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Dataiku executive: Enterprise AI success hinges on change management, not models

By PulseAugur Editorial · [1 sources] ·

Sophie Dionnet of Dataiku highlighted that the primary challenge for enterprise AI adoption is not the technology itself, but rather the extensive change management required. She emphasized the significant gap between making an AI decision and successfully implementing it, a process that can span up to two years. This implementation phase is critical for determining the ultimate success or failure of AI initiatives within organizations. AI

IMPACT Successful AI implementation in enterprises depends heavily on organizational change management, not just the underlying models.

RANK_REASON The item is an opinion piece from an executive at an AI-related company discussing enterprise AI adoption challenges.

Read on Mastodon — mastodon.social →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Dataiku executive: Enterprise AI success hinges on change management, not models

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The item is an opinion piece from an executive at an AI-related company discussing enterprise AI adoption challenges.
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COVERAGE [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    AI isn’t magic. In our conversation with Sophie Dionnet (Dataiku), she cuts to the real enterprise AI trap: not models, but change management. “Taking a decisio

    AI isn’t magic. In our conversation with Sophie Dionnet (Dataiku), she cuts to the real enterprise AI trap: not models, but change management. “Taking a decision is one hour, implementation is two years.” That gap is where AI succeeds or stalls. Watch on YouTube: https:// youtube…

    LINKS youtube.com/…/Rh2kZ4P_ib4

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