Look Past Productivity to Get Real Value from AI

BCG's 2026 AI Radar survey finds that while 82% of CEOs are more optimistic about AI ROI than a year ago, only 6% of companies are seeing meaningful value measured in reduced costs and increased revenue. The core problem is that most organizations deploy AI to automate existing tasks rather than redesigning end-to-end processes, causing efficiency gains to be reabsorbed into unchanged cost structures and measured only in activity metrics rather than P&L impact. BCG estimates that AI-enabled transformations can reduce general and administrative costs by 25–35%, R&D costs by 20–30%, and sales and marketing costs by 15–35%—but only when companies prioritize a small number of high-impact initiatives and redesign operating models around AI-enabled decision making. Case examples include a global consumer company achieving €250 million in cost savings and 15–20% P&L efficiency gains through AI-redesigned marketing workflows, a food and beverage company cutting procurement costs by $500 million, and a technology company targeting ~30% reduction in operating expenses on a $15 billion cost base. The central thesis is that depth of transformation in fewer initiatives—not breadth of pilot deployment—is the differentiator between leaders and the majority of AI adopters.