Enterprise AI Success at Scale: Why Execution Beats Experimentation

Gartner's 2026 analysis found that by the end of 2025, at least 50% of generative AI projects were abandoned after proof of concept. McKinsey confirmed that nearly two-thirds of organizations still had not begun scaling AI across the enterprise. BCG found that only 5% of firms were seeing material value despite significant investment.

The pattern is clear: the bottleneck is not access to models. It is the data foundation, governance, operating discipline, and deployment architecture required to turn pilots into repeatable business value.

Our new report, Enterprise AI Success at Scale, integrates current research from Gartner, McKinsey, BCG, Deloitte, EY, PwC, and MIT with IBM's recent AI and infrastructure developments. It evaluates how a unified, open operating model can improve enterprise AI execution, governance, and time to value.

Key areas explored include: why an open AI operating model reduces dependency risk while improving execution; how IBM Fusion HCI, Content-Aware Storage, and watsonx address the production infrastructure gap; what separates organizations that scale AI from those stuck in pilot; and what a credible enterprise value case actually looks like.

Armando Arias, President and CEO of Li9 Technology Solutions, will present the findings live on Thursday, April 22, 2026 at 1:00 PM ET, followed by a Q&A session.