Production AI success: From gen AI promise to business impact

Production AI success: From gen AI promise to business impact 1. Defining a strategic path and clear business value for AI 2. Addressing the AI talent gap 3. Establishing a robust and scalable AI infrastructure 4. Addressing AI risks and regulatory compliance 5. Cultivating executive sponsorship 6. Overcoming employee reluctance Building a foundation for AI success Get started with AI for enterprise: A beginner’s guide About the author Brian Stevens More like this Blog post Blog post Blog post Keep exploring Browse by channel Automation Artificial intelligence Open hybrid cloud Security Edge computing Infrastructure Applications Virtualization Share Generative AI (gen AI) has the potential to significantly improve customer engagement, reduce costs, and boost productivity. However, many enterprises struggle to move beyond initial experiments to widespread and scalable implementations. This article examines 6 common obstacles to enterprise AI adoption —as highlighted in this Harvard Business Review report —and how Red Hat can help you overcome them. Many organizations initiate gen AI projects without a defined strategy or roadmap. This can lead to fragmented efforts that make it difficult to demonstrate a return on investment (ROI). A well-articulated strategy is crucial for successful adoption.