Currently, local elected officials and public actors are actively engaged in responding to territorial divides.
However, inequalities are no longer limited to the simple divide between cities and countryside: they reveal a much more complex reality. They form a complex network of economic, social, environmental, residential and now digital vulnerabilities.
Faced with these multiple realities, traditional approaches show their limits. How, then, can we make innovation, and in particular artificial intelligence, a real driver of transformation of territorial policies?
Analysis in six axes:
1 – Data as a revealer of invisible divides
Fragile territories often have disadvantages: low income, dilapidated housing, environmental nuisances, poor access to digital technology. Geospatial analysis, now accessible to communities, makes it possible to highlight these hidden correlations. Data no longer simply describes: it helps us understand that exclusion is systemic.
This granularity, sometimes down to the neighborhood or the street, reveals what the averages masked:
· pockets of poverty within municipalities perceived as dynamic,
· neighborhoods combining environmental nuisances and social insecurity,
· very isolated rural areas despite a correct departmental location,
· strong contrasts in digital access between two neighboring municipalities.
Inequalities do not follow administrative boundaries: they respond to functional logics linked to housing, employment, mobility or industrial heritage.
Data helps elected officials to:
· follow the evolution of a neighborhood over time,
· identify weak signals before they become critical,
· adjust local policies without waiting for a new diagnostic cycle.
We are thus moving from a static report produced every five or six years to a living dashboard, capable of supporting daily decisions.
2 – Artificial intelligence as a compass for territorial policies
AI brings a new dimension to this territorial reading. By combining thousands of socio-economic, environmental and demographic data, it can suggest priority areas for action, identify the most relevant levers and anticipate the impact of future public policies.
Used responsibly, AI becomes a territorial compass: a decision-making tool to guide investments, prioritize infrastructure, or even propose development scenarios. This is already demonstrated by certain geospatial analysis tools, capable of assessing inequalities at the municipal level, and tomorrow, at that of the neighborhood or street.
3 – Delve into the geography of inequalities
To understand territories, we must first accept their complexity. Behind the national statistics lie very contrasting local realities.
The most visible economic inequalities pit large cities, where qualified jobs, high incomes and investments are concentrated, against rural or peri-urban areas, marked by structural unemployment and lower standards of living. Added to these disparities is an inequality in attractiveness: businesses, infrastructure and innovation continue to be concentrated in the same dynamic centers, leaving other territories to sink into a spiral of disinvestment.
Emblematic example: Denain (North).
A former industrial basin, Denain illustrates this economic divide. Its young population (nearly 47% are under 30 years old) lives in a stock of dilapidated housing (85% built before 1970), often poorly renovated. The median income there is less than €10,000 per year, less than half the national average, the poverty rate is close to 60%, and unemployment exceeds 36%, three times the national average.
4 – The accumulation of vulnerabilities: a major challenge for public action
Inequality is not limited to the economy. Residential and environmental divides reveal a social geography of cities where low-income households are pushed to poorly served outskirts and exposed to nuisances. Disadvantaged areas are often home to the most polluting infrastructure (factories, roads, warehouses), aggravating a form of environmental injustice.
Auchel (Pas-de-Calais).
A former mining town, Auchel has lost a third of its population since the 1970s. Old housing, sometimes vacant, and degraded workers’ housing estates create a fragmented residential landscape, a symbol of poorly accompanied urban decline.
Fos-sur-Mer (Bouches-du-Rhône).
At the heart of an industrial-port area, the town concentrates refineries, steelworks and warehouses. Health studies reveal an excess of respiratory and cancerous pathologies, a consequence of prolonged exposure to industrial pollution. Here, social injustice and environmental injustice overlap.
Added to this is the digital divide, a new frontier of inequalities: access to very high speed, fiber, digital skills… all conditions now essential for economic and social inclusion.
5 – Inequality of access to public services: another face of the divide
Inequalities in access to services constitute another major face of the territorial divide. Closures of post offices, train stations, maternity wards: all signals of a gradual decline in public presence in certain areas.
Saint-Denis (Seine-Saint-Denis).
In this department where the poverty rate exceeds 28%, public services (school, health, security) are often in tension: lack of teachers, overcrowded classes, understaffing in hospitals. However, the nearby Parisian metropolis concentrates wealth and infrastructure just a few kilometers away.
Souleuvre-en-Bocage (Calvados).
The gradual disappearance of services (post office, police station, tax counter) symbolizes a retreating rurality. Residents have to travel tens of kilometers for simple procedures, reinforcing a feeling of abandonment.
Innovation must make it possible to reinvent public presence, via predictive tools, mobile services, intelligent platforms, supported digital counters.
6 – From diagnosis to action: innovation as a lever for transformation
AI alone will not create a fairer territory. But by offering an objective and localized diagnosis, it allows action to be taken in a more targeted and equitable manner. Where public policies have sometimes lacked granularity, data provides precision. Where diagnostics were too slow, AI introduces reactivity.
Reducing territorial inequalities means recognizing their complexity and interdependence. It means seizing the opportunity offered by technology to move from a logic of compensation to a logic of transformation, based on a detailed knowledge of territories and the potential of their inhabitants.
The question is no longer whether AI can help, but how to integrate it responsibly and equitably into planning strategies. What if the key to a fairer territory lay in our ability to combine technological innovation and social ambition?
