Doing More with the Same Staff: The Role of AI in Municipalities
In many municipalities, the delivery of public services relies on a complex organizational structure that must balance operational efficiency, budgetary constraints, and high public expectations. Municipal teams manage a wide range of responsibilities, from urban planning and infrastructure management to citizen services, regulatory compliance, and land-use planning.
This complexity has intensified in recent years. The volume of information has increased, requirements have multiplied, and expectations of municipal organizations have evolved. Against this backdrop, the pressure on teams has grown, while resources have not necessarily kept pace. The need to do more with less has become a management reality.
An information-driven operational reality
Even today, much of municipal work relies on accessing and interpreting information. Urban planning files, citizen requests, technical reports, infrastructure inventories: every decision depends on data from multiple, often fragmented sources.
In practice, this means that teams spend a significant portion of their time searching for, verifying, and organizing information before they can even analyze it. This step is essential, but it becomes increasingly burdensome as data volumes grow. This phenomenon is evident in administrative processes as well as in infrastructure management and interactions with citizens.
Given this situation, the options are limited. Continuing with current processes won’t allow us to keep up, and increasing resources is rarely sustainable in the long term.
For Francis Ouellet, Director of AI Strategy Consulting at Explor.ai, the situation is clear: municipal teams aren’t lacking in skills—they lack the time to use them. “Too many hours are spent searching for and verifying information before we can even begin to analyze anything.”
AI as an operational lever
Artificial intelligence fits into this framework. Its role is not to completely overhaul operations, but to step in where information management slows teams down. It integrates with existing tools and streamlines certain steps without fundamentally changing the processes already in place.
AI makes it possible to process large volumes of data more quickly, automate certain repetitive tasks, and make information more accessible.
This translates into tangible benefits in several contexts:
processing of citizen requests
analysis of administrative documents
classification and processing of requests
or the use of infrastructure-related data.
These approaches generally do not rely on complex projects from the outset, but rather on targeted interventions that are gradually integrated into operations.
In any case, AI is used as a preliminary step in the teams’ work. It reduces the time needed to access reliable information and helps speed up the processing stages.
How AI Integrates into Existing Operations
What sets organizations that truly leverage these approaches apart is not just the technology they use, but how it integrates into their operations. When deployed effectively, artificial intelligence acts as an intermediary layer between existing systems and teams.
It streamlines access to information, reduces friction between processes, and accelerates data flow. Cases move through the system more quickly, approvals become smoother, and decisions can be based on more comprehensive information—all without increasing the workload on teams.
This ability to make operations simpler, more transparent, and more consistent is becoming a key factor in improving overall performance without adding organizational complexity.
However, this transformation cannot be achieved through a single project. The most effective approaches are based on targeted use cases, where benefits can be observed quickly and tangibly. They require sufficiently reliable data, clearly defined objectives, and a focus on integration into existing operations.
Governance, security, and privacy considerations must also be taken into account from the outset. Over time, these initiatives can be expanded to other processes as organizations mature and gradually build their capacity to leverage their data.
Make time for what really matters
The most tangible impact of these approaches lies in the redistribution of time.
According to McKinsey, in the public sector, about 40% of employees' time is spent on data collection and processing —tasks that automation can largely take over.
By reducing the workload associated with searching for, validating, and organizing information, teams can process cases more quicklyand with fewer delays. A permit application moves through the system more efficiently, a citizen inquiry is addressed more quickly, and an infrastructure analysis relies on information that is already organized rather than having to be reconstructed.
In an environment where resources are limited, this time savings isn't just about moving faster. In a pre-itit not only allows us to keep up with the volume, but also to regain the capacity to act, which had been gradually limited by the operational workload.
The role ofExplor.ai
Explor.ai supports municipal organizations looking to turn their intentions into action. Founded in 2019, our team of approximately 50 professionals has completed more than 150 artificial intelligence integration projects. This experience has taught us that the most lasting benefits rarely come from the most complex projects.
Our approach begins with an on-site assessment. We identify the processes where information management is the most time-consuming, then take targeted action by automating repetitive tasks, categorizing requests, and organizing infrastructure data. Each solution integrates seamlessly with existing tools.
Would you like to assess the potential within your organization? Let’s talk about it with one of our professionals.
