AI is transforming Digital Asset Management (DAM) and marketing, but enterprise-wide adoption remains low. Only 8% of organizations have integrated AI comprehensively, with common challenges including high costs, security concerns, inconsistent output quality, and a shortage of skilled personnel. Predictions indicate that the divide between organizations successfully using AI and those lagging behind will continue to widen. Although concerns related to data, bias, and accuracy are improving, they are still significant hurdles for many enterprises in realizing the full potential of AI.
AI adoption remains notably slow despite the perception of widespread use, with only 8% of enterprises achieving organization-wide adoption and less than 20% reporting revenue increases.
Concerns regarding data, bias, and accuracy are significant barriers to AI adoption, compounded by high costs, lengthy implementation times, and a lack of skilled resources.
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