AI adoption continues to spread across industries and regions, including public sector organizations all around the world. However, AI algorithms rely on large amounts of data to learn and make accurate predictions, and their output depends on the data quality on which they are trained. This presents a unique challenge for public sector organizations since they manage, store, and share a high level of sensitive information, including personal data, which makes them prone to data breaches. That's why striking a balance between innovation and information protection is essential to determine success in AI implementation, especially in the public sector.
According to JP Morgan, the need for structured and secure information management has never been more critical, with AI adoption accelerating and the cost of data breaches rising 10% year over year. This need is particularly acute in the public sector, where the prevalence of legacy technology and stringent regulations make AI adoption more onerous and complex. The National Organization of State CIOs found, for example, that 69% of state government data management strategies are still in the “beginning stages,” presenting a significant barrier to AI adoption. The 2024 AI and Information Management Report also states that while an information management strategy can help protect data and drive greater AI success, 44% of organizations lack basic measures such as archiving and retention policies and lifecycle management solutions.
As AI adoption accelerates, government organizations need to do more to safeguard their most sensitive data and optimize storage costs to keep pace with data's exponential growth and complexity. This blog will discuss how to protect your data and improve organizational performance with a comprehensive information lifecycle management strategy.
The Current State of Data Management in the Public Sector
Digital workplace inherently leads to content sprawl, bringing greater risk, increased compliance challenges, and rising storage costs. Public sector organizations often lag behind their private sector counterparts in adopting modern information management practices. Even more concerning, a 2020 Government Accountability Office audit revealed that several federal agencies did not have policies and procedures to fully incorporate record-keeping functionalities into electronic systems, establish controls and preservation considerations, and issue instructions on email requirements.
This slow adoption is not without reason. The public sector faces unique challenges such as:
- Legacy Systems: Decades-old systems and data formats that require careful migration and integration.
- Sensitive Information: Vast amounts of confidential data demand robust security measures.
- Bureaucratic Constraints: Complex approval processes and rigid organizational structures can make implementing new technologies time-consuming and expensive.
The stakes are higher than ever for public sector organizations to implement stronger information management and governance to secure data and better serve people, businesses, and other agencies. Successful AI adoption is not only about the technology, but also the people involved and the data used in it. For example, the City of Vincent, a local government in Western Australia, was able to balance collaboration and governance by leveraging an AI-powered information management solution to better assess and manage the information they store and dispose of. “By not storing unnecessary data, we remove the ability to compromise it,” says Peter Ferguson, Executive Manager, Information and Communication Technology, City of Vincent. Proper data handling makes it easier for users to retrieve and utilize the information accurately and effectively.
Key Components of Effective Information Management for the Public Sector
The public sector can transform their ability to serve the public by leveraging AI, turning information into a powerful asset for decision-making and operational efficiency. As digital transformation deployments mature, with a striking 440% increase in AI-related bills at the state level from 2022, organizations should follow these three critical steps to maximize AI benefits while maintaining data security:
1. Prepare Data. A practical first step is establishing clear criteria for redundant, obsolete, and trivial data, ensuring alignment with organizational goals and compliance requirements. Implementing data classification and labeling systems allows you to build a foundation for intelligent storage optimization.
2. Secure Data. Once you understand your data landscape, conduct risk assessments and consolidate sensitive data into a centralized location. Review and update access permissions to implement security encryption and protocols to prevent AI systems and users from inadvertently discovering your security vulnerabilities.
3. OptimizeOperations. Establish a governance framework and structure that meets ethical AI considerations and addresses gaps identified in your information audit. Keep employees informed of what is happening and build training programs to prepare them for AI’s impact and advancements. Automate information management best practices like auto-classifying content as it is created and simplifying retention and disposal rules.
While the public sector has a long way to go in its digital transformation journey, many governments around the world are taking important steps to modernize their information management. For example, Southern Grampians Shire Council (a local government in Australia) modernized their infrastructure with new software, implementing automated business rules and content lifecycles that reduced staff workload while improving user experience. Similarly, Tasmanian Irrigation (also in Australia) used new technology to implement an automated information management solution that decreased information sprawl, reduced storage costs, and ensured compliance with state and federal regulations.
Using AI to complete repetitive tasks can free up valuable time and resources for humans to focus on more strategic initiatives. It is important to recognize that AI is not here to replace humans but is designed to augment and enhance people’s capabilities. Strong information management is critical to AI success.
The Future of Information Management in Government
Effective information management becomes increasingly crucial as emerging technologies such as AI, big data, and analytics continue to reshape the public sector. Organizations can help prevent incidents or exposures that could impact public administration operations, disrupt government services, and jeopardize confidentiality. The U.S. Government Accountability Office (GAO) recognizes this, and has issued new mandates for agencies to improve their information management practices and implement frameworks supporting AI adoption.
Currently, only one federal agency meets GAO’s electronic record-keeping standards, highlighting the urgent need for improvement across the board. The Department of Defense and other agencies are being directed to implement new acquisition standards specifically designed for AI applications. AI models thrive on high-quality and well-structured data, which means organizations must ensure that their data is clean, secure, and accessible in a format that AI systems can utilize effectively.
Decision-makers must prioritize robust information management strategies to safeguard data, enhance AI performance, and ensure compliance with regulatory standards. Implementing these practices will protect sensitive information and drive innovation and efficiency in public sector operations. Do not wait for a data breach or compliance violation to modernize your information management strategy.
