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Case studyAI platforms — data science & MLRoche
ThoughtSpot Blog · Read source ↗

At the Agentic Analytics Playbook event in London, Yannick Misteli from Roche highlighted a key reason AI pilots often fail: the lack of addressing 'day after' questions. These are the practical considerations that arise once a pilot is operational, beyond initial technology or budget concerns.

MyDataWork POV — Roche's insight into AI pilot failures is a wake-up call for data teams. It's not the tech or the budget that trips us up—it's the mundane, post-launch realities. Misteli's focus on 'day after' questions is a reminder that operationalizing AI requires more than a flashy pilot. It's about preparing for the everyday grind of maintenance and iteration. This is a message for those ready to move beyond the pilot phase, not for those still dazzled by initial AI promises.
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Agent Studio can help teams like Roche's by providing a structured way to scope and define agentic use cases before they hit the 'day after' phase. By using the five-step flow to plan and document, teams can better anticipate and address post-launch challenges. Explore MyDataWork ↗
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