Data management has become a critical aspect of operations across the federal government in the digital age. The sheer volume of data generated daily requires efficient and effective management tools. Enter artificial intelligence (AI)-powered automation, a catalyst for enhanced data management and governance in government.
AI-powered automation is revolutionizing the federal government’s digital transformation and IT modernization by enabling organizations to model, share, and store data in a centralized manner. It automates the management of queries based on their likely resource consumption, reducing manual governance and work. This automation not only enhances query performance and accuracy but also accelerates the productivity of federal employees by handling most of the work itself.
Moreover, AI-powered automation significantly reduces manual data-entry efforts and overall labor costs, saving millions in taxpayer dollars. It enhances enterprise data catalogs, optimizing data collection, curation, and discovery. Even non-technical federal employees can access high-quality data daily with intelligently automated data catalogs. This democratization of data access is a significant step toward fostering a data-driven culture within federal agencies.
The benefits of AI-powered automation for data management and governance also extend to service delivery, customer experience, employee engagement and other essential government functions. To that end, automation improves public services while reducing waste and automating time-consuming tasks. When combined with machine learning, AI and automation can boost citizen engagement and help prevent fraud.
Furthermore, AI-powered automation can extract information and automate paper-based processing, creating systems that automatically generate summaries and reports on government activities. AI’s role in enhancing data management across federal agencies is not limited to automation. It continuously mines content to surface unseen patterns and trends, providing agencies with greater visibility and actionable insights to aid federal decision-making.
How federal agencies can use AI-powered automation to overcome data management challenges
Firstly, adopting AI-powered automation by federal government agencies requires strategic planning and a robust data management strategy. Such a strategy must encompass robust data collection, storage and analysis processes that support training and developing AI algorithms while ensuring security, privacy and ethical considerations. This entails adopting explainable and interpretable AI models that can be subject to research and validation by stakeholders, including citizens, without compromising data privacy or confidentiality.
Secondly, one of the most prevalent challenges is the misconception that federal IT departments have to own data governance, which can hamper digital transformation efforts. In reality, federal data governance should be a shared responsibility, with federal IT managers playing a crucial role in decision-making processes related to data. Another significant challenge is siloed data. Different departments within an agency often operate in isolation, leading to fragmented and uncoordinated data management. This lack of integration can result in poor data quality and a lack of trust in the data, which also impedes strategic decision-making. However, agencies can overcome this challenge through dual mode operation, DevOps and dynamic systems development.
Thirdly, federal agency leaders and their employees must adopt specific best practices to maximize the effectiveness of AI-powered tools like automation. To start, they need to prepare their teams for AI implementation, ensuring that they understand that AI is a tool that relies on direction from a team of experts. This means creating an agency culture that embraces and advocates using AI-powered tools. Next, they need to understand their data, as AI’s performance is only as good as the data it uses. Training AI models, determining use cases, and measuring and tracking results are crucial steps for any data management strategy.
Lastly, to ensure the responsible use of AI, agencies should establish technical guardrails and create quality assurance and governance mechanisms. These steps will allow for traceability and auditability of AI-powered automation systems, enabling operational and responsible AI to scale.
In conclusion, while data governance presents numerous challenges for federal agencies, by adopting AI-powered automation and implementing its best practices, agencies will improve compliance, ensure transparency and deliver more efficient public services.
Mike Daniels, senior vice president of public sector at UiPath, is responsible for driving growth and enabling customer success through the placement and expansion of the UiPath platform within public sector agencies.
Mike and his team are focused on helping customers achieve breakthrough digital transformation results by effectively capitalizing on the innovation offered by UiPath solutions. He has worked to help public sector entities take advantage of groundbreaking technology solutions for over 30 years.
Mike earned his MBA from the Ohio State University and his BSBA from Ohio Northern University.
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