AI and Information Management Report 2024
Discover the Data Problem That's Stalling AI Success
Access ReportExplore the Latest on the Future of Work
Managing the Unmanageable: Improving Public Sector Information Management in the Age of AI
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.
Read MoreEvaluating Low-Code/No-Code for Government Agencies: Benefits and Drawbacks
In an age of rapid technological advancement, governments must move quickly to keep pace with the latest trends and advances, a task that’s made more complex by the prevalence of legacy tech in government IT. In 2019, the US federal government spent almost $340 million maintaining legacy technology. An often-overlooked frontier of digital transformation, low-code and no-code platforms offer a promising avenue for addressing these challenges by enabling non-technical staff to develop customized applications swiftly and effectively, without the hassle of external procurement processes.
Read MoreThe Power of Data in Shaping AI: Maximizing Impact with a Strategic Approach
A PwC report estimates that AI could add up to $15.7 trillion to the global economy by 2030, potentially surpassing the combined current outputs of China and India. However, to capitalize on this potential, businesses need a comprehensive data strategy that supports AI innovation, ensuring data is not only available but used effectively to solve problems and create value. This article explores how businesses can strategically leverage data to enhance AI capabilities while addressing the challenges of data security, governance, and privacy.
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