The skills gap that is stifling development in artificial intelligence (AI) is well documented, but another aspect stands out: data complexity. According to a new IBM study, the most common barriers to AI success are limited AI skills and knowledge (33%), followed by data complexity (25%).
The majority of companies (58%) that participated in the poll of 8,584 IT professionals said that they have not yet begun to actively adopt AI. At these non-AI-enabled companies, trust and transparency (43%) and data privacy (57%) are the biggest obstacles to generative AI.
Companies using AI typically face data-related challenges. Some are taking initiatives to ensure trustworthy AI, such as tracking data provenance (37%), and reducing bias (27%). Around one-quarter (24%) of businesses are looking to improve their business analytics or intelligence capabilities, which rely on reliable, high-quality data.
However, several industry leaders warn that organisational data may not be ready to support burgeoning AI ambitions. “To remain competitive, CIOs and technology leaders must adapt their data strategies as
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