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EYA-F01Continuous training programme

Digital Transformation & Applied AI

Master digital transformation and deploy AI in the enterprise

Duration
21 hours (3 days)
Quote response lead time
24 working hours
Training start lead time
First start available 7 to 30 days after signing the agreement (subject to scheduling). Agreement signed ≥ 7 working days before D1.
Format
Blended Learning (50% in-person + 50% online)
Group size
12 participants maximum
Location
On-site, in-person Paris or online
Language
French (English on request)

Access conditions

  • ▸Personalised quote within 24 working hours
  • ▸Training agreement signed by both parties
  • ▸Prior positioning test (≥ D-5)
  • ▸Preparatory documents (programme, welcome booklet, internal rules) provided before start

Lead times to training

  • ▸Agreement signed ≥ 7 working days before training start
  • ▸First D1 available 7 to 30 days after signing the agreement (subject to scheduling and funding)
  • ▸Average cumulative lead time: 14 to 30 days between first request and training start

Evaluation methods

  • ▸Entry positioning test (self-assessment + quiz, ≥ D-5)
  • ▸Formative quizzes during session (D1, D2, D3 depending on duration)
  • ▸Individually graded deliverable (validation threshold 65/100)
  • ▸End-of-session evaluation questionnaire (D0)
  • ▸Follow-up evaluation questionnaire (D+90 — field impact)
  • ▸Attendance certificate and realisation certificate provided at end

Overview

A hands-on training to frame a digital transformation strategy and identify concrete AI levers in your industry.

Learning objectives

  • Master the stakes and components of enterprise digital transformation
  • Identify and assess AI use cases in your industry
  • Design a digital transformation roadmap tailored to your context
  • Drive the organisational change induced by digitalisation

Detailed programme

01

Digital transformation fundamentals

4h

Definition and scope. The 4 dimensions: technology, processes, data, people. In-depth analysis of transformed enterprise models (real cases: banking, insurance, public sector). Strategic stakes, risks and key success factors.

02

Applied AI: from theory to use cases

6h

AI technology landscape: Machine Learning, NLP, Computer Vision, Generative AI, AI agents. Sector-specific use cases (banking, insurance, public sector, industry). Extended hands-on workshop: mapping + prioritisation of AI opportunities in your company.

03

Roadmap & Transformation architecture

6h

Digital Maturity Model framework. 12-24 month roadmap construction. Programme governance, KPIs, adoption indicators. Technology choices: cloud, data platform, integrations. Workshop: co-building a tailored roadmap.

04

Change management & adoption

5h

Human levers of transformation. ADKAR / Kotter models. Managing resistance and stakeholders. Communication, internal training, support. Building a data-driven culture. Real case study: change management on an AI project.

Evaluation & follow-up

Entry positioning quiz (15 min). Pair case study delivered at end of D2. Post-session evaluation questionnaire (satisfaction + learning). Individual attendance certificate.

Pedagogical resources

Interactive slide decks, real case studies from 67 field projects (banking, insurance, public sector, transport). Online AI tools (live demos). Digital resource materials.

Trainer qualification

Expert Trainer — Computer Science Engineering Degree (ENSI 2006), MSc MIDO Intelligent Systems Paris-Dauphine (2008). 20+ years of experience in digital transformation, AI and IS architecture.

Page last updated on : 08/05/2026