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This new 28-page report explores how organizations can break free from the “gen AI paradox”—where widespread use of generative AI has yet to produce measurable business results. At the core of this paradox is a mismatch between horizontal tools like enterprise-wide copilots and chatbots—which are easy to scale but deliver diffuse, hard-to-track gains—and vertical use cases embedded in specific business functions, which offer more transformative potential but are rarely deployed beyond pilot phases. To unlock real value, the authors argue that organizations must shift to agentic AI: proactive agents that autonomously execute workflows and drive outcomes. But success requires more than layering agents onto old processes—it demands rethinking how work gets done and designing workflows with agents at the core. While the report contains numerous insights, one visual that stands out is Figure 4, which illustrates how a retail bank reimagined the creation of credit-risk memos. Relationship managers (RMs) had been spending weeks manually drafting memos using data from ten sources. In the agentic model, AI agents now extract data, draft sections, generate confidence scores, and propose follow-up questions—shifting the RM’s role to strategic oversight. The result: a potential 20–60% boost in productivity, including a 30% faster credit turnaround. As organizations envision the potential impact of AI agents on core workflows, the visual is a useful framework for presenting the before-and-after picture. As a bonus, here is Stanford University’s 2025 Artificial Intelligence Index Report, which includes 457 pages on various aspects of AI.
