AI adoption is accelerating, but most initiatives fail to scale. Nearly 80% of AI projects stall before delivering business value. The causes are consistent. Poor data quality. Unclear processes. Architectural misalignment. Overstated vendor claims. AI does not fix these weaknesses. Instead, it amplifies them. Bad processes get worse. Bad data becomes operational risk. As a result, AI readiness has become a prerequisite—not an afterthought.

Meanwhile, vendors promise rapid AI transformation. They market copilots, autonomous workflows, and predictive insights. However, buyer readiness often lags behind these claims. Most organizations still lack data consistency and process clarity. Governance remains fragmented. Departmental expectations are misaligned. This gap creates failed pilots, stalled rollouts, and wasted investment. AI requires a new operating model. It demands redesigned processes, aligned architectures, and clear decision rights.

Finally, this webinar presents a practical AI-readiness framework for executives exploring AI initiatives. It introduces five foundational pillars across data, process, architecture, people, and governance. We contrast real-world AI success with common failure scenarios. We also outline what to demand from AI vendors and partners. The session concludes with a 12–24 month roadmap. The focus stays on measurable business value.

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