In brief — An AI cannot have a political program: objectives and value trade-offs remain human. But used as a public, auditable, and controlled tool, it could track every euro spent, compare policies, simulate laws before they are voted on, and measure their results after adoption.
What if France entrusted its finances, public policies, and major decisions to an artificial intelligence? The question readily evokes a digital president coolly deciding between pensions, hospitals, and defense. This spectacular scenario, however, misses the real issue. A machine cannot decide what a just society is. It can only seek the best way to achieve the objectives assigned to it by humans.
The thought experiment proposed here therefore sets several simultaneous goals: improving living standards and public services, making finances sustainable, protecting the most vulnerable, and preserving sovereignty. It is neither a prediction nor an electoral program. It explores what a system capable of analyzing accounts, evaluating policies, and testing numerous scenarios could bring, provided it remains subject to law and democratic institutions.
The Starting Point: 1,714 Billion Euros in Spending
Public accounts measure the scale of the challenge. According to INSEE, public administrations spent 1,714.1 billion euros in 2025, or 57.3% of the gross domestic product. Revenues accounted for 52.2% of GDP. The deficit stood at 152.5 billion euros, or 5.1% of GDP, while public debt reached 115.7% of GDP at the end of the year.
This spending is not a homogeneous block that could be reduced in one fell swoop. Social benefits represent 771 billion euros, public salaries 370 billion, intermediate consumption 163.5 billion, and investment 132.2 billion. Interest charges amount to 64.7 billion euros. In 2024, social protection accounted for 41.5% of public spending and healthcare for 15.6%. Spending a lot does not automatically mean wasting: the real question is about the results obtained and the ability to sustainably finance the chosen model.
First Mission: Track Money to Results
An AI tasked with improving public action would more likely start by measuring than by cutting. It would build a map linking each euro to its collection, the bodies managing it, the program funded, the final beneficiary, and the observed result. Administrative costs, delays, population served, efficiency, and potential redundancies would become comparable.
This method would allow for the identification of redundancies between the state, local authorities, social security, operators, and public establishments before eliminating missions. Data already legally held by an administration would no longer be requested multiple times. Policies with proven usefulness would be distinguished from those with weak or unknown effects.
Reduce the Deficit Without Programming a Recession
A decision-support algorithm would not necessarily propose immediate austerity. It would compare multi-year trajectories, adjusted for growth, employment, inflation, and interest rates. Any permanent expenditure would need to specify its sustainable financing, the expenditure it replaces, or the expected return. Borrowing would remain possible to respond to a crisis or finance certain long-term investments.
Growth would count as much as savings. Productivity, employment of young and senior people, skills, investment, and innovation would be tracked as budgetary levers in their own right. For businesses, the priority would be stability: fewer stacked systems, more transparent tax rules, and a sufficiently long horizon to invest and recruit.
Automate Administration, Not Human Interaction
In public services, the machine would prioritize repetitive tasks: data entry, document verification, request routing, or anomaly detection. The time thus freed up could be given back to agents for reception, care, teaching, investigation, or support. In hospitals, it would study bottlenecks, readmissions, and preventable procedures. In schools, digital tutors could adapt exercises, without diminishing the teacher's pedagogical role.
The same caution would be necessary regarding fraud. Detecting an anomaly can help target an audit; it should never turn a score into guilt. Any sensitive decision would need to be explained, traced, verified by a human, and subject to appeal.
Energy, Industry, and Computing: Invest Rather Than Suffer
The scenario would treat energy, defense, computing, critical components, cybersecurity, and research as strategic assets. It would seek to direct savings towards productive investment and make France a simpler environment for young companies, through faster procedures and regulated experimental regulations.
In housing, new projects would be targeted by cross-referencing transport, jobs, networks, prices, land, risks, and demographics. For immigration, the analysis would distinguish asylum, studies, work, family, and irregular status, in order to balance economic needs and reception capacities without reducing fundamental rights to an equation.
Simulate Laws Before Voting, Evaluate Them After
The most profound reform might concern law-making. Before a vote, several scenarios would be published with their assumptions, their cost over ten years, and their expected effects on households, businesses, territories, and public finances. After adoption, results would be measured at twelve months, three years, and five years. Ineffective measures could be corrected or removed instead of accumulating.
Each ministry would have a public dashboard covering not only its budget but also its deadlines, service quality, access, and results. Transparency would not eliminate political disagreements; it would simply oblige everyone to defend their choices based on visible assumptions.
Democracy Must Remain Above the Algorithm
No optimization can decide the desirable level of redistribution, the role of the state, the trade-off between security and freedoms, or the acceptable degree of inequality. Two policies can be financially sustainable and based on opposing conceptions of justice. These trade-offs belong to citizens and their representatives.
The inverse risk would be that of a machine that is too effective: a state capable of cross-referencing income, health, travel, and digital habits would become dangerously intrusive. Data should therefore be limited to what is strictly necessary, models audited, and decisions contestable before a human authority and the justice system.
The most credible scenario is ultimately not that of an AI president. It is that of a public AI serving as a permanent counter-expert: it informs, elected officials decide, the judiciary controls, and citizens contest. Its revolution would not be to replace power, but to make it much more difficult to govern without measuring.
Editorial Note — The value of this thought experiment lies less in the thirty-three measures considered than in a simple question: for every euro collected, what result was obtained? AI can make this question more documented and harder to evade. It cannot answer in place of the French when it comes to choosing who contributes, who receives, and which freedoms must remain untouchable.
