The rapid embrace of artificial intelligence (AI) is driving a paradigm shift in data generation, with projections indicating that storage requirements could potentially double over the next three years. This conclusion arises from a comprehensive global survey administered by Recon Analytics and underwritten by Seagate. The dominant themes are the aggressive growth of AI usage, the resultant explosion in data production, and an increased dependency on cloud-based storage solutions. Businesses now stand at a crossroads, where the choice of storage infrastructure becomes critical in harnessing the full potential of AI.
The survey revealed that a striking 72% of businesses are already leveraging AI, while an additional 28% plan to integrate it into their operations within the next three years. By 2024, 65% of AI-generated data will be stored in cloud environments, with forecasts suggesting an increase to 69% by 2028. Companies currently utilizing over 100 petabytes (PB) of storage often resort to saving AI training checkpoints in the cloud or a combination of hard drives and solid-state drives. This frequent checkpointing process significantly contributes to the soar in storage demands. Notably, 28% of companies save these checkpoints daily, while 43% do so on a weekly basis. This frequency underscores the crucial role that continuous data saving plays in refining AI models.
Importance of AI Training Data Retention
Another pivotal element highlighted by the survey is the emphasis on retaining AI training data over extended periods, with 90% of respondents indicating that this practice enhances model accuracy. Companies storing daily checkpoints reported that 32% preserve this data for more than 12 months, underscoring the significance of historical data in improving AI model performance. The prolonged retention of training data allows for better model tuning and incremental learning, leading to more reliable AI predictions and outcomes.
Security remains a top priority for these companies, as indicated by 25% of respondents, followed by storage capacity at 18%. Security concerns are tightly coupled with the need to protect sensitive AI-generated insights and intellectual property from unauthorized access and malicious attacks. Data management, computing resources, network capacity, and regulatory compliance also rank high among infrastructure priorities. This multifaceted approach ensures that AI operations remain secure, efficient, and compliant with industry standards.
Addressing the Burgeoning Storage Needs
To tackle the burgeoning storage demands, a substantial 61% of companies have adopted scalable cloud storage solutions. These solutions offer the flexibility to expand storage capacities as data volumes grow, ensuring that businesses can continuously accommodate the increasing influx of AI-generated data. Moreover, 56% of companies have implemented advanced data management software to streamline data handling processes, while 55% have upgraded their infrastructure to support the intensive requirements of AI operations. Data compression techniques are also employed by 49% of respondents to manage the rising volumes of data effectively.
Data replication emerged as another essential strategy for ensuring data integrity and availability, with 80% of respondents deeming it crucial for their AI strategies, particularly those managing storage capacities exceeding 100PB. By replicating data across multiple locations, companies can mitigate risks associated with data loss and ensure uninterrupted access to critical information. This practice becomes indispensable in maintaining the reliability and robustness of AI-driven operations.
Transition to Cloud Environments
The rapid adoption of artificial intelligence (AI) is creating a major shift in data production, with estimates suggesting storage needs might double over the next three years. This conclusion is based on a global survey by Recon Analytics, funded by Seagate. Key themes include the swift increase in AI use, the resulting surge in data generation, and a growing reliance on cloud storage solutions. Businesses face a critical decision regarding storage infrastructure to maximize AI’s potential.
The survey showed that 72% of businesses are already using AI, with another 28% planning to incorporate it within three years. By 2024, 65% of AI-generated data is expected to be stored in the cloud, with predictions of an increase to 69% by 2028. Companies using over 100 petabytes (PB) of storage often store AI training checkpoints in the cloud or a combination of hard drives and solid-state drives. Frequent checkpointing greatly contributes to rising storage demands. Notably, 28% of companies save checkpoints daily, while 43% do so weekly, highlighting the essential role of continuous data saving in improving AI models.
