Appen’s 2024 State of AI Report reveals that while generative AI adoption has surged by 17%, companies face significant challenges in data quality and management, VentureBeat writes. The report, based on a survey of over 500 U.S. IT decision-makers, indicates a 10% increase in bottlenecks related to data sourcing, cleaning, and labeling. As AI models become more complex, the need for high-quality, tailored data has intensified, leading to a decline in the deployment and ROI of AI projects. Data accuracy has dropped nearly 9% since 2021, with 86% of companies retraining their models quarterly, complicating the maintenance of data quality.
The report highlights a worsening situation regarding data bottlenecks and emphasizes the necessity for strategic partnerships with data providers. Additionally, it underscores the vital role of human involvement in AI development, with 80% of respondents recognizing the importance of human-in-the-loop processes to ensure ethical and effective AI systems. Experts are key for mitigating bias and refining AI outputs, particularly in generative AI, where unpredictability poses unique challenges.
