Across government, public servants are drowning in a broken operating model.

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Hundreds of siloed applications, manual hand-offs between teams and human co-ordination acting as the glue between systems. This mode of operation was never designed for the speed, complexity and scale public servants now face.

Every public servant knows the daily reality of copying data from PDFs into spreadsheets, putting the same information into three slightly different reports and chasing approvals through email threads. Adding a layer of AI will not fix the problem. The model itself needs to change.

This is where the Autonomous Enterprise comes in.

The Autonomous Enterprise is not a product or feature. It's a new operating model based on human-agent collaboration, in which people set the direction and AI executes. It's not about replacing public servants with machines, but about moving work up the value chain - using AI agents to handle routine processes so people can focus on human judgement, complex problem solving and delivering public value.

From incremental AI to a new operating model

Government leaders aren't asking for AI. They're asking for business outcomes: faster decisions, lower costs, resilient operations. AI is valuable only insofar as it enables those outcomes.

At Germany's Federal Foreign Office, an AI chatbot responds to 50 per cent of incoming citizen inquiries without human intervention. Hamburg's Ministry of Finance is using generative AI to support the processing of social benefit applications, saving up to 33,000 hours of manual effort each year. The City of Madrid's AI hub assists auditors to review about 150,000 cases annually.

These initiatives are important and encouraging. But they also share a common characteristic: AI is applied within narrow, bounded domains - citizen interaction, application intake, case reviews - while the overall process remains fragmented and human-coordinated. The result is meaningful efficiency gains, but not........

© Canberra Times