AI Project: To fail or not to fail?

Based on this article by Constantinos Papantoniou posted on LinkedIn.

Despite massive global investment in AI, most organizations report minimal impact, as the majority of projects fail to reach production. This discrepancy is not a technology problem but a failure of delivery, rooted in issues like untrustworthy data, poor governance, and a lack of user adoption.

Common pitfalls include getting stuck in the pilot phase, fragmented accountability, and failing to manage organizational change. To overcome these challenges, success requires a programmatic approach that prioritizes business outcomes, treats data as a product, and builds in governance from the start.

Check out the article and the six points outlined..

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