The explosion of generative AI and advancements in multimodality, reasoning, and autonomous AI agents are transforming industries. However, a new MIT Technology Review Insights report underscores a critical bottleneck: data. The study, surveying 800 data and technology executives, found a significant gap between AI’s potential and organizations’ ability to manage the data fueling it. Alarmingly, only 2% of executives believe their AI strategies are delivering desired business results. The report highlights challenges in accessing timely data, maintaining data lineage, and navigating increasing security complexities. While a substantial number of organizations (two-thirds) have experimented with generative AI, widespread deployment is limited, with only 7% achieving broad adoption. This points to underlying difficulties in scaling AI initiatives due to data management hurdles. Produced by Insights, the custom content arm of MIT Technology Review, the full report offers a detailed analysis of these challenges and proposes strategies for organizations seeking to build high-performing AI infrastructures centered around robust data practices.
AI Success Hinges on Data: Study Reveals Widespread Struggles in Data Management
