{"id":17051,"date":"2026-06-10T08:30:00","date_gmt":"2026-06-10T06:30:00","guid":{"rendered":"https:\/\/www.tolk.ai\/blog-ia\/non-classe\/guide-map-your-automatable-processes-in-just-2-hours"},"modified":"2026-06-25T16:51:01","modified_gmt":"2026-06-25T14:51:01","slug":"guide-map-your-automatable-processes-in-just-2-hours","status":"publish","type":"post","link":"https:\/\/www.tolk.ai\/en\/blog-ia\/business-sectors\/guide-map-your-automatable-processes-in-just-2-hours","title":{"rendered":"Guide: map your automatable processes in just 2 hours"},"content":{"rendered":"\t\t
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\n\t\t\t\tMost artificial intelligence (AI) projects in public administrations do not fail because the technology does not work. They fail because no one asked the right questions before signing. This quick AI guide fixes that problem.\t\t\t<\/p>\n\t\t\t\t\t<\/blockquote>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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In our previous article, we showed how the Brittany regional prefecture cut its inbound calls by 56% thanks to its AI experiment<\/a>. This result was no accident: it was preceded by precise mapping of the use cases to automate as a priority. That is exactly the purpose of this AI guide dedicated to the public sector.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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The common mistake to avoid<\/h2>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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On the one hand, the pattern is always the same: a department buys an AI solution, then looks for use cases that fit it. As a result, the outcomes are disappointing. The project is then put on hold, and AI becomes synonymous with a broken promise in internal reports.<\/p>

What this highlights is a confusion<\/strong> between the technology demonstration and the operational benefit. A solution can be impressive in a demo and have little effect once deployed, simply because it was grafted onto a poorly understood flow.<\/p>

The technology works, but it answers a question that no one had really asked.<\/strong><\/p>

On the contrary, the reverse approach is nevertheless simpler<\/strong> and far more effective<\/strong>. First, you need to identify what, in your current flows, does not require human judgment. Then, selecting the two or three use cases that combine strong impact and high feasibility is essential. Indeed, deployment should take place only on those cases. Where possible, teams test, measure and analyze the first results to adjust the scenarios.<\/p>

Finally, the solution expands gradually. This workshop is the first step required for success in an AI project, particularly in the public sector. Moreover, the tolk.ai teams are present at each of these stages to combine their expertise with your business skills and make the most of it.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Practical AI guide to prepare the foundations of your project<\/h2>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\tThis workshop usually brings together 3 to 5 people: the head of services or their representative, one or two staff members familiar with the processes concerned, and if possible an IT department contact. No prior technical preparation is required.\t\t\t<\/p>\n\t\t\t\t\t<\/blockquote>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Step 1: Inventory of flows<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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First, the goal of this step is to take stock of your main points of contact with your users. Here, you analyze your channels: phone, front desk, email, forms, appointment booking and so on. For each flow, estimate the weekly volume, the nature of the requests (informational, transactional or complex) and the share that genuinely requires the expertise of a trained agent.<\/p>

Moreover, for most administrations we support, 50 to 65% of the reception flow can be handled without human expertise<\/strong>. This figure is never shown in dashboards. It only appears when we carry out this inventory work with the business teams.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Step 2: Prioritization and roadmap<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Second, on the basis of this inventory, building the impact\/feasibility matrix is valuable. Each use case is positioned along two axes: the volume handled and the potential time saved<\/strong> on one side, and data availability and ease of integration<\/strong> on the other.<\/p>

In this example, the cases in the green zone are your priorities. At the end of these two steps, you leave with a structured working document: mapped flows, a prioritized matrix and an estimate of the benefit of AI.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Example: 3 key public sector use cases<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Indeed, despite the diversity of institutional contexts, certain use cases recur in almost all the workshops we run with our clients.<\/p>

First, information on the documents to provide<\/strong> is identified as a priority in 80% of workshops. It is the most frequent and most standard reason for contact, and the one for which the necessary data is almost always already available in documentary form.<\/p>

Also, real-time case tracking<\/strong> is another frequently identified case. As soon as your management system allows a lookup by case number, an AI agent can answer status requests 24\/7 without any human intervention.<\/p>

Finally, assisted appointment booking<\/strong> is particularly relevant for public administrations. The virtual agent can qualify the need, direct users to the right service and offer available slots. As a result, it reduces the rate of misdirected appointments and unnecessary callbacks.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Summary<\/h2>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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In the end, mapping is not just one preparatory step among others. It is what separates a successful AI project from one that stays in the pilot phase for several months.<\/p>

Thanks to this guide, you identify the two or three leverage points on which to focus your efforts. The ones where the impact is strong for your staff and your users alike. You also focus on the cases with high feasibility, where data is already available. It is precisely this preliminary work that has driven the success of the public sector projects we support.<\/p>

In conclusion, the question is not only whether your processes are automatable<\/strong>. In almost all administrations they are, to the tune of 50 to 65% of the reception flow<\/strong>. The question is which ones to handle first, and in what order to build the roadmap.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Our team can support you in running this workshop. This session is free and with no commitment.<\/p>

> Book an appointment<\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

Most artificial intelligence (AI) projects in public administrations do not fail because the technology does not work. They fail because no one asked the right questions before signing. This quick AI guide fixes that problem. In our previous article, we showed how the Brittany regional prefecture cut its inbound calls by 56% thanks to its […]<\/p>\n","protected":false},"author":15,"featured_media":17053,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"content-type":"","inline_featured_image":false,"footnotes":""},"categories":[90],"tags":[102],"class_list":["post-17051","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-business-sectors","tag-public-administration"],"yoast_head":"\nPublic sector AI guide: map your processes<\/title>\n<meta name=\"description\" content=\"Discover the tolk.ai public sector AI guide: define your key use cases and prepare the deployment of your AI project.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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