Survey: Lack of data automation inhibits AI maturity

The majority of organizations are struggling with their AI maturity due to a lack of automated data integration, broad trust in AI, and the right expertise. While 85% of organizations are using AI models for strategic insights, only 14% consider themselves advanced in AI capabilities. Key challenges include manual data processes, limited IT resources, and insufficient stakeholder education on AI benefits. To advance AI initiatives, organizations should automate their data pipeline, free up data scientists to focus on high-value models and insights, and educate stakeholders to increase trust in AI. Automation is essential for handling the volume of data necessary for building and running AI and ML models, improving data quality, and achieving buy-in from stakeholders.

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