Artificial intelligence (AI) can play a decisive role in breaking down traditional barriers in information management. By leveraging AI effectively, organisations can make better decisions, respond more quickly to change, and actively use their data as a strategic source of value and innovation.
Artificial intelligence (AI) is playing an increasing role in the world of information management and governance. The Breaking Defense article Could AI help US intelligence end decades-long aversion to unclassified data? discusses how AI could help US intelligence agencies overcome their traditional reluctance to unclassified data.
From classified to unclassified data
Traditionally, intelligence agencies have relied primarily on classified data, with skepticism toward open, unclassified sources. This attitude is not unique to intelligence agencies; many organisations cling to traditional, structured data streams because of fears of chaos, data breaches or compliance issues. Yet AI makes it possible to extract valuable insights from vast amounts of unstructured, publicly available data.
Classified information is confidential data accessible only to those with special permission, due to security risks or strategic interests. Examples include military plans, spy data or state secrets.
Unclassified information, on the other hand, is publicly available without special restrictions. An example is news reports, social media, or data from public Web sites.
An example of classified versus unclassified information is the exact location of military bases (classified) versus online satellite images on Google Maps (unclassified). Although the satellite images are publicly available, sensitive information such as precise activities within the bases may remain classified.
The power of AI: practical examples
A striking example of valuing classified information over unclassified information was visible just before Hamas' surprise attack on Israel in October 2023. It was then retrospectively observed that prior to the attack there was a striking increase in Arabic-language online visits to certain sites, which were later actually attacked. Such patterns can only be recognised with powerful, AI-driven analytics systems.
This example shows how AI not only offers strategic advantages, but can also be potentially life-saving by enabling early warnings.
How AI is changing data analytics
AI systems and large language models (such as GPT models) offer the capacity to analyse vast amounts of data quickly and effectively. These systems are particularly well suited for recognising patterns, trends and anomalies in data that human analysts may miss, especially when dealing with huge, dynamic and diverse data sets.
AI also allows organisations to respond quickly to changing conditions because analysis occurs in near real-time. Where human analysts take days or weeks to process complex data sets, AI models can complete the same tasks within minutes or even seconds. This makes it possible to make faster decisions, minimise risk and better exploit opportunities.
In addition, AI provides a level of scalability that manual analytics cannot match. As data sets grow, the number of human analysts required also increases exponentially, which can become expensive and practically unfeasible. AI systems, on the other hand, are designed to scale effortlessly. This allows them to continuously grow with the amount of data and remain equally effective regardless of the size of the dataset.
The importance of effective information governance
Information governance is becoming even more important because of these developments. After all, good governance not only means ensuring compliance and risk management, but also actively steering for value creation from data. AI can support this by automatically classifying, tagging and protecting data, so that information always remains accessible, reliable and secure.
AI also strengthens data control by being able to detect anomalies and risks early. This helps organisations proactively resolve potential problems before they escalate. AI-driven governance also improves regulatory compliance by automatically checking whether data complies with policies and legal requirements.
Furthermore, effective information governance with AI helps improve transparency and accountability within organisations. Because AI systems can automatically log and monitor data, it creates a clear audit trail of data use and management, which is essential for auditing and compliance purposes. This not only increases trust within the organisation, but also toward external stakeholders and regulators.
Strategy and governance in AI implementation
However, implementing AI requires a thoughtful strategy around governance and data management. Organisations must invest in clear guidelines, policies and controls that ensure data integrity, quality and compliance. After all, the lack of these can lead to unwanted biases, privacy risks or compliance issues.
In addition to establishing policies and guidelines, training and awareness is crucial. Employees should be trained on how to effectively handle AI tools and the associated risks and responsibilities. This allows them to better understand how AI can support their decision-making and the risks it may pose.
Technical infrastructure also plays an important role in AI implementation. Investment in powerful and secure technology platforms is essential to store data securely, manage it effectively and protect it from unauthorised access. This requires not only technology solutions, but also continuous evaluation and improvement of the systems used.
From defensive to proactive
In addition, AI in information governance requires a shift from a purely defensive approach to a more proactive strategy. This means anticipating risks, seizing opportunities and enabling innovation through advanced analytics and data management techniques.
A proactive approach includes actively monitoring data to identify early trends and potential problems. This allows organisations to not only respond to threats in a timely manner, but also discover new opportunities that give them a competitive advantage. This requires a cultural shift where employees are encouraged to actively use data and drive innovation.
Moreover, a proactive strategy helps increase flexibility and agility within organisations. By having continuous insight into the status of data and systems, organisations can move quickly in the face of changing circumstances, such as new regulations or sudden technological developments. This ensures that they are always prepared and can respond effectively to challenges and opportunities.
Roadmap for AI information management
Organisations that want to make real work of AI in information management can do the following:
Inventory and classify data: Map all data (structured and unstructured) and determine which is classified or unclassified.
Use AI for data analysis: Deploy AI tools and language models to quickly extract insights from large data sets and identify patterns and anomalies early.
Develop a governance framework: Establish clear guidelines and policies for using AI, including privacy, security and compliance.
Implement automated controls: Use AI to automatically classify, secure and check data for compliance.
Train employees: Provide awareness and education around AI use, data risks, and data accountability.
Create transparency and accountability: Provide systems that automatically support audits and monitoring to make accountability easy.
Encourage a proactive culture: Encourage employees to actively leverage data, think innovatively, and proactively identify opportunities and risks.
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