The public sector has long been the guardian of an exceptionally large volume of data and information. In recent years, the digital transformation wave has drastically multiplied the amount of data these agencies need to store, manage, and utilise. Furthermore, as the expectation for transparency and efficiency continues to rise, the complexity of managing information across multiple silos deepens. The result is an overwhelming challenge for public sector entities and records and information managers. Enter Generative AI - the groundbreaking technology promising to revolutionise how information is sorted, processed, and utilised.

At Objective, we recognise the immense potential of Generative AI and are committed to helping our clients harness its power for their specific needs. During our annual user conference, Objective Collaborate, we unveiled our latest AI capabilities set to redefine the landscape of public sector information management. The introduction of powerful auto-classification and content summarisation functionalities to help solve many cumbersome challenges of data organisation and comprehension. This AI-driven technology seamlessly categorises vast volumes of data, automatically sorting them into meaningful classifications, speeding up information retrieval and ensuring its accuracy and relevance. 

Furthermore, its content summarisation capability distils extensive documents into concise, easily digestible summaries, enabling quick decision-making and improving operational efficiencies. Objective 3Sixty is poised to become an indispensable tool in the arsenal of public sector agencies, striving for enhanced productivity and superior information governance.

Practical Applications of Generative AI in the Public Sector

Auto Classification

One of the most significant advantages Generative AI brings to the public sector is auto-classification. With the increasing volume and complexity of data entities handled, manually categorising information can be cumbersome, inconsistent and prone to errors. Generative AI can automatically sort and label data based on its content, relevance, and context, making data retrieval straightforward and time-efficient. This means critical information can be accessed promptly when needed, enhancing decision-making processes and operational efficiencies.

Auto-classification, a pivotal application of Generative AI within the public sector, revolutionises the management and organisation of vast information landscapes. At its core, auto-classification leverages artificial intelligence to categorise and manage content without manual intervention or the need to train ML algorithms with large data sets. This sophisticated process can be broadly divided into three key categories: Business Classification, Security Classification, and Records Classification.

  • Business Classification streamlines organisational workflows by automatically identifying document types. For example, it can distinguish whether a document is a contract, an invoice, or identify which department it belongs to, thereby optimising data retrieval and usage.
  • Security Classification focuses on safeguarding sensitive information that is critical to operations and poses security risks if exposed. Generative AI excels in identifying complex and sensitive information patterns, such as criminal records or religious beliefs, going beyond mere pattern discovery to ensure robust data protection.
  • Records Classification is essential for determining how long information should be retained or when it should be disposed of, based on predetermined criteria and regulations. This classification aids in compliance management and ensures that records are kept or discarded in an orderly and lawful manner.

Auto-classification is a game-changer, especially when tasked with handling the massive amounts of data endemic in the public sector. Historical data shows that it takes a human an average of 4-5 minutes to process, classify, and categorise a single email. Generative AI, on the other hand, can slash this time to mere seconds, while also ensuring a level of consistency that is virtually impossible for manual classification to achieve.

The implications here are immense. Think of the countless hours of labour that can be repurposed, the elimination of costly errors, and the acceleration of critical processes that used to be stifled under a backlog of unprocessed data.

Content Summarisation

Another pivotal application of Generative AI is content summarisation. Public sector organisations often deal with vast amounts of text data in the form of reports, submissions, and communications, which require considerable time to read and understand. Generative AI can condense these extensive documents into concise summaries, capturing essential information and key points. This enables stakeholders to quickly grasp the gist of documents without dedicating hours to reading, significantly boosting productivity and ensuring that decision-makers are well-informed in a fraction of the time.

One of the most theoretically critical but practically difficult tasks in information management is extracting value from data through understanding and summarisation. Objective 3Sixty summarisation capability understands the crux of documents and data points, distilling information into clear, concise forms.

This not only aids in the internal understanding of information but improves the user experience of systems that can be trained to present this abbreviated information. Through this enhancement of accessibility and actionability, essential decision-making can occur much faster.

Starting Your Generative AI Journey in Information Management

The first step in harnessing the power of Generative AI for Information Management is to address the challenge of connecting disparate information silos. Implementing a data fabric architecture is key to this process. A data fabric offers a unified, integrated layer of data and connectivity that breaks down the barriers between different sources of information. It acts as a foundation that facilitates data aggregation across various environments and enables the seamless exchange and interoperability of data.

A robust data fabric is an essential preliminary step for any institution looking to optimise its Information Management processes through Generative AI.


By leveraging a data fabric, organisations can create a holistic view of their information landscape, making it easier to manage, access, and analyse data from multiple sources. This infrastructure supports the implementation of Generative AI technologies by providing them with the comprehensive data needed to generate meaningful insights, predictions, and summaries. Therefore, establishing a robust data fabric is an essential preliminary step for any institution looking to optimise its Information Management processes through Generative AI.

Conclusion: A Bright Horizon Beckons

The future is exceptionally bright for organisations ready to leverage Generative AI in Information Management. This new horizon is lit not just by the technological advancements themselves but also by choosing the right partners to guide the way. With experienced allies, organisations can revolutionise their Information Management, breaking down silos and creating a comprehensive, interconnected data ecosystem. This synergy is set to unlock incredible efficiencies and produce outcomes that push organisations into a new era of operational brilliance and superior service provision.

Objective is at the forefront of this movement, committed to equipping clients with Leverage your Knowledge Fabric tailored to their unique needs. By combining our expertise in information governance with innovative AI technologies, we aim to position organisations ahead of the curve in a constantly changing digital environment. Explore the endless potential of Generative AI with us and see how it can redefine the future of information management in your sector, especially in the public domain, propelling you to lead in the digital age.