Recently, the UK government's proposal to save £4.5 billion through artificial intelligence (AI) in the public sector has attracted widespread attention. However, at a parliamentary committee on science, innovation, and technology, experts pointed out that this figure lacks clear evidence and is based on rough assumptions. The government's funding is mainly used for employee salaries and infrastructure, and how to achieve such a large amount of savings in these areas has become a focus of criticism.
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According to a report, UK public services such as the National Health Service (NHS), local councils, and the central government have missed out on potential productivity gains of £4.5 billion due to improper or outdated technology use. A government study published in June this year suggested that the application of artificial intelligence could save each employee the equivalent of nearly two weeks of work per year. This research, based on extensive data, shows that about half of office work can be optimized through AI technology.
However, Nick Davies, an expert, stated at a parliamentary hearing that achieving such a large-scale saving would require significant staff reductions or cuts in capital expenditures. He pointed out that if the goal is only to increase productivity without reducing spending, it would be more feasible. Furthermore, the government has not set clear standards for defining "routine tasks," making it difficult to assess their potential for automation.
Davies also mentioned that many AI tools currently available are still in the early stages and have not been widely adopted. Moreover, they often rely on high-quality data and data architecture, which are not commonly found in the public sector at present. A pilot project last year showed that using Microsoft's Copilot tool did not significantly improve productivity, and Microsoft itself admits it is still working to convince customers of its return on investment.
Key Points:
🔍 **The plan to save £4.5 billion has been questioned by experts, lacking specific evidence.**
💼 **Achieving such a large-scale saving requires significant staff reductions and cuts in capital expenditures.**
📊 **Current AI tools are still in the early stages and have not yet significantly improved productivity in the public sector.**
