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Artificial intelligence training · Product Owners and Product Managers

AI Training Program for Product Owners and Product Managers

This two-day training course enables Product Owners and Product Managers to integrate artificial intelligence concretely into their product practices.

Duration
2 days (14 h)
Inter-company fee
Inter-company training: EUR 1500 excluding VAT for 2 days.
Programme and practical details Download the PDF programme

Artificial intelligence training

Upcoming sessions

These inter-company sessions run from the first confirmed registration.

  1. Maison des Lois, 2 impasse Michel Labrousse, 31100 Toulouse
    • 14 hours
    • €1500 excl. VAT
    Pre-register
  2. Maison des Lois, 2 impasse Michel Labrousse, 31100 Toulouse
    • 14 hours
    • €1500 excl. VAT
    Pre-register
  3. Maison des Lois, 2 impasse Michel Labrousse, 31100 Toulouse
    • 14 hours
    • €1500 excl. VAT
    Pre-register

General information

AI training for Product Owners and Product Managers

This two-day training course enables Product Owners and Product Managers to integrate artificial intelligence concretely into their product practices. It shows how to use AI to frame an opportunity, analyze an existing product, produce product deliverables, prototype quickly and make better decisions, while keeping the right vigilance reflexes regarding the AI Act, the European regulation on artificial intelligence, confidentiality and human control. Participants work on realistic product cases or on a context provided by the company for in-company sessions, so that they leave with a directly reusable method.

Objectives and target skills

  • Identify relevant AI uses for a Product Owner or Product Manager by distinguishing real gains, limits and risks.

  • Accelerate product framing with AI: need, personas, journeys, value hypotheses, success criteria and initial backlog.

  • Produce and improve product deliverables: product brief, user stories, acceptance criteria, MVP, roadmap, decision support and documentation.

  • Prototype a solution quickly to test an idea, collect feedback and adjust scope before full development.

  • Use AI as product decision support: prioritization, competitive analysis, pricing, business projections and responsible use.

Audience

Product Owners, Product Managers, product managers, product project managers, innovation managers or product marketing managers.

Prerequisites

Experience in product management, digital project management, innovation or product marketing. No advanced technical development prerequisite. For in-company sessions, participants should, if possible, bring a product idea, backlog, prototype or business topic to work on.

Duration

2 days (14 h)

Training content

Understand AI applied to product work

  • Essential vocabulary: generative AI, LLMs, agents, RAG, specialized assistants.

  • Tools that can be used according to company use cases and constraints: Claude Pro, Codex, Obsidian, conversational assistants, prototyping tools and knowledge bases.

  • What AI really changes in PO/PM practices.

  • Difference between one-off assistance, reusable workflow and automation.

  • Limits: data quality, hallucinations, confidentiality, bias, responsibility and essential AI Act reference points.

Choose the right AI uses for a product context

  • Identify product tasks that can be accelerated by AI.

  • Assess the value, feasibility and risk of a use case.

  • Build a decision grid for using AI, or choosing not to use it.

  • Define confidentiality, human validation and AI Act vigilance rules.

  • Prepare a work environment suited to the company’s context.

Frame a product opportunity with AI

  • Clarify the business need and user problem.

  • Reformulate an idea into a value proposition.

  • Produce a usable product brief.

  • Identify stakeholders, users and pain points.

  • Define measurable objectives and success criteria.

Produce personas, journeys and value hypotheses

  • Generate and challenge personas.

  • Describe user journeys and key moments.

  • Identify pain points, expected gains and adoption risks.

  • Turn hypotheses into verifiable elements.

  • Prepare interview or user-test questions with AI.

Build the MVP, backlog and specifications

  • Define the scope of an MVP.

  • Turn a product intent into epics, user stories and acceptance criteria.

  • Prioritize by value, risk, dependencies and estimated effort.

  • Use AI to detect omissions, contradictions and ambiguities.

  • Prepare a short and readable roadmap.

Analyze an existing product and document with AI

  • Use AI to understand an existing product, process or codebase.

  • Produce a functional summary from documents or discussions.

  • Generate diagrams and maps useful for framing.

  • Identify areas of uncertainty and questions for experts.

  • Turn analysis into product decisions.

Prototype a solution quickly

  • Move from an idea to a testable prototype.

  • Use AI to produce screens, texts, sample data and scenarios.

  • Iterate on the prototype from feedback.

  • Prepare a short and structured demonstration.

  • Define what should be kept, discarded or industrialized.

Test, deploy and collect feedback

  • Organize a first user validation.

  • Prepare test scenarios and observation criteria.

  • Deploy or share a prototype according to the technical context.

  • Collect, summarize and prioritize feedback.

  • Decide on the next iterations.

Assess the market, positioning and pricing

  • Search for comparable offers with AI.

  • Compare strengths, weaknesses, features and promises.

  • Identify differentiators and positioning angles.

  • Build a first pricing hypothesis.

  • Produce a simplified forecast or decision note.

Industrialize AI practices in the product team

  • Capitalize useful prompts, templates and workflows.

  • Define shared usage rules in the team.

  • Work with developers, UX, business stakeholders and sponsors.

  • Secure the quality of product deliverables through human review.

  • Build a progressive adoption plan.

Exercises and deliverables

  • Framed product brief.

  • Personas and user journeys.

  • Value hypotheses and success criteria.

  • MVP, initial backlog, user stories and acceptance criteria.

  • Functional prototype or usable mockup.

  • Short documentation and diagrams.

  • Competitive analysis and first pricing hypotheses.

  • Responsible AI usage checklist for PO/PM.

  • Action plan to reuse the method after the training.

In-company adaptation

For in-company sessions, the training can be adapted to the company’s context: existing product, idea to frame, backlog to improve, prototype to build or product process to equip. A short upstream framing phase identifies priority use cases, confidentiality constraints, authorized tools and expected deliverables.

This adaptation turns the training into an operational workshop: exercises do not remain generic and can produce elements directly usable by the participant or team.

Access conditions

Registration lead time: from 2 months to 1 week before the training starts, subject to available seats and scheduling constraints.

See the General Terms and Conditions of Sale: https://www.opcoach.com/cgv.

Registration is completed on the OPCoach website using a link provided in the invitation. This registration collects information about the participant, their professional environment, role, expectations and prerequisites before the training starts.

Accessibility for people with disabilities

People with disabilities may have specific accessibility needs to attend the training. Please contact us so that we can discuss suitable arrangements.

Training format

On-site or remote training.

Fees

Inter-company training: EUR 1500 excluding VAT for 2 days.

In-company and custom training: please contact us.

Group size

From 1 to 8 participants, on site or remotely.

Schedule

Schedule available on https://www.opcoach.com/.

Training location

Inter-company training takes place in our InterIndep premises at 2 impasse Michel Labrousse, 31100 Toulouse. The training room is accessible by public transport and by car, and has parking facilities. Several restaurants and a hotel are located nearby. A break area is available for cold and hot drinks during breaks. All these facilities are accessible to people with reduced mobility.

In-company training is preferably delivered at the client’s premises. Hosting conditions are validated before the training.

Remote training is delivered with Zoom and can be organized as inter-company or in-company training.

Teaching approach

Alternating short lectures and individual hands-on exercises on a workstation. Sharing and discussion of the results obtained.

Teaching resources

On site: training room with video projector, whiteboard, high-speed Wi-Fi and a training binder provided to the participant.

Remote: high-speed internet access, webcam, free Zoom software, PDF course material sent to the participant. One workstation per participant.

Trainer supervision

Olivier Prouvost, DEA in Computer Science, recognized open source expert and trainer for more than 20 years, developer of AI solutions to optimize SMEs, speaker at international conferences, Eclipse committer on several projects, founder of OPCoach, a Qualiopi-certified training organization since 2020, and ICPF & PSI certified expert trainer and consultant.

Learning assessment

Continuous assessment through the completion of the practical exercises, leading to the creation of a functional prototype.

Recognition

A certificate of skills is provided to the participant.

Satisfaction assessment

At the end of the training, the participant completes a satisfaction survey and takes part in a group feedback session. The participant benefits from unlimited email support for practical questions related to the training. After 3 months, or after applying the training in the workplace, a follow-up questionnaire is completed to assess practical use.

Technical, teaching, administrative and financial contact

Olivier Prouvost, +33 6 28 07 65 64, contact@opcoach.ai