From AI Hype to Hard ROI: Scaling What Actually Works
AI adoption has surged, but execution is lagging. According to McKinsey & Company, while over 70% of organizations report using AI in some capacity, fewer than 20% have successfully scaled it across the enterprise. At the same time, Gartner predicts that by 2026, over 80% of AI projects will fail to deliver expected value without proper governance and operational alignment. Executives are facing mounting pressure to prove ROI while navigating fragmented data, unclear ownership, rising costs, and a growing disconnect between experimentation and real business impact.
Leading organizations are shifting their focus from tools to transformation. This means building strong data foundations, embedding governance and accountability from the outset, and aligning AI initiatives to measurable business outcomes. It also requires rethinking operating models—integrating AI into core workflows, enabling cross-functional collaboration, and preparing the workforce for a future where humans and intelligent systems work side by side. Those making progress are not just deploying AI—they are operationalizing it with discipline, clarity, and purpose.
Previous Speakers Include:
Lambert Hogenhout
Queena Cheung
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