# Schneider Electric AI Adoption: Four Tiers, 160,000 People > How Schneider Electric matches AI training to each role across 160,000 people: the four tiers, the numbers and their caveats, and the model at your size. Source: https://wecallshotgun.com/blog/schneider-electric-ai-adoption-role-based-training Language: en Author: Toni Dos Santos Published: 2026-10-06 Updated: 2026-10-06 --- AI Tools # How Schneider Electric Tailors AI Adoption to Every Role By [Toni Dos Santos](https://wecallshotgun.com/toni-dos-santos) • Oct 6, 2026 • 17 min read • **Summary:** Schneider Electric splits its workforce into four groups and gives each a different AI curriculum, built with Coursera: a mandatory foundation for all 160,000 employees, production-line workers included; a programme on AI and strategy for senior management, who "need to lead by example" (Chief AI Officer Philippe Rambach, CIO Dive, 5 October 2026); continuous learning for AI experts; and tailored training for transformation owners (product, process and IT owners), the hardest group to identify and serve. According to Schneider's answers to written questions for its 2026 AGM, more than 140,000 employees, close to 100% of staff, completed the mandatory "AI Awareness for All" course in 2025, more than 50,000 took advanced training, and 60,000 use group AI tools every day. About 100 AI use cases run in production (MIT Sloan Management Review, March 2026), including technician dispatch and sales-pitch tailoring, built by cross-functional business, IT and AI teams. No published figure yet links a tier to a productivity result. At 500 or 5,000 people the same structure becomes a baseline, leadership alignment, a shared foundation, a programme per management level, department workflow sprints, and measurement at 30, 60 and 90 days. Schneider Electric runs four AI learning tracks for its 160,000 employees, each matched to a role: mandatory basics for everyone, a strategy track for senior management, continuous learning for AI experts, and tailored training for the people who own transformation. Chief AI Officer Philippe Rambach says senior leaders "need to lead by example." The principle underneath: people learn AI for the decisions they make. I run AI adoption programmes for teams in France and the UK at We Call Shotgun. Most companies that call us have already run an AI training. One version, for everyone. Schneider's model is the clearest public example I've found of why that version stalls, and of what a company of 160,000 people does about it. ## The all-hands AI session You've sat through this one. Everyone gets the same two hours. The sales team learns to summarise a PDF. Finance learns to summarise a PDF. The executive committee was booked for the same slot and sent apologies. Feedback is good. Three weeks later the usage dashboard looks like the week before. Nobody was lazy. A seller's week is call prep, proposals and CRM notes. A controller's week is the close and the variance commentary. A director's week is three decisions and a board pack. One session can't land in all three weeks, so it lands in none of them. Schneider Electric built its programme around that problem. ## What is Schneider Electric's AI training model? Schneider Electric splits its workforce into four groups and gives each one a different AI curriculum, built with Coursera. Everyone takes a mandatory foundation course. Senior management gets a programme on AI and strategy. AI experts keep learning as the field moves. The people who own transformation (product, process and IT owners) get training tailored to their roadmaps. CIO Dive reported the model on 5 October 2026 in [How Schneider Electric is bridging the AI literacy gap](https://www.ciodive.com/news/schneider-electric-ai-literacy-gap/832179/), quoting Rambach, Schneider's senior vice president and chief AI officer. [CIO.inc](https://www.cio.inc/schneider-electrics-playbook-for-scaling-ai-a-32754) and [CDO Magazine](https://www.cdomagazine.tech/aiml/schneider-electric-caio-on-why-ai-transformation-is-largely-not-about-ai) described the same four groups earlier in 2026. | Group | Who's in it | What they get | Why, according to Schneider | | --- | --- | --- | --- | | **1. All employees** | Every employee, production-line workers included | A mandatory foundation: how AI learns from data, and why its outputs are probabilistic | Run like compliance training: tracked, chased with reminders, tied to consequences (CDO Magazine) | | **2. Senior management** | The senior management team | A programme blending AI and strategy, centred on business value and organisational change | "They need to lead by example" (Rambach, CIO Dive) | | **3. AI experts** | The people who write AI software, in a team reporting to Rambach | Continuous learning as the technology changes | They have to keep pace with the field (CIO.inc) | | **4. Transformation owners** | Product, process and IT owners, and the people building the customer roadmap | Tailored training on what AI can and can't do inside their roadmaps and processes | "Those groups [...] need a special focus" (Rambach, CIO Dive) | ![Diagram of Schneider Electric's four-tier AI learning model, as reported by CIO Dive on 5 October 2026, CIO.inc and CDO Magazine. Tier 1, all employees, about 160,000 people including production-line workers: a mandatory foundation on how AI learns from data and why its outputs are probabilistic, tracked like compliance training. Tier 2, senior management: AI and strategy, business value and organisational change, so leaders can lead by example. Tier 3, AI experts who write AI software: continuous learning as the field moves. Tier 4, transformation owners, meaning product, process and IT owners: tailored training to put AI into roadmaps and processes. CIO.inc and CDO Magazine describe tier 4 as the hardest group to serve and to identify.](https://wecallshotgun.com/images/blog/schneider-electric-ai-four-tier-model.svg) CIO.inc summed up the aim: give each group what it needs "without expecting every employee to become an AI engineer." ## How many Schneider employees have completed AI training? More than 140,000, close to all of its staff, completed the mandatory "AI Awareness for All" course in 2025, according to Schneider's [answers to shareholders' written questions](https://www.se.com/ww/en/assets/pdf/2026-AGM-questions-ecrites-written-questions) for its May 2026 annual general meeting. More than 50,000 went on to advanced training on chatbot use, prompting and embedded AI. And 60,000 employees use the AI tools the group provides every day. The programme took four years to get there: - **2021.** Schneider appoints Philippe Rambach as its first chief AI officer and creates an AI Hub ([Schneider Electric](https://www.se.com/ww/en/about-us/newsroom/news/press-releases/schneider-electric-advances-its-artificial-intelligence-ai-strategy-with-appointment-of-chief-ai-officer-and-creation-of-new-ai-hub-617aa598b7359463ac1f3144/)). - **November 2023.** The first promptathon runs with the quality department and draws 250 people. A "promptathon in a box" kit follows so other departments can run their own ([L'Usine Nouvelle](https://www.usinenouvelle.com/editorial/stellantis-thales-schneider-electric-comment-les-industriels-forment-leurs-salaries-a-l-ia-generative.N2213814)). - **2024.** After a pilot with tech and digital staff, 48,000 employees complete AI training and 13,000 take part in promptathons ([Coursera](https://www.coursera.org/enterprise/articles/learn-act-advocate-schneider-electric-cm)). - **2025.** The foundation course, a 30-minute module, becomes mandatory for everyone ([EdtechActu](https://edtechactu.com/digital-learning/schneider-electric-acculture-ses-150-000-collaborateurs-a-lia/)). More than 140,000 complete it. - **March 2026.** About 100 AI use cases are in production, split roughly evenly between customer-facing and internal ([MIT Sloan Management Review](https://sloanreview.mit.edu/article/how-schneider-electric-scales-ai-in-both-products-and-processes/)). - **May 2026.** 60,000 employees use group-provided AI tools daily, in sales, finance, customer support and code generation (AGM answers). ![Bar chart of Schneider Electric AI adoption figures. More than 160,000 employees (company profile, 2026). More than 140,000 completed the mandatory AI Awareness for All course in 2025, close to 100 percent of staff. 60,000 use group-provided AI tools every day. More than 50,000 took advanced training on chatbot use, prompting and embedded AI. Sources: Schneider Electric answers to written questions for the 2026 AGM, and the company profile.](https://wecallshotgun.com/images/blog/schneider-electric-ai-adoption-figures.svg) ## Why does Schneider train senior managers separately? Because people copy what their leaders do with AI, and leaders can't sponsor what they've never used. Schneider's senior management programme covers AI and strategy, business value and organisational change. Rambach's reason is example: > "They need to lead by example, so these teams need special attention with specific trainings that have been deployed to them." Philippe Rambach, SVP and Chief AI Officer, Schneider Electric, in CIO Dive, 5 October 2026 CDO Magazine's interview adds the brief for this group: understand the value of AI, the "why" and its limits well enough to explain them to the people who report to them. This is the layer most companies skip. In our programmes, leadership alignment comes before any team session: one day with the executive committee to agree an AI charter, where the value and the risk sit, and the story leaders will tell their teams. Then each leader uses AI on their own work, a board pack or a forecast review, before asking anyone else to. A director who has never written a prompt can't tell a good AI-assisted proposal from a bad one. Their team notices. More on that in [why executive AI literacy is the missing link](https://wecallshotgun.com/blog/c-suite-ai-literacy-executive-training). ## Which group is the hardest to train for AI? The transformation owners. CDO Magazine calls them the most operationally important group and the hardest to identify, and CIO.inc the most challenging to serve. They're the product, process and IT owners who decide whether AI goes into a roadmap or a workflow. They need enough technical understanding to judge trade-offs, without becoming engineers. > "Those groups who are either in charge of building the customer roadmap or driving the internal transformation need a special focus." Philippe Rambach, SVP and Chief AI Officer, Schneider Electric, in CIO Dive, 5 October 2026 In a company of 500 or 5,000 people, this group has a plainer name: heads of department and the managers who run teams. They own the workflows. If the weekly forecast, the month-end close or the ticket queue is going to change, they're the ones who change it. That's also why they're hard to train. Their day-to-day has little in common with the department next door. A finance manager's AI question is "can I trust this variance commentary?" A sales manager's is "will this proposal still sound like us?" One programme can't answer both. We covered this layer in [AI for middle managers](https://wecallshotgun.com/blog/ia-managers-intermediaires-france). ## How does Schneider turn AI training into use cases? Through cross-functional teams. Schneider puts business, IT and AI people on the same use case, for internal projects and for customers, according to CIO Dive. Rambach describes the learning as a by-product of the project: > "They learn by doing the project, they learn by working together." Philippe Rambach, SVP and Chief AI Officer, Schneider Electric, in CIO Dive, 5 October 2026 The use cases are departmental. That's the point. CIO Dive names three: - **Field service:** an AI tool to dispatch technicians more effectively. CDO Magazine reports that the scheduling of thousands of field service visits was done by hand until recently. - **Sales:** an internal tool to tailor sales pitches quickly. MIT Sloan Management Review also describes an agentic system that reads requests for quotation and extracts, reformulates and summarises them for salespeople. - **Customers:** a service that helps them cut energy consumption. The promptathons follow the same logic. The first one ran with a single department, quality, on its own problems. The kit that followed let every other department do the same with theirs. Jean-Côme Renaudin, who directs Schneider's Data & AI School, describes the job in a Coursera write-up: > "It's about change management. You need to make the learning sticky." Jean-Côme Renaudin, Director, Data & AI School, Schneider Electric, in Coursera's case article ## Read the numbers before you copy the model Three caveats before this goes into a board deck. - **The headcount moves between sources.** CIO Dive says the mandatory course covers all 160,000 employees. Schneider's AGM answers say more than 140,000 completed it in 2025, close to 100% of staff. Earlier Schneider material says 150,000. The figures come from different dates and probably different scopes. I use "more than 140,000 completed" because it's Schneider's own count. - **Completion measures reach.** When 140,000 people finish a mandatory 30-minute module, that tells you the module was mandatory. The more useful figure is 60,000 daily users of group AI tools, roughly 37% of a 160,000 headcount (my arithmetic). Even daily use is activation. Adoption is a workflow that runs differently this quarter, and Schneider's public figures don't break that down by department. - **Nobody has published the effect of each tier.** I found no figure linking a training tier to a productivity or revenue result, and no independent evaluation. The sources are Schneider's own disclosures and interviews with its executives. None of that changes the design lesson. Schneider shows how to structure AI learning at scale. The return is still unpublished. ## Why does role-based AI training drive adoption? Because people adopt AI when it lands in a task they own this week. A generic course teaches the tool's features and leaves each person to find a use. Role-based training starts from the use. Rambach's advice, as CIO.inc reported it: start from a defined business problem and train people according to the decisions they have to make. Microsoft reached the same conclusion about its own Copilot rollout. Licensed to more than 200,000 of its people, usage in sales plateaued until teams started from a business outcome and redesigned the workflow ([our breakdown of what Microsoft learned](https://wecallshotgun.com/blog/why-ai-training-fails-microsoft-lessons)). > "The tool was never the problem. Nobody taught them to drive." Toni Dos Santos, author of Teach Them to Drive: The AI Adoption Playbook for Teams Each management level makes different AI decisions, so each needs a different programme. | Level | What their week looks like | The AI decision they own | What their programme covers | | --- | --- | --- | --- | | **Executive committee** | Strategy, investment, risk, the board | Where AI gets budget, what risk is acceptable, what they tell the company | Leadership alignment: AI charter, value and risk zones, the internal narrative, AI on their own work | | **Heads of department** | A function's targets, priorities and headcount | Which workflow changes first, and which number proves it | Choosing the workflows, setting the baseline, owning the 30, 60 and 90-day reviews | | **Team managers** | One-to-ones, the weekly rhythm, quality control | How the team uses AI on real work, and what gets checked before it leaves | Running the weekly huddle, reviewing AI-assisted output, bringing the sceptics along | | **Teams, by department** | The recurring work of their function | How to do their own tasks with AI, safely | Workflow sprints on the team's real work, on top of the shared foundation | | **Builders and champions** | Internal tools, automation, peer support | What to build, and what to hand to IT | Custom assistants, agents and automation once the foundation is in place | Inside the teams, the split runs by department. The same AI tool does different work in each one, and Schneider's own deployments show it. | Department | Recurring work AI lands on | Schneider's equivalent | | --- | --- | --- | | **Sales** | Call prep, proposals, follow-ups, CRM notes | Tailoring sales pitches; summarising requests for quotation | | **Field service and operations** | Scheduling, procedures, incident reviews, recurring reports | Dispatching technicians, once scheduled by hand | | **Customer support** | Ticket triage, reply drafting, the knowledge base | AI tools used daily by customer support teams | | **Finance** | Close commentary, variance analysis, forecasting | AI tools used daily by finance functions | | **Software and IT** | Code, tickets, documentation | Code generation | The last three rows come from Schneider's 2026 AGM answers, which list where its 60,000 daily users work. They don't give per-department figures. ## What does Schneider's model look like at 500 or 5,000 people? The same four layers, smaller and faster. The structure copies without a Coursera contract or a chief AI officer: each layer gets a programme built around its own week. Here's how we run it with clients: - **Baseline.** We time two or three priority workflows per department (hours, turnaround, rounds of review) and check who uses which tool, team by team. - **Leadership alignment.** One day with the executive committee: the AI charter, value and risk zones, the narrative, and each leader using AI on their own work. - **Shared foundation.** Everyone gets the same grounding in how AI works, where it fails and the company's rules. In the EU, that's also part of meeting Article 4 of the AI Act on AI literacy, in force since 2 February 2025 and supervised since 3 August 2026 ([what Article 4 expects](https://wecallshotgun.com/blog/eu-ai-act-ai-literacy-article-4-risks-action-plan)). - **A programme per management level.** Separate tracks for the executive committee, heads of department and team managers, because they make different decisions about AI. - **Department workflow sprints.** Sales, marketing, finance, HR, operations and support each rebuild their own recurring tasks with AI and human checks, on their real files. - **Measurement at 30, 60 and 90 days.** The same workflow metrics as the baseline, plus the share of people running the new workflow without help. That's the [AI adoption programme](https://wecallshotgun.com/ai-workforce-transformation) we run at We Call Shotgun, in France and the UK: [leadership alignment and enterprise rollouts](https://wecallshotgun.com/enterprise), an [executive programme](https://wecallshotgun.com/ai-training-c-level), and department sprints for [sales](https://wecallshotgun.com/ai-training-sales), [marketing](https://wecallshotgun.com/ai-training-marketing), [operations](https://wecallshotgun.com/ai-training-operations), [HR](https://wecallshotgun.com/ai-training-hr), [legal](https://wecallshotgun.com/ai-training-legal) and [customer support](https://wecallshotgun.com/ai-training-customer-support). The free [AI adoption audit](https://wecallshotgun.com/audit) takes eight minutes and shows which layer is missing in your company. For the scale question, [how to build an AI programme for 50, 200 or 1,000 employees](https://wecallshotgun.com/blog/programme-formation-ia-grande-echelle) covers the sizing. Four layers, one programme each Bring your org chart and the two workflows that eat the most hours. Twenty minutes with Toni or Meera. You'll leave knowing which layer of your company is missing a programme, where to start, and what a 90-day sprint on those two workflows would change. Tool-agnostic, so nobody on the call is selling you a licence. [Book a 20-minute call →](https://cal.com/wecallshotgun/ai-adoption) ## Frequently asked questions ### What is Schneider Electric's AI training programme? A four-tier AI curriculum built with Coursera and matched to roles. All employees, production-line workers included, take a mandatory foundation course. Senior management gets a programme on AI and strategy. AI experts get continuous technical learning. Transformation owners (product, process and IT owners) get tailored training to put AI into roadmaps and processes. CIO Dive reported the model on 5 October 2026. ### How many Schneider Electric employees have completed AI training? More than 140,000 employees, close to 100% of staff, completed the mandatory "AI Awareness for All" course in 2025, according to Schneider's answers to written questions for its 2026 AGM. More than 50,000 took advanced training on chatbot use, prompting and embedded AI, and 60,000 use group-provided AI tools every day. Schneider has more than 160,000 employees. ### Who leads AI at Schneider Electric? Philippe Rambach, senior vice president and chief AI officer, appointed in 2021 when Schneider created its AI Hub. The AI experts' group reports to him. Jean-Côme Renaudin directs Schneider's Data & AI School, which runs the employee learning programme. ### Why does Schneider Electric train senior managers separately? So they can lead by example. Rambach told CIO Dive that senior management teams "need special attention with specific trainings." Their programme focuses on AI and strategy, business value and organisational change, so leaders understand the value and limits of AI well enough to explain them to their teams. ### What is role-based AI training? AI training designed around what each group of employees decides and does, instead of one course for everyone. Executives learn to set direction and risk, managers learn to redesign and review their team's workflows, and each department practises on its own recurring tasks. Schneider's chief AI officer describes it as training people according to the decisions they have to make. ### Is mandatory AI training enough to drive adoption? No. A mandatory course builds a shared baseline and reach: Schneider got more than 140,000 completions. Adoption shows up when work changes, which needs leaders who use AI themselves, managers who own workflow changes, and departments that rebuild their own tasks. At Schneider, 60,000 employees use AI tools daily, a smaller number than the 140,000 who completed the course. ### How do you tailor AI training by department? Start from each department's recurring work. Time two or three workflows (hours, turnaround, rounds of review), rebuild them with AI and a human check on the team's real files, then measure the same things at 30, 60 and 90 days. Sales works on call prep and proposals, finance on close commentary, support on ticket triage, operations on scheduling and procedures. ### How can a mid-size company copy Schneider's four-tier model? Keep the four layers and shrink the format. Give everyone a short shared foundation and the company's AI rules. Run a leadership alignment day with the executive committee. Give heads of department and team managers their own programme, since they own the workflows. Then run department workflow sprints, and let a small group of builders and champions take on custom assistants and agents. ### Does the EU AI Act require AI training for employees? Article 4 of the EU AI Act has applied to providers and deployers of AI systems since 2 February 2025, and national authorities have supervised it since 3 August 2026. Since the Digital Omnibus, it requires measures to support staff AI literacy. No certificate is required. Our reading of what's expected includes role-based training, an inventory of AI use, an internal policy and records of what was done. ## Sources and further reading - [How Schneider Electric is bridging the AI literacy gap](https://www.ciodive.com/news/schneider-electric-ai-literacy-gap/832179/), Roberto Torres, CIO Dive, 5 October 2026 - [Schneider Electric's Playbook for Scaling AI](https://www.cio.inc/schneider-electrics-playbook-for-scaling-ai-a-32754), Jennifer Lawinski, CIO.inc, 4 September 2026 - [Schneider Electric CAIO on Why AI Transformation Is Largely Not About AI](https://www.cdomagazine.tech/aiml/schneider-electric-caio-on-why-ai-transformation-is-largely-not-about-ai), CDO Magazine, March 2026 - [AI That Doesn't Scale Doesn't Matter: Schneider Electric CAIO Explains Why](https://www.cdomagazine.tech/aiml/ai-that-doesnt-scale-doesnt-matter-schneider-electric-caio-explains-why), CDO Magazine, 2026 - [Answers to written questions, 2026 Annual General Meeting](https://www.se.com/ww/en/assets/pdf/2026-AGM-questions-ecrites-written-questions), Schneider Electric - [Company profile](https://www.se.com/ww/en/about-us/company-profile/), Schneider Electric - [How Schneider Electric Scales AI in Both Products and Processes](https://sloanreview.mit.edu/article/how-schneider-electric-scales-ai-in-both-products-and-processes/), Thomas H. Davenport and Randy Bean, MIT Sloan Management Review, 16 March 2026 - [How Schneider Electric Drives Success with the Learn, Act, Advocate Framework](https://www.coursera.org/enterprise/articles/learn-act-advocate-schneider-electric-cm), Coursera - [Schneider Electric acculture ses 150 000 collaborateurs à l'IA](https://edtechactu.com/digital-learning/schneider-electric-acculture-ses-150-000-collaborateurs-a-lia/), EdtechActu, 18 April 2025 - [Stellantis, Thales, Schneider Electric : comment les industriels forment leurs salariés à l'IA générative](https://www.usinenouvelle.com/editorial/stellantis-thales-schneider-electric-comment-les-industriels-forment-leurs-salaries-a-l-ia-generative.N2213814), L'Usine Nouvelle, 2024 - [Schneider Electric advances its AI strategy with appointment of Chief AI Officer and creation of new AI Hub](https://www.se.com/ww/en/about-us/newsroom/news/press-releases/schneider-electric-advances-its-artificial-intelligence-ai-strategy-with-appointment-of-chief-ai-officer-and-creation-of-new-ai-hub-617aa598b7359463ac1f3144/), Schneider Electric, 2021 - [What we've learned from Microsoft's own AI transformation](https://blogs.microsoft.com/blog/2026/09/17/what-weve-learned-from-microsofts-own-ai-transformation/), Kathleen Hogan, Official Microsoft Blog, 17 September 2026 - Toni Dos Santos, [Teach Them to Drive: The AI Adoption Playbook for Teams](https://www.amazon.com/dp/B0GYSSFNPK/ref=tmm_pap_swatch_0) **About the author.** [Toni Dos Santos](https://wecallshotgun.com/toni-dos-santos) is co-founder of We Call Shotgun, an AI adoption practice for teams in the UK and France, with Meera Sanghvi. He wrote [Teach Them to Drive: The AI Adoption Playbook for Teams](https://wecallshotgun.com/teachthem). Before that he worked in corporate banking at Crédit du Nord (Société Générale), ran B2B product marketing at Banque BCP, and was a B2B product manager at lemlist. ## Keep Reading [AI Tools Oct 30, 2026 Microsoft Copilot Notebooks for teams: how to replace scattered chats with one shared workspace (2026 guide) Copilot Chat starts every conversation from zero, and a team's best prompt lives in one person's notes file. A Copilot Notebook, the shared workspace Microsoft also calls a project workspace, keeps the references, the instructions and the outputs for one piece of work in one place. 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Every figure with what it counts, what the ONS and DSIT data add, what Teach Them to Drive says about budget without strategy, and the six-step sequence that turns a budget line into a measured workflow. 21 min read Read →](https://wecallshotgun.com/blog/uk-ai-spending-strategy-governance-sap-2026) [AI Tools Oct 21, 2026 What Can ChatGPT Enterprise Do Beyond Writing Emails? 5 Features to Use at Work Five ChatGPT Enterprise features for the work around the email: Projects for the brief you keep repeating, scheduled tasks for the weekly check you run by hand, skills for the prompt your team keeps re-pasting, the browser extension for pages you keep copying, and deep research for cited decision briefs. Each with a copy-paste prompt and the caveat from OpenAI's own documentation. 19 min read Read →](https://wecallshotgun.com/blog/chatgpt-enterprise-features-for-work) ## Related AI Training Solutions Programs tailored to your role, industry, or function. 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