Jean Ramirez, Vice President of the Drôme Ardèche Construction Federation (FFB) and President of Hythlodée, shares his experience on the adoption of artificial intelligence (AI) in the construction sector. In this interview, he discusses data structuring, change management, and concrete use cases that are progressively transforming the construction industry.

A Pragmatic Approach to AI in Construction

Jean Ramirez begins by introducing his group, Hythlodée, which owns four companies specializing in climate engineering, electrical work, hydrotherapy, and IT. “Under this holding, we have Largier Technologie, which operates in climate engineering, plumbing, and heating. Electro Industrie complements this activity with electrical engineering. We also have Somethy Technologie, which manufactures hydrotherapy equipment, and finally Altup Conseil, our IT services company.”

AI is progressively being integrated into these fields to improve data management, optimize decision-making, and automate certain tasks. Jean Ramirez emphasizes that his group initiated its digital transition well before the arrival of generative AI. “We’ve been digitalized for a long time. Today, we use these foundations to leverage AI capabilities.”

The Creation of the AI Working Group in 2018 at FFB

They began taking an interest in artificial intelligence in 2018, following the publication of the Villani Report. This document, which addressed the impacts of AI on the economy and society, did not mention the construction sector. “We were surprised that not a single line was devoted to our industry.” Faced with this oversight, the Federation decided to establish a working group dedicated to AI to assess the implications and opportunities for construction.

Since its creation, this group has published four reports aimed at educating professionals, identifying innovation levers, and supporting companies in AI adoption. “The first step was to understand the technologies and distinguish what truly qualifies as AI compared to conventional IT solutions.”

Funding Mechanisms and Support from BPI

One of the major levers for the digital transition of construction companies relies on support from the Public Investment Bank (BPI). The BoosterIA program offers financial and technical assistance to companies wishing to structure their data and integrate artificial intelligence tools. “We promoted this program at the national level to encourage our members to benefit from it.”

The program unfolds in several phases: an initial online education phase, followed by a diagnosis conducted by a BPI-accredited expert. This expert analyzes the company’s data, identifies relevant use cases, and proposes suitable solutions. To date, over 400 companies have joined the program, and the Federation continues to encourage its members to engage in this process. “The goal is to help companies take the first step and understand how AI can optimize their processes.”

Feedback from companies that have benefited from these initiatives is positive. Some have successfully automated repetitive actions, such as report writing or tender management, thus freeing up time for higher value-added tasks. “AI doesn’t replace humans; it supports them by simplifying complex tasks.”

Experience in His Companies: Use Cases

One of the group’s first challenges was to organize and structure data. “It’s the fuel for AI. We must start from the principle that everything can be structured, from files archived in metal boxes to digital databases.”

Through foundational work on document digitalization, the group was able to progressively implement AI solutions capable of searching, analyzing, and exploiting this information. “We vectorized our databases and implemented an internal search engine to query our technical documents and knowledge bases.”

One of the first concrete AI use cases within the group was the automation of technician intervention reports. “Previously, our technicians manually entered their reports, often with errors and approximate wording. A human review was then necessary before sending them to the client.” With AI, this process has been automated. “Now, technicians dictate their interventions, AI reformulates them properly, and the report is generated instantly. The client immediately receives a structured and readable document.” This automation has reduced delays and freed up time for back-office employees.

The group has also implemented AI-based tools to analyze contracts and tenders. “Analyzing a tender takes time. Penalties and guarantees are often scattered across dozens of pages. We created AI software that extracts these key pieces of information and synthesizes them.” This time saving has a direct impact on productivity and helps limit risks related to unfamiliarity with certain contractual clauses.

Towards Integrated Industry-Specific AI

The group’s objective is now to develop AI specific to internal needs. “We have over 12,000 pages of technical documentation and a history of 20,000 quotes. The idea is to be able to query this database directly with a virtual assistant.”

This AI will enable technicians in the field to get answers to their questions and accelerate case management. “Today, a technician must search for information across different systems. Tomorrow, they will simply be able to ask a question in natural language and get the solution immediately.”

One of the major projects currently being implemented concerns transforming client specifications into article codes directly usable by their internal software systems. This task, which currently engages specialized engineers and technicians, represents an annual cost of €200,000. “The current process relies on manual reading and interpretation of specifications, which takes considerable time.” The objective is to develop artificial intelligence capable of analyzing these documents and extracting the necessary information to automatically generate article codes adapted to management systems. “If we can automate even just 20% of this task, it would represent significant savings and improvement in terms of speed and reliability.” This project perfectly illustrates AI’s potential impact in the construction sector by lightening the workload and improving team productivity.

Change Management and Team Adoption

One of the essential points addressed by Jean Ramirez is change management. “AI must not be imposed top-down. Each project must be co-constructed with the teams.” This methodology has enabled the progressive integration of AI tools without generating resistance. “The technicians themselves propose improvements, such as simplifying time entry or optimizing schedules.”

One of the main difficulties has not been acceptance, but rather project prioritization. “Our employees have many ideas and needs. Our major challenge today is to prioritize these requests and implement the most profitable solutions quickly.”

AI’s Impact on Employment and Work Organization

Questioned about AI’s impact on employment, Jean Ramirez takes a pragmatic stance. “AI doesn’t replace technicians; it assists them. In our sector, the workforce remains essential. What AI enables is the elimination of tasks without added value.” He takes the example of time saved through report automation and contract review. “Employees can focus on more interesting and higher value-added tasks.” However, he acknowledges that the massive arrival of AI in the workplace raises ethical and societal questions. “Reflection on AI must not be limited to technical aspects. We must also question the impact of these technologies on work organization and the place of humans in the company.”

Advice for Companies Wishing to Adopt AI

Jean Ramirez emphasizes the need to start with concrete use cases. “The secret to action is to get started. You must identify a specific problem, measure potential gains, and begin with a low-cost, high-ROI project.”

He recommends expert guidance and the use of support programs like BPI’s BoosterIA. “It’s important to be guided to avoid going in all directions and wasting time and money.”

The experience of the Hythlodée group shows that integrating AI in construction is not only possible but also beneficial. By structuring data, identifying opportune use cases, and involving employees, companies can leverage AI to improve their efficiency and competitiveness. Jean Ramirez concludes on an optimistic note: “Well-used AI enables the automation of tedious tasks and refocuses teams on their core business. It’s a transformation lever that, if well mastered, can bring much to construction companies.”