Using AI to transform government data management

Roland Rosenau at Quantum describes how governmental bodies, handicapped with low budgets, can use AI to turn their unstructured data into actionable benefits for their communities

 

In a recent speech, Rishi Sunak predicted that AI would bring “a transformation as far reaching as the Industrial Revolution”. However, today’s government agencies currently find themselves grappling with the challenge of how best to put this revolutionary technology to work.

 

On the one hand, AI and analytics have the potential to generate significant benefits: everything from enhanced decision making to smart workflows that generate operational efficiencies and seamless interactions for citizens. On the other, capturing this value depends on being able to manage complex data management tasks more efficiently while still protecting sensitive data.

 

No easy feat when data volumes are growing exponentially. This opens the door to significant risks and complexities that include escalating data storage costs, potential security vulnerabilities, and difficulties maintaining data compliance and governance.

 

To realise the vision of a data-driven government where data informs every decision, interaction, and process, government organisations will need to adopt new AI-powered capabilities that enable new ways of making data accessible and unlocking its value. 

 

Dealing with the data storage dilemma

Today’s government organisations are generating, storing, and analysing more data than ever before. Increasingly, much of this data is unstructured data that includes audio and sound files, video and images, geospatial data, video surveillance, medical research, text files, social media posts, websites and more. Hard to organise and search, due to the variety of forms it can take, the volume of unstructured data that is being created, captured, and copied is increasing at a significant rate.

 

With IDC predicting that by 2025, 80% of data held in an organisation will be unstructured, ensuring that these assets can be easily stored, accessed, and utilised for analysis and decision-making is a top priority.

 

In the case of public sector bodies, making sense of all this information and leveraging unstructured data to derive actionable insights will be mission critical. They must have the ability to effectively analyse unstructured data to propel community research efforts, enhance threat assessments, deliver improved intelligence about public safety or health care, inform service improvement decisions, and so forth.

 

However, government organisations often find their AI implementation efforts are hampered by legacy storage infrastructures that are unable to deliver the accessibility and visibility into the value of data that is key for leveraging data assets in ways that are both simple and cost-effective.

 

But that’s not the only data management challenge the government must contend with.

 

Safeguarding data

Alongside addressing how data is stored so that users can quickly find, access, and integrate the data they need, government organisations also need to ensure that this data is also appropriately safeguarded. 

 

In addition to providing comprehensive protection against cyber-threats, that means utilising storage that features a framework for controlling system access and undertaking system monitoring and detection, as well as managing data security and encryption.

 

These apparently competing requirements introduce an additional layer of difficulty for government entities: while data must be extremely secure at all times, it also needs to be easily accessible to those that need it for analysis.

 

Using AI-powered storage for efficiency, security, and insights

In recent years, AI-powered storage solutions have emerged that make it easier for government organisations to manage large volumes of data more effectively in a variety of ways. 

 

Today’s intelligent data management systems use AI algorithms that automatically tag, catalogue, and index data to identify what is critical versus what can be archived and deleted. In addition to making it easier for users to search and find the data they want to recall for analysis and put it to future use, these autonomous storage systems can also identify classified or sensitive information and move this to a location where only those with appropriate clearance can access.

 

Similarly, AI-powered storage can enhance data security by detecting anomalies and potential threats to protect critical data from unauthorised access and cyber-attacks.

 

Able to self-adjust and optimise storage performance, dynamically adapting resources to changing usage and workload needs, these AI-driven storage platforms not only reduce the storage management burden on IT teams; they also support better-informed decisions on data storage requirements.

 

Driving efficiency and enhanced data management

Today’s AI-powered high-performance storage solutions simplify data storage and management for public sector organisations. By eliminating the need for manual intervention, they make it easier to manage large volumes of unstructured data from a range of sources more effectively while simplifying data retrieval and management.

 

Featuring advanced security measures such as anomaly detection and real-time threat analysis, these solutions make it easier for government bodies to understand and manage their unstructured data and extract the hidden value within it. All of which reduces the time, complexity, and cost associated with delivering new AI-driven capabilities.

 

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Roland Rosenau is SE Director EMEA at Quantum

 

Main image courtesy of iStockPhoto.com