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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 difficulty in managing organizational change. She emphasized that the significant gap between making an AI-related decision and its successful implementation over a two-year period is the critical factor determining AI's success or failure within businesses. AI

IMPACT Enterprise AI adoption success is more dependent on organizational change management than on the AI models themselves.

RANK_REASON Opinion piece from an executive discussing enterprise AI 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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2 / 100
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Commentary
Opinion piece from an executive discussing enterprise AI challenges.
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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product, opinion
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Standard
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Breaking (< 6h)
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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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