Traditional backup systems often rely on fixed schedules and predefined rules for data protection, which may not be optimal for ever-changing business environments. AI and ML algorithms, on the other hand, can dynamically adjust the backup frequency and prioritise critical data based on real-time usage patterns. This adaptability ensures that important information is backed up more frequently while reducing the load on the infrastructure during periods of low activity.
AI and ML technologies have made it possible to identify and eliminate duplicate data more effectively while optimising how data is compressed and stored. As a result, organisations can now store their data more efficiently, saving valuable storage space and reducing overall backup times. Redundant data is intelligently identified and stored more efficiently, reducing storage costs and improving overall backup performance. This level of data optimisation is especially beneficial for organizations with massive data sets, enabling them to save both time and money while ensuring the highest level of data protection.
One notable benefit of employing AI and ML in data backup is their capacity to proactively recognise and minimize potential risks of data loss, preempting their occurrence. Through the analysis of historical data patterns and the projection of forthcoming trends, these technologies can take a proactive approach in recognising susceptible areas and initiating preventive measures against data loss.
Furthermore, these technologies offer the advantage of automating mundane backup tasks, thereby freeing up IT personnel to concentrate on more strategic endeavours. AI and ML can also improve the speed and accuracy of data recovery, reducing downtime and minimising the impact of data loss on business operations.
See also: Why knowledge graphs are crucial for agentic AI
The Singapore government is driving a coordinated society-wide approach to deepening Singapore’s generative AI capabilities across the private and public sectors to advance Singapore’s position as an open and trusted global AI hub through the National AI Strategy. As a region, Singapore is working with other Asean nations to come up with a set of guidelines on the responsible use of artificial intelligence (AI) in the region, which will be released in early 2024. The Asean Guide on AI Governance and Ethics will serve as a practical and implementable step to support the trusted deployment of responsible and innovative AI technologies in the region.
The adoption of AI and ML in data backup is experiencing significant growth in the Southeast Asia region, and this trend brings promising prospects for businesses in the area. As industries across Southeast Asia continue to embrace digital transformation, there has been an exponential increase in data generation, making efficient data backup and recovery strategies more crucial than ever. Recognising the advantages of AI and ML in safeguarding their valuable information, businesses are eagerly adopting these technologies to optimise their backup processes.
In conclusion, the rise of AI and ML in data backup has marked a turning point in the field of data resilience. As businesses continue to navigate the challenges posed by increasing data volumes, these technologies provide a smarter, more automated, and adaptive approach to safeguarding critical information. Embracing AI- and ML-powered backup solutions can empower organisations to stay ahead in an ever-evolving data landscape, reinforcing their ability to recover swiftly from any data-related incidents and secure sustained success in their operations.
Manikandan Thangaraj is the vice president at ManageEngine
