{"id":1165,"date":"2026-07-02T15:38:48","date_gmt":"2026-07-02T13:38:48","guid":{"rendered":"https:\/\/aicet.eu\/?p=1165"},"modified":"2026-07-03T14:32:58","modified_gmt":"2026-07-03T12:32:58","slug":"ai-maturity-assessment-in-the-workplace-insights-from-the-bouygues-group-and-230-senior-hr-leaders","status":"publish","type":"post","link":"https:\/\/aicet.eu\/en\/actualites\/ai-skills-training\/ai-maturity-assessment-in-the-workplace-insights-from-the-bouygues-group-and-230-senior-hr-leaders\/","title":{"rendered":"AI Maturity Assessment in the Workplace: Insights from the Bouygues Group and 230 Senior HR Leaders"},"content":{"rendered":"

Introduction: from large-scale AI rollout to genuine operational mastery among leaders<\/strong><\/h2>\n

The Bouygues Group is among the major French corporations that embraced artificial intelligence early on. Tools rolled out at scale, sustained investment, a structured AI ecosystem: the foundations are in place. But as is the case for many organisations at this stage of maturity, one central question remained: how do you move from mass deployment to a genuine, measurable, operational command of AI among your people?<\/p>\n

This is precisely the question the Bouygues Group decided to put to its HR function in concrete terms, not through a survey, but through a standardised, objective assessment of AI maturity among its leadership teams. 230 senior leaders from across the group’s entities (TF1, Colas, Bouygues Immobilier, Bouygues Construction, Bouygues Telecom and Equans) took part in the process. Once the assessment campaign was complete, a full diagnostic together with several dozen recommendations was produced and presented by Arnault Ioualalen, CEO and founder of Numalis and AICET, during an HR morning session devoted entirely to artificial intelligence.<\/p>\n

This account looks back at the key stages of the initiative, the lessons it produced, and the principles it offers to any HR department wishing to build lasting AI proficiency within its teams.<\/p>\n

Why the Bouygues Group chose to measure the AI maturity of its senior HR management<\/strong><\/h2>\n

The trigger for the initiative was a finding shared by many large organisations at an advanced stage of their AI transformation: the tools are deployed, initiatives are multiplying, but genuine operational command among teams remains difficult to pin down. Organisations know what they have put in place. What they don’t know precisely is what their people actually do with it, or how far their understanding really extends.<\/p>\n

This lack of measurement creates a strategic blind spot. It becomes impossible to know where to focus future efforts, which profiles are ready to accelerate, and which need targeted support to reach the operational level expected at their level of responsibility.<\/p>\n

It is this shift, from a deployment-driven approach to one grounded in measured, managed mastery, that the Bouygues Group wanted to embody within its HR function. With a clear objective: to have a precise, objective diagnostic in hand before taking the next steps, so as to prioritise accurately rather than act blindly.<\/p>\n

The AI skills assessment method: 6 modules, a two-week campaign<\/strong><\/h2>\n

The assessment was rolled out over a two-week campaign, giving all 230 HR leaders across the group time to complete it at their own pace.<\/p>\n

The AICET framework used for the initiative is designed to be both standardised, to allow comparison across entities and over time, and tailored to the realities of the HR profession and each participant’s level.<\/p>\n

Six modules structured the assessment to cover the full spectrum of AI skills relevant to senior HR profiles:<\/p>\n

M1 \u2013 AI culture and critical judgement. <\/strong>Understanding what AI is, how it works, its limitations, and exercising critical judgement over its outputs.<\/p>\n

M2 \u2013 Use of generative AI and prompting. <\/strong>Knowing how to formulate effective requests and use generative AI tools productively in day-to-day work.<\/p>\n

M3 \u2013 Reliability, risk and safe use. <\/strong>Identifying the risks associated with AI use: bias, hallucinations, data confidentiality, unsupervised use.<\/p>\n

M4 \u2013 Governance and AI Act compliance. <\/strong>Understanding the applicable regulatory framework and its practical implications for HR functions operating AI systems.<\/p>\n

M5 \u2013 Creating value through the business. <\/strong>Identifying opportunities to apply AI within HR processes and assessing their potential value.<\/p>\n

M7 \u2013 Management, adoption and workplace transformation. <\/strong>Understanding how to support teams through AI transformation, manage resistance and embed new practices.<\/p>\n

The assessment covered three distinct levels: Foundation (FND), Familiarisation (ACC) and Advanced (ADV), allowing both basic grounding and more operational, expert-level mastery to be measured.<\/p>\n

Presenting the results: a driver of engagement for international leaders<\/strong><\/h2>\n

Once the campaign was complete and all the data consolidated, the full diagnostic was presented during the Bouygues Group’s HR morning session, an event bringing together the function’s international leaders around an ambitious programme devoted entirely to artificial intelligence.<\/p>\n

Arnault Ioualalen’s presentation played a significant role: setting out the AI maturity diagnostic results entity by entity, drawing out an analysis, and presenting the several dozen recommendations put forward by AICET’s team of experts. This entity-by-entity granularity produced an unexpected but powerful effect: a healthy sense of competition in the room. As results were unveiled entity by entity, with each leader keen to see their team come out on top, this positive tension turned what could have been a simple report-back into a moment of strong collective engagement, proof that measurement, well presented, is itself a powerful driver of mobilisation.<\/p>\n

Another notable effect of the presentation was that it removed any sense of blame. Rather than placing leaders in a binary judgement about their level of AI proficiency, the AICET diagnostic made it possible to state precisely what had already been achieved and what still needed to be consolidated, skill by skill. A leader with a modest overall score could see exactly which specific skill they needed to improve to lift the whole picture, making the goal of skills development concrete and achievable.<\/p>\n

In its message to the speakers following the morning session, Bouygues Group management praised the quality and openness of the discussions, noting that they would feed into further thinking and, above all, into action within the business lines. This is precisely the intended effect: turning a moment of measurement into a catalyst for lasting action.<\/p>\n

What an AI maturity diagnostic reveals about an entire HR function within a large group<\/strong><\/h2>\n

The Bouygues Group’s experience illustrates several realities that any HR leadership team engaged in AI transformation can usefully bear in mind.<\/p>\n

Measurement improves the quality of decisions. <\/strong>Without a prior diagnostic, actions are calibrated subjectively. With an objective diagnostic of teams’ AI maturity, they can precisely target the skills to strengthen, the priority populations and the appropriate level of intervention.<\/p>\n

Variation between entities is strategic data. <\/strong>In a group as diverse as Bouygues, bringing together entities as different as TF1, Colas, Bouygues Telecom and Equans, AI maturity levels naturally vary from one organisation to another. The entity-by-entity mapping produced by AICET turns this variation into a lever: it makes it possible to identify where good practice already exists and how to spread it across the group.<\/p>\n

Internal champions already exist. <\/strong>Within any population assessed, a well-designed diagnostic brings to light high-potential AI profiles capable of acting as internal points of reference. Identifying them objectively, rather than through co-option or self-selection, ensures the strength of the network they form and drive.<\/p>\n

Presenting the results is a strategic moment, not a formality. <\/strong>Well delivered, it turns data into engagement. The format chosen by the Bouygues Group, a collective presentation of entity-by-entity results in front of international leaders, is a compelling illustration of this.<\/p>\n

Post-diagnostic action: from AI maturity assessment to concrete transformation<\/strong><\/h2>\n

The AICET diagnostic does not stop at producing results and recommendations. It leads to a concrete action plan, built together with teams based on the data gathered.<\/p>\n

For the Bouygues Group, the next steps are organised around three areas:<\/p>\n

Implementing the diagnostic’s several dozen recommendations. <\/strong>Each module assessed gives rise to precise recommendations, prioritised by importance and effort, enabling targeted action rather than generic programmes.<\/p>\n

Setting up working groups and mentoring. <\/strong>Drawing on the internal champions identified during the AI skills diagnostic, the aim is to foster collective intelligence within the HR function by organising exchanges of good practice between the most advanced profiles and those looking to progress.<\/p>\n

Building an internal knowledge base. <\/strong>The long-term aim is to capitalise on the good practice identified, and on the mistakes to avoid, to build a living reference resource continually fed by teams’ feedback and experience.<\/p>\n

This logic of continuous capitalisation is what sets a lasting AI transformation initiative apart from a one-off training programme. The initial measurement becomes the starting point of a virtuous cycle: assess, act, reassess, progress.<\/p>\n

Conclusion: the ROI of AI is no longer a question of tools, but of human skills<\/strong><\/h2>\n

The Bouygues Group’s experience is a concrete demonstration of what a well-designed assessment can achieve: turning a subjective view of teams’ capability into a precise, actionable and mobilising map of AI skills, across a multi-entity group operating on an international scale.<\/p>\n

230 senior HR leaders, from TF1, Colas, Bouygues Immobilier, Bouygues Construction, Bouygues Telecom and Equans, spent an average of under 30 minutes on an assessment tailored to their profession. What they produced in return was management data that neither the tools deployed nor the initiatives launched could have provided on their own: an accurate picture of the function’s true AI maturity, several dozen actionable recommendations, and a roadmap towards full operational mastery.<\/p>\n

More than ever, effective use of AI is no longer simply a question of tools, but above all a question of human skills. And the organisations that measure these skills before acting are the ones that transform for good.<\/p>\n

Would you like to launch a similar initiative for your HR department or organisation? <\/em>Talk to an AICET expert<\/em><\/u><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Introduction: from large-scale AI rollout to genuine operational mastery among leaders The Bouygues Group is among the major French corporations that embraced artificial intelligence early on. Tools rolled out at scale, sustained investment, a structured AI ecosystem: the foundations are in place. But as is the case for many organisations at this stage of maturity, […]<\/p>\n","protected":false},"author":4,"featured_media":1168,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_seopress_titles_title":"AI Maturity Assessment in the Workplace: Insights from the Bouygues Group and 230 Senior HR Leaders","_seopress_titles_desc":"How the Bouygues Group assessed the AI maturity of 230 senior HR leaders from TF1, Colas, Equans and Bouygues Telecom using AICET, shared the results live, and set dozens of concrete recommendations in motion. 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