategic leaders.
The solution:
At QA, we partnered with Amazon Web Services (AWS) to deliver two targeted programmes: Generative AI Essentials on AWS and AWS Agentic AI Foundations.
- Generative AI Essentials on AWS introduced the principles of generative AI, ethical considerations, and AWS services such as Amazon Bedrock and SageMaker. Learners explored real-world use cases and built prototypes to enhance productivity and customer engagement.
- AWS Agentic AI Foundations focused on the next frontier – autonomous, goal-driven systems. Participants learned to design and deploy agentic architectures using AWS technologies, preparing them to lead innovation in this emerging space.
Both programmes combined conceptual learning with hands-on labs, enabling immediate application to live projects.
The result:
The impact was clear:
- Over 400 professionals trained across 50+ global organisations.
- AI concepts applied to projects in customer experience, process automation, and intelligent agent design.
- Cross-functional engagement strengthened collaboration between technical and strategic teams.
- Confidence in AWS tools grew, accelerating scalable AI adoption.
Feedback highlighted the value of blending theory with practical labs. Many participants reported the training sparked innovation and aligned teams with digital transformation goals.
“This programme exemplifies how AWS and QA can collaborate to drive real-world AI adoption. By combining foundational knowledge with practical application, we’ve empowered teams to take meaningful steps toward building AI intelligent systems.”
Chris Burr
EMEA Training Partner Manager at AWS
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